effective demand response management in a low...

MURDOCH UNIVERSITY

School of Engineering and Information Technology

Bachelor of Engineering Honours

2016

Effective Demand

Response Management in a

Low Voltage Grid

By: Mohammad Essarras

Thesis Supervisor: Dr. GM Shafiullah

Unit Coordinator: Prof. Parisa Bahri

Declaration

This thesis is presented for the award of a Bachelors of Engineering Honours degree

in Electrical Power and Renewable Energy at Murdoch University. I declare that the

work presented in this report is of my effort and that all sources used in the

preparation of this report have been cited and acknowledged to the best of my ability.

Name:

Signature:

Date:

Abstract

This project investigates the application of demand response on a low voltage grid

with a comparison between traditional and effective demand response strategies to

minimise the voltage violations in a network. For the project, a low voltage grid was

constructed using the DIgSILENT PowerFactory 15.2 power systems analysis

software. The low voltage grid built represents a common low voltage Australian

distribution grid. This was achieved by using standards, technical manuals, and

literature related to Australian distribution networks. Six different scenarios were

considered to examine the performance of demand response on the constructed grid.

Only two scenarios required the use of demand response; the grid under peak loading

condition and the grid under average loading condition with future PV penetration

values. For the peak loading condition, the voltage limits were breached with a

minimum bus voltage of 0.93 Vp.u. The traditional demand response strategy equally

reduced the 22 loads in the network from a scaling factor of 1.00 to 0.839. This

resulted in a total load reduction of 35.4 kW which equated to a 16.1% load

reduction. The effective demand response strategy reduced only 4 loads by a total of

23.8kW which equated to a 10.8% reduction of the total load.

For the average load with future PV generation values condition, voltage limits were

breached with a maximum bus voltage of 1.072 Vp.u. The traditional demand response

strategy reduced the PV generation uniformly from a scaling factor of 1.00 to 0.874.

This resulted in a total PV generation reduction of 27.72 kW which equated to 12.6%

and was distributed between 22 PV systems. The effective demand response strategy

reduced the PV production of 4 PV systems by a total reduction of 26.07kW which

equated to 11.85 %. The results showed that using an effective demand response

management with a direct load control strategy is a more efficient solution than using

a traditional demand response strategy.

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Table of Contents

Declaration.............................................................................................................................. i

Abstract .................................................................................................................................. ii

Acknowledgement ................................................................................................................. v

Acronyms and Abbreviations ............................................................................................... vi

Chapter 1- Introduction ..................................................................................................... 1

1.1 Overview ................................................................................................................. 1

1.2 Background ............................................................................................................. 1

1.3 Objective ................................................................................................................. 4

1.4 Project Outline ........................................................................................................ 4

1.5 Significance of Project ............................................................................................ 5

Chapter 2- Literature Review ............................................................................................ 6

2.1 Overview ................................................................................................................. 6

2.2 The current and future Australian utility grid design.............................................. 6

2.3 Demand response (DR) ........................................................................................... 7

2.4 LV Australian network ........................................................................................... 8

2.4 DIgSILENT PowerFactory ................................................................................... 11

2.5 Power flow simulation .......................................................................................... 12

2.6 Sensitivity analysis ............................................................................................... 12

2.7 The current state of the Australian Grid ............................................................... 13

2.8 The predicted future of the Australian grid........................................................... 14

Chapter 3- Methodology .................................................................................................. 15

3.1 Overview ............................................................................................................... 15

3.2 Project structure .................................................................................................... 15

3.3 Grid construction using DIgSILENT PowerFactory 15.2 .................................... 16

3.4 Scenario characterization ...................................................................................... 19

3.4.1 Scenario 1: Average load condition .............................................................. 19

3.4.2 Scenario 2: Peak load condition .................................................................... 20

3.4.3 Scenario 3: Average load condition with current PV penetration values ...... 20

3.4.4 Scenario 4: Average load condition with future PV penetration values........ 21

3.4.5 Scenario 5: Peak load condition with current PV penetration values............ 21

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3.4.6 Scenario 6: Peak load condition with future PV penetration values ............. 22

3.5 Scenario simulation ............................................................................................... 22

3.6 Traditional DR ...................................................................................................... 22

3.7 Effective DR management .................................................................................... 23

3.8 Traditional and Effective DR flow charts ............................................................. 25

Chapter 4- Results and Analysis ...................................................................................... 26

4.1 Overview ............................................................................................................... 26

4.2 Results ................................................................................................................... 26

4.2.1 Scenario 1: Average load condition .............................................................. 26

4.2.2 Scenario 2: Peak load condition .................................................................... 27

4.2.3 Scenario 3: Average load condition with current PV penetration values ...... 31

4.2.4 Scenario 4: Average load condition with future PV penetration values........ 32

4.2.5 Scenario 5: Peak load condition with current PV penetration values............ 36

4.2.6 Scenario 6: Peak load condition with future PV penetration values ............. 37

4.3 Result Analysis ..................................................................................................... 38

Chapter 5- Conclusion ..................................................................................................... 41

5.1 Overview ............................................................................................................... 41

5.2 Conclusion ............................................................................................................ 41

5.3 Obstacles and difficulties ...................................................................................... 42

5.4 Future recommendations ....................................................................................... 43

References ........................................................................................................................... 44

Appendix A: Project grid parameters .............................................................................. 47

Appendix B: Simulation parameters and results ............................................................. 51

Scenario 1 ........................................................................................................................ 51

Scenario 2 ........................................................................................................................ 52

Scenario 3 ........................................................................................................................ 55

Scenario 4 ........................................................................................................................ 56

Scenario 5 ........................................................................................................................ 59

Scenario 6 ........................................................................................................................ 60

Appendix C .......................................................................................................................... 61

Newton-Raphson load flow equations ............................................................................. 63

Jacobian Matrix load flow sensitivity equations ............................................................. 64

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List of Figures and Tables

Figure 1: Project method structure flow chart ..................................................................... 15

Figure 2: DIgSILENT PowerFactory diagram .................................................................... 18

Figure 3: Demand response flow chart ................................................................................ 25

Figure 4: Voltage level against load scaling factor plot for feeder A buses ........................ 29

Figure 5: Voltage level against generation scaling factor plot for feeder A buses .............. 34

Figure 6: Scenario 2 Voltage VS Scaling factor plot .......................................................... 53

Figure 7: Scenario 2 Voltage VS Scaling factor plot .......................................................... 57

Table 1: Average load condition simulation results 26

Table 2: Peak load condition simulation results .................................................................. 28

Table 3: Peak load condition simulation results after traditional DR application ............... 29

Table 4: Violated buses and voltage values......................................................................... 30

Table 5: Load flow sensitivity values .................................................................................. 30

Table 6: Load reduction values ........................................................................................... 30

Table 7: Peak load condition simulation results after effective DR application ................. 30

Table 8: Average load condition with current PV penetration simulation results............... 31

Table 9: Average load condition with future PV penetration simulation results ................ 33

Table 10: Average load condition with future PV generation simulation results after

traditional DR application ................................................................................................... 34

Table 11: Violated buses and voltage values....................................................................... 35

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Table 12: Load flow sensitivity values ................................................................................ 35

Table 13: Required change in active power ........................................................................ 35

Table 14: Average load condition with future PV penetration value simulation results after

effective DR application ...................................................................................................... 35

Table 15: Peak load condition with future PV penetration simulation results .................... 36

Table 16: Peak load condition with future PV penetration simulation results .................... 37

Table 17: Project transformer parameters ........................................................................... 47

Table 18: Project transformer parameters ........................................................................... 47

Table 19: Project cable lengths ............................................................................................ 48

Table 20: Project bus parameters......................................................................................... 49

Table 21: Project loads and PV generators, locations and values ....................................... 50

Table 22: Scenario 1 parameters and simulation results ..................................................... 51


Table 24: Scenario 2 Change in bus voltage due to change in scaling factor ..................... 53

Table 25: Scenario 2 load flow sensitivities ........................................................................ 54



Table 28: Scenario 4 Change in bus voltage due to change in scaling factor ..................... 57

Table 29: Scenario 4 load flow sensitivities ........................................................................ 58



v

Acknowledgement

I would like to foremost acknowledge both my parents for their loving support and

patience throughout the course of my studies. Furthermore, I would like to

acknowledge the amazing academic staff at Murdoch University, all of which

contributed in helping me throughout the course of my study, especially my

supervisor Dr. GM Shafiullah who has supported and stood by me since the

beginning of my project and to my mentor and friend Mr. Md Moktadir Rahman

who was a source of inspiration and guidance throughout my thesis. I would like to

acknowledge my classmates who I shared ideas and knowledge with and Murdoch

University for the professionalism and dedication towards its students and staff. I

truly thank them all form my heart and wish them the very best.

vi

Acronyms and Abbreviations

AC Alternating Current

AMI Advanced Metering Infrastructure

DER Distributed Energy Resource

DC Direct Current

DG Distributed Generation

DR Demand Response

HV High Voltage

kW Kilowatt

LV Low Voltage

MEPS Minimum Energy Performance Standard

MW Megawatt

MV Medium Voltage

P Active Power

P.f Power factor

PV Photovoltaic

Q Reactive power

S Apparent power

V Volts

Vp.u Voltage Per Unit

W Watt

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Chapter 1- Introduction

1.1 Overview

This chapter addresses background information, objectives, the outline and the

significance of this project. The background information will introduce concepts,

statistics, issues faced, and strategies currently practiced. The project objectives

will outline the main aims that the project intends to achieve. The significance of

the project will highlight the motives behind this project.

1.2 Background

Electricity power systems are an essential part of the infrastructure of any modern

society. Over the past century, electricity power systems have grown in size and

capacity to meet the increasing power demand of these growing societies (Hughes,

1983). With this growth, challenges arise and one of the most confronting

challenges is meeting residential power demands. Residential power demands are

challenging as they fluctuate with great contrast. In Australia, residential power

demands can fluctuate between 25% and 45% of the total energy demand in a

given network (AEMC, 2012). In addition, residential areas are powered by low

voltage (LV) networks with high currents (AS/ACIF, 2006). These high currents

contribute to high power losses that result in a drop in the voltage levels of these

networks. In response, power producers tend to overproduce electric power to

accommodate for the power fluctuations and to prevent voltage levels from

dropping below required limits. This approach is not only inefficient due to the

increase power losses associated with increased power flowing through

transmission lines, but as 63% of this energy is generated from coal, it has a high

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contribution towards Australia’s carbon emissions (Australian Energy Update,

2016).

A viable alternative to this is to distribute the load profile to reduce the contrast

between base load demand and peak load demand through schemes such as

demand response (DR). DR helps ease the balance between supply and demand by

involving the consumer to participate in reducing electricity power consumption at

peak load periods, and thus acting as a peak shaver to the load profile. The

traditional DR schemes being used today involve price based or incentive based

programs which only encourage the consumers, and thus could have a reliability

factor left unaddressed in the event of the consumers not being persuaded into

responding to the demand (U.S Department of Energy, 2006). In addition, these

programs targeted peak shaving of peak loads in a conventional electric system

built on the foundation of a unidirectional power flow. However, with the

introduction and recent increase in distributed generation (DG) in electricity grids,

the foundation on which these conventional electricity distribution systems were

built has started to change (Cappers, 2016).

This change has raised questions over the integration of DG into electricity

distribution systems, especially renewable distributed energy resources (DER),

which are growing rapidly due to economic, political and environmental factors

worldwide (Purchala, 2010). This concern is due to the intermittent nature of

renewable DER’s which not only change the power flow from unidirectional to

bidirectional, but do this at an unpredictable and rapid rate (ARENA, 2015). This is

a growing concern in Australia as it currently has the highest residential PV

penetration levels of 16.2% and is predicted to continue growing, with some

suburbs in Brisbane and Adelaide currently reaching 50% PV penetration

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(Australian Energy Council, 2016). The concern is that these residential DER’s

collectively can impact the electricity network grid significantly with no

administration or oversight from grid operators (Mauch, 2006). New schemes such

as the Advanced metering infrastructure (AMI) have been introduced to combat

this obstacle, it is now shifting the conventional grid and transforming it into a

modern “Smart Grid”, this has the ability to facilitate the required communication

between the grid operators and consumers (Wolfs, 2009). Similarly, this

advancement can be used in conjunction with the traditional DR and transform

traditional DR into an effective modern DR that can be managed to work in

conjunction with the modern smart grid. This will allow DR to achieve better

results when reducing the load in peak load periods, as it gives operators the ability

to target the most effective nodes in any given network. In addition, this opens a

new door for operators to monitor and manage residential PV power flow in today's

bi-directional power flow grid.

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1.3 Objective

The objective of this project is to investigate the difference between using a

traditional DR in comparison to an effectively managed DR on an Australian LV

residential network. In addition, this study will also investigate the use of an

effectively managed DR on residential PV to illustrate its viability and potential in

a modern bidirectional power flow grid.

1.4 Project Outline

- This project will begin by introducing the literature review and the studies

the project was based on.

- The methodology of the project will be explained in detail, including the

methodologies for grid construction, scenario characterization, and the

scenario simulation process.

- The results of the simulated scenarios will be presented with the discussion

of the outcomes in relation to the objectives of this project.

- The conclusion, obstacles faced and future recommendations will conclude

this report.

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1.5 Significance of Project

Utility grids are one of the largest and most complex networks known to mankind.

As demand for energy grows and the fundamental design on which utility grids

were built on changes, utility grids are under threat of having to be redesigned and

reconstructed. To upgrade or change the entire infrastructure of these large-scale

networks would mean a devastating blow to any economy. This would not only

affect utility providers and shareholders, but would also burden the consumers as

electricity prices would have to rise to compensate for the colossal changes. This

has pushed for a large investment into innovation for means to avoid such an event.

Demand response has been a cost effective and successful scheme for many

decades practiced by utility grids worldwide. However, as the centralized grid

changes towards becoming a more DER intensive grid, DR needs to adapt to the

changes and prove that it can remain to be a useful tool in utility grids. Therefore,

this project aims to improve the use of DR and provide a foresight to the potential

it holds in the near future by investigating current and future scenarios.

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Chapter 2- Literature Review

2.1 Overview

This chapter addresses the literature on which this project was built on. This

chapter will also address the Australian standards and technical guides for the

requirements and parameters of an LV Australian grid. The software manual for

DIgSILENT PowerFactory 15.2 will be examined for the clarification of the

simulation process.

2.2 The current and future Australian utility grid design

The current conventional Australian utility grid is made up of 3 main elements:

generation, transmission, and distribution. This type of grid has been dominant

over the past century. The fundamentals of this design consisted of a large

centralized generation unit that supplied the demand required by the consumers

connected to its grid. This design accommodates a reserve margin for the

continuously fluctuating power demand. The central generation units are required

to maintain a reserve margin (or reserve capacity) to readily meet any sudden rise

in power demand. The power flow in this type of grid is described as a

unidirectional power flow, as the power flows from production to consumption

(Lasster, 2003).

In the near future, this conventional design will start to shift due to two main

factors. The first is due to the depleting reserve capacity in transmission lines as the

utility grid and power demands grow (Lasster, 2003). The second is the increase in

DER’s which is causing the utility grid to shift from the conventional

unidirectional power flow to a bidirectional power flow grid which allows the

7

consumption end of the network to produce power and inject it back into the larger

network body (Lo, 2013).

2.3 Demand response (DR)

DR is a strategy that reduces energy consumption at peak demand periods in a

network. This is done by encouraging consumers in reducing or shifting their

electricity demand during peak load periods in response to time-based rates or

financial incentives. The traditional DR strategy consisted of time-based rates that

offered consumers time-varying rates that vary with the value of electricity in

different time periods. This often encouraged the consumer to shift electricity

usage to less costly periods outside peak demand (U.S Department of Energy,

2006).

A more effective strategy is the incentives strategy which encourages consumers to

participate in programs that reduce their loads upon request by a program sponsor

often referred to as an "Aggregator." Participating consumers agree to respond with

load reduction upon request from the aggregator at high electricity demand periods

in return for a financial incentive. This strategy often involves a direct load control

approach in which the aggregator has direct control over certain consumer

equipment (U.S Department of Energy, 2006). This form of DR is referred to in

this project as an effectively managed DR strategy as it involves an aggregator or a

grid operator to manage the DR efficiently and thus has a more effective approach

to restoring voltage limits.

For the direct load strategy the current traditional grid needs to upgrade into a

smart grid. The smart grid has an integrated two-way communication system

between the power producer and the power consumer. These grids rely on the

8

integration of an AMI (Advanced Metering Infrastructure) where smart meters are

installed to provide grid operators with better visibility into lower voltage networks

at the distribution end of the grid. This enables power producers to monitor power

consumption in real time which in turn allows better energy production and

delivery management (Hossain, 2013)

AMI is a system that allows two-way communication between consumers and

utilities. The network requires the installation of "Smart meter" at the user end. The

smart meter communicates by sending packages of information at short time

intervals to the utilities. This is a vital part of the smart grid and provides vision for

grid operators into the consumer ends of the network (U.S Department of Energy,

2015).

2.4 LV Australian network

Electricity grids around the world share the concept of distributing their power to

consumers by using LV grids. Interchangeable with LV network, an LV grid is a

grid that operates on voltages of up to 1000V AC. The LV grid is the last level in

the electricity grid structure which begins with the power generation at the power

plant. LV grids supply power to residential, commercial and industrial entities

(Siemens, 2016).

Low voltage networks distribute the power received from HV or MV transmission

lines by stepping down the voltage using transformers which consumers can then

use to run their equipment and loads. In Australia, any voltage up to 1000V AC is

considered a low voltage. However, most Australian low voltage grids deliver

power using 415V in a three-phase configuration or 240V single-phase.

Regulations and standards have been put in place to ensure the safety and stability

9

of running these grids. These standards and regulations differ between utility

operators. In this project, the standards and regulations used in Western Australia,

regulated by Horizon Power and Western Power were used as a reference.

Horizon Power and Western Power own and operate the grids in the North-West

interconnected system (NWIS), the South-West interconnected system (SWIS) and

the non-interconnected system (NIS) and has placed regulations and standards for

these grids (Horizon Power, 2015). The LV networks within those grids consist of

overhead and underground networks. Horizon Power has specified that all future

LV networks will be built as underground LV networks unless within an area

where overhead cables are still in use. Standards have been put in place to regulate

each one of these LV network types. In recent years as PV systems have become

increasingly popular, standards and manuals have been revised to address the

changes and their effects on Australian LV networks. For this project, these

manuals and standards have been studied to gather the necessary parameters for

constructing an LV grid that resembles a common LV network in Australia. From

the Western Power technical rules (Western Power, 2016), Western Power

distribution connections manual (Western Power, 2015), Australian standard for

power transformers (AS 2374.1.2:2003, 2016), Horizon Power distribution design

manual (Horizon Power, 2014), Horizon Power technical rules (Horizon Power,

2013), and Australia and New Zealand standard for electrical installations

(AS/NZS 3008.1.1:2009, 2009), it was found that in Western Australia for a SWIS

LV network the operation conditions are as follows:

-The system supply is to function within 2.5% of the system nominated frequency

of 50 Hz.

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-The permitted voltage levels at any given node in the network must be within the

limits of 6% of the standard supply voltage.

-Distribution systems must be designed to supply the maximum load for the area

served while considering changes in the foreseeable future.

-Liquid cooled distribution transformers of a 200kA size require a minimum of

98.73% efficiency rating.

-Distribution transformers may operate to up to 1.4 of their maximum rating.

-Consumer loads are measured in their active power values.

-Power factor requirement for consumer loading in Western Australia is no less

than 0.8. However, it is a requirement by most distributors that the P.f remains

between 0.9 and 0.95.

-A load power factor correction device is to be installed with loads below 0.8 P.f.

-Most PV system outputs have a power factor output of 1.

-Cables supplying an LV network will have a three-phase configuration of ABC-N.

-Cable loadings allow a tolerance of 10% minimum.

-In an LV distribution network all residential, commercial and industrial

installations supplied are to be within 500m from the distribution transformer.

-Cable de-rating factor of overhead cables with more than 600mm spacing is 1.

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2.4 DIgSILENT PowerFactory

DIgSILENT PowerFactory is a power systems analysis software used to simulate

networks for the applications of generation, transmission and distribution of power.

It is the preferred program in grid operations by Western Power. The DIgSILENT

PowerFactory manual was a vital tool in understanding the calculation methods

used by the program for analysis purposes. The manual was used as a reference in

carrying out the grid construction and scenario simulations. It showed the technical

background including the equations used. DIgSILENT PowerFactory uses the

Newton-Raphson power equations for load flow calculation and the Jacobian

Matrix for load flow sensitivity calculation. From the user manual, the following

was extracted:

-Loads under normal conditions were modeled as general loads where the P and Q

are constant without voltage dependency.

-The load scaling factor can be adjusted manually at each load or collectively by

using the load scaling factor entry when calculating load flow.

-The calculation method to be used in a balanced grid is a positive sequence AC

load flow.

-The generation scaling factor can be adjusted manually at each PV generator or

collectively by using the generation scaling factor entry when calculating load

flow.

-The active and reactive powers of loads and generators will be scaled equally.

-Load flow analysis can be calculated for diagonal elements or to a single bus bar.

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2.5 Power flow simulation

Power grids are complicated networks with expensive equipment connected to

serve the purpose of delivering high amounts of electric power. It would be costly

and dangerous to make alteration to a grid based on a trial and error approach.

Therefore power flow simulation tools are used to predict the performance of a

power system in the real world. This is performed by using numerical and complex

calculation methods. The Newton-Raphson algorithm (see Appendix C) is a

common numerical technique used for solving non-linear equations in power flow

simulations. This method uses sequential linearization and iterations of multi-

variables to reach solutions.

2.6 Sensitivity analysis

The power flow sensitivity analysis determines the effect of an independent

variable on a dependent variable under certain conditions. The sensitivity analysis

of a model investigates the potential changes and the results of these changes to

optimize the outputs of the model. In any system, the optimal version of that

system is always preferred as it means the best potential use of that system is in

effect (Pannell, 1997). Electricity distribution grids are constantly striving to

achieve maximum efficiency in its operation; therefore, a sensitivity analysis is

vital to the optimization of a distribution grid as a large portion of the losses occur

in the transmission and distribution. Sensitivity analysis of a grid contributes

positively towards the overall performance of the grid. It does so by taking full

advantage of the maximum available resources and selecting the most viable

technical parameters. The sensitive analysis of a system also helps illustrate the

constraints and limits of the system components. The Jacobian matrix (see

13

Appendix C) is a mathematical approach used to calculate the sensitivities of the

bus voltages in power distribution systems. It uses iterations to the change in active

and reactive power to calculate the change in voltage for a specific bus. This

enables an accurate prediction of bus voltage performance of the voltage of a bus

relative to changes in power demand.

2.7 The current state of the Australian Grid

The current state of the Australian grid is important as it currently delivers power

to more than 20 million people across Australia. Australia currently produces 3

times the amount of energy that it currently consumes (Office of the Chief

Economist, 2016). The surplus reserve capacity found in the SWIS network

between the years 2016 and 2017 was 23% (Department of Finance Public Utilities

Office, 2016). This is a troubling statistic as the yearly energy consumption rise in

Australia does not exceed 2%. Only 14% of the electricity generated in Australia

comes from renewable energy resources in comparison to almost 63% coming from

coal. Australia is a solar rich country with almost 65% yearly sunny days. Also,

with the dropping prices in PV system installations, many Australian consumers

are installing PV systems with an average size being 5 kW. This has made the

average residential PV penetration levels in states such as Queensland reach 30%

with some networks reaching as high as 50%.

The current peak to average demand ratios present in Australian LV networks

range between 1.61 and 2.7 (Utility Magazine, 2015). Supplying electricity with a

large difference in demand ratios requires ramping down or ramping up electricity

generator outputs. This can be difficult with coal electricity generators as they are

not quick in changing their generation speeds. This could be concerning as it leads

to power quality issues. Also with the expansion of the grid and increase in loading

14

the reserve capacity is depleting and thus this strategy of over producing electricity

cannot last. Other more effective strategies are being implemented or developed.

The demand response strategy of time-based rates has been used for decades and

has proven to be effective. Other more effective strategies are in their development

stages. The use of aggregators and direct load control are slowly expanding with

the first step of installing smart meters being implemented. All new connections are

fitted with the smart meters. The overall current state of Australian LV grids is

stable with power outages only occurring in sever conditions.

2.8 The predicted future of the Australian grid

For the future of the Australian grid renewable DER’s are being studied closely as

a viable alternative to the extensive coal energy production option currently being

used. The expected forecast for coal energy consumption is a 2% drop in the next

10 years. Renewables on the other hand are expected to increase by 2.1% (Office of

the Chief Economist, 2016). The annual growth of all sectors in energy

consumption is expected to rise by only 1% (Office of the Chief Economist, 2016).

The cost of electricity is expected to continue increasing with distribution network

costs being the major contributor. The peak demand to average demand ratio is also

expected to grow and plays a major role in increasing electricity prices. Residential

PV generation systems are expected to grow with a steeper incline as PV prices

continue to drop. Studies are currently being conducted on battery installations and

micro grid development especially in rural areas.

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Chapter 3- Methodology

3.1 Overview

This chapter explains the methodology of the project. The structure of the project is

addressed and defines the steps taken in accomplishing this project. The grid and

the construction process are then illustrated. The methods for scenario building and

execution are defined. This is followed by an explanation of the process of

applying demand response and effective demand response management.

3.2 Project structure

The project was built by initially investigating methods addressed in the literature

review. A model was then constructed and scenarios were designed to represent the

current and future states of LV networks in Australia. Simulations were run and

adjustments were made. Results were then recorded and used for the discussion and

recommendations for future projects.

Figure 1: Project method structure flow chart

Literature review Scenario

characterisation

Project topic

Model

construction

Scenario

simulation

Result analysis Result discussion Conclusion

Recommendation

16

3.3 Grid construction using DIgSILENT PowerFactory 15.2

The structure of the LV network grid (see figure 3) was constructed based on the

guidelines specifications and standards of the following:

1- Western Power distribution connections manual (WADCM) 2015.

2- Western Power technical rules 2016.

3- Australian standard for power transformers (AS 2374.1.2:2003) Part1.2: MEPS

requirements for distribution transformers.

4- Australia and New Zealand standard for electrical installations (AS/NZS

3008.1.1:2009) Part 1.1: Cables for AC voltages up to and including 0.6/1 kV-

typical Australian installation conditions.

5- Aerial – Nexans Olex cable catalogue.

Using DIgSILENT PowerFactory a new project was selected on which to build the

LV network. The nominal frequency of supply was selected as 50 Hz. The power

supplied to the LV grid needed to come from the greater HV or MV network of the

grid and therefore the power supply was modeled as an external grid. The present

standard voltage for an MV distribution network used in the SWIS is 22kV and this

was used as the MV end bus voltage. The external grid was connected to the MV

bus. A single 200kVA transformer was selected to step down the voltage from

22kV to 415V for the LV network. The transformer MV side was connected to the

22kV MV bus and the LV side was connected to a 415V main feeder bus. The

main feeder bus then supplied power to 4 feeders labeled A, B, C and D specifying

their designated supply areas. Feeders A, B, C and D delivered power to 7, 6, 7 and

2 LV buses respectively. Some nodes were connected to a single bus, for example

LV bus A5 was connected to a single node, others nodes were connected to 2

buses, for example LV bus A6 and A7 share the same node (see figure 2). A single

17

load and a single PV unit were connected to each LV bus. Each load was modeled

as a general 3 phase load and represented three single phase consumers. The PV

unit was modeled as a static generator. The parameters of the transformer, buses,

lines and loads were then entered for each respective element (see Appendix A).

The values of the grid components such as feeder lengths, bus loading and bus PV

generation values were kept uniform throughout the design. This ensured that the

outcomes of the application of DR were clear and that no other elements were

involved in influencing the results. Also, no other voltage manipulating means

were present as it was assumed that these means had been depleted before resorting

to DR.

The project grid built using DIgSILENT PowerFactory is presented in figure 2. The

parameters are presented in Appendix A.

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Figure 2: DIgSILENT PowerFactory diagram

19

3.4 Scenario characterization

The scenario characterization objective was to represent present and future

conditions that could be faced by a typical Australian LV grid. These scenarios

were built on the literature investigated while complying with the standards.

The scenarios considered were:

1- Average load condition

2- Peak load condition

3- Average load condition with current PV penetration values

4- Average load condition with future PV penetration values

5- Peak load condition with current PV penetration values

6- Peak load condition with future PV penetration values

3.4.1 Scenario 1: Average load condition

In this scenario, the grid was to operate under normal conditions with an average

demand for power by the loads. The purpose of this scenario was to examine the

grid performance and the parameters chosen in the grid construction. The average

loading assumed was 40% of peak demand. This value of loading was chosen as it

was extracted from the literature that the average peak to average demand ratio was

2.5 and thus the average loading was assumed as 40% of the peak demand. Also,

the transformer loading in response at this consumer loading value was close to

50%. This value also allowed some tolerance for change if the peak loading in later

conditions appeared to exceed the grid component limitations. To apply the 40%

loading the loading scale of all the buses on the grid was adjusted to 0.4 of the

maximum demand. The simulation scenario was saved and the component

20

performance values were recorded for ease of adjustments if necessary as the

scenario simulations progressed.

3.4.2 Scenario 2: Peak load condition

For the peak load scenario, the grid was required to respond to a peak demand in

power by the consumers connected to the grid. The purpose of this scenario was to

test the grid performance under maximum loading conditions. From the literature,

it was found that the loads can exceed the transformer rating under peak load

conditions. This scenario was built to overload the transformer and examine the

effects of applying DR to reduce the overload in the transformer. Due to the peak

demand to average demand ratio assumed, the peak load was simulated as 100% of

the available bus loadings. This was applied to the grid by adjusting the load scale

factor of the loads to 1. The collective power demand of the loads was checked to

be 220 kW. The simulation scenario was saved and was then run and the voltage

per-unit values were recorded.

3.4.3 Scenario 3: Average load condition with current PV penetration values

From this scenario, the requirement was to represent the current state of the

Australian LV network. A PV generation value was added to resemble the effects

of residential PV systems on the network as this was the case in the real world. The

PV penetration values were chosen to be 30%. This was assumed to be an

appropriate penetration value as values ranged between 0 and 50% in extreme

cases. This scenario presents an insight to current performance of LV networks in

Australia under the real-world conditions where PV penetration levels are taken

into consideration. This scenario was simulated by adjusting the load scaling factor

21

to 0.4 to represent the 40% average loading and the PV generation values were

adjusted to 0.3 to express the 30% PV penetration value.

3.4.4 Scenario 4: Average load condition with future PV penetration values

The objective of this scenario was to examine the effects of future PV penetration

values. As the price of PV systems drops and the price of electricity increases it

was assumed that more PV systems will be installed in the near future (Office of

the Chief Economist, 2016). The value chosen for examination was 100% PV

penetration value. This value was chosen as it represented a grid in the future

where all the consumers have a PV system installed. Also, it was assumed that the

outputs of the PV systems were equal to the maximum peak demand. This scenario

would illustrate the effects of PV systems at low power consumption times if the

PV systems were designed to meet the consumers highest load needs. This scenario

was implemented in the simulation by increasing the PV generation scale factor to

1 to equate to the 100% PV penetration value and the load was adjusted to 0.4 to

represent the average loading of 40% on the grid.

3.4.5 Scenario 5: Peak load condition with current PV penetration values

From this scenario, the requirement was to examine an Australian LV network

under full loading with the consideration of the current real world PV penetration

values. This scenario illustrates the effects of current PV generation on an

overloaded grid. This would show if the current PV generation values were

beneficial to the grid. This scenario was simulated by adjusting the load scaling

factor to 1 to represent the full loading of consumer buses and the PV generation

values were adjusted to 0.3 to express the current 30% PV penetration value.

22

3.4.6 Scenario 6: Peak load condition with future PV penetration values

For this scenario, the goal was to investigate the effects of future PV penetration

values on the current grid in peak load periods. This will allow the grid and its

components to be investigated under the maximum range of loading and

generation. The scenario was simulated by increasing both the load and generation

factors to 1. In addition to the bus voltages, the line and transformer loadings were

observed in this scenario to record any load limitation breach.

3.5 Scenario simulation

For the scenario simulation stage, the scenarios characterized for this project were

run individually on the model constructed. The scenario parameters were entered

by accessing the load and PV generation scaling factors. The simulation was then

run using the load flow calculation method. The method was selected as a Newton-

Raphson load flow classic equation. The calculation method was chosen as

balanced, positive sequence, AC load flow. The tap adjustments were removed as

the transformer was assumed to have already exhausted the available tapings. All

the other load flow calculation parameters in DIgSILENT PowerFactory were kept

standard as they are not required to be altered. The voltage per-unit values of each

bus were recorded. For the scenarios that encountered bus voltage limit violations,

the buses violating the voltage limits were specified for the implementation of

traditional DR and effective DR management.

3.6 Traditional DR

The traditional DR approach involved applying demand response in a uniform

fashion (see figure 3). This represented a time-based rate being applied to all

consumers. After the voltage violating buses were specified from the scenario

23

simulations the loads were reduced with iterations to the load scaling factor. The

load flow calculation process was repeated for each iteration. The values of the

power reduced and the voltage limits were recorded for each scaling factor. The

values of loads reduced were plotted against the voltage levels of the bus with the

largest voltage violation. A linear trend line was inserted and the equation of the

trend line identified the ratio of power reduction to bus voltage reduction. The

equation was then used to reduce the loads by a scaling factor that corrected the

voltage of the most violated bus. The values of reduced power, number of

consumers involved and the bus voltages of the network were recorded.

3.7 Effective DR management

The effective DR management approach involved applying demand response to

specific buses (see figure 3). These buses were chosen based on their effectiveness

in the rectification of bus voltage limit violations in the network. This represented

an incentive based, direct load control DR being applied to the most effective

consumers. After the voltage violating buses were specified from the scenario

simulations a load flow sensitivity analysis was performed for each of the voltage

violating buses. The sensitivity of each bus was recorded. The voltage violation

value of each bus was calculated by finding the absolute value of the difference

between the current voltage limit and the acceptable voltage limit. This value was

then multiplied by the sensitivity of that bus to attain the required change in load or

change in PV generation. As each bus had a varying effect on other bus voltages in

the network, the process of effective DR management was conducted by changing

the load or PV generation of the most effective buses. If there remained a voltage

violation in the network the second most effective bus was considered and the

process was repeated until all the buses in the network were within the desired

24

voltage limits. The values of reduced power or PV generation, number of

consumers involved and the bus voltages of the network were recorded.

25

3.8 Traditional and Effective DR flow charts

Figure 3: Demand response flow chart

Yes

No No

Yes

Start

Grid

construction

Characterize

scenario

Run load flow simulation of

scenario

Bus voltage

limits violated?

Implement traditional DR

by uniform load reduction

Start

Grid

construction

Characterize

scenario

Run load flow simulation of

scenario

Bus voltage

limits violated?

Run load flow sensitivity

Implement effective DR by

reducing loads or PV generation of

the most violated buses

End

End

Bus voltage

limits violated? Yes

No

Traditional DR Effective DR

26

Chapter 4- Results and Analysis

4.1 Overview

This chapter will present summarized simulation results from each scenario with

the interpretation and discussion. (for detailed results refer to Appendix B)

4.2 Results

4.2.1 Scenario 1: Average load condition

For the average loading condition, the assumption was made that the loadings were

at a scaling factor of 0.4. This represented the average loading of 40% on a low

voltage grid. The power factor of the loads was assumed to be 0.95 as some utility

providers require a P.f of at least 0.95. From the results, it was found that the

minimum and the maximum bus voltages were within the required limits and thus

the application of DR was unnecessary.

Table 1: Average load condition simulation results

Loads active 22

Load kW 10

Load scaling factor 0.4

Load P.f 0.95

PV active 0

Generation kW 0

Gen. scaling factor 0

Gen. P.f 0

Minimum bus voltage (LV Bus A6, A7) 0.972

Maximum bus voltage (LV Bus D1) 0.985

27

4.2.2 Scenario 2: Peak load condition

The peak load condition was assumed to be 2.5 times the average load as this was a

common average to peak load ratio. This meant a loading scale factor of 1 meaning

the loads at each bus were at their maximum of 10kW. The minimum bus voltage

measured at LV bus A6 and A7 was 0.93 Vp.u.

A traditional and effective DR was applied to the condition. For the traditional DR,

the values of voltage and load scaling factor were plotted against each other and a

trend line was inserted. A required load scaling factor of 0.839 was calculated

which meant the load had to be reduced by 16.1% from the current value. A

uniform load reduction was applied reducing all loads from 10 kW to 8.39 kW. The

simulation was run again and the minimum bus voltage was 0.94 at LV bus A6 and

A7. The same scenario was repeated but this time with the application of effective

DR. The load flow sensitivities for the buses with the most violated voltage levels

were targeted first. The buses of LV bus A6, A7, B6 and C7 had the most influence

on the grid. This meant that any change in these buses would have a more

significant effect on the grid than the same change being applied elsewhere. The

required load reductions calculated from the load flow sensitivities were found to

be 10.323, 10.323, 5.563 and 7.913 kW for buses A6, A7, B6 and C7 respectively.

Since LV bus A6 and LV bus A7 were on the same node, half the load reduction

was applied to each. The results after the effective DR application show that the

bus voltages were now within acceptable limits but the % reduction of each bus

was up to 79%. This would be impractical in a real world situation. However, less

overall load reduction was applied than the traditional DR with a better result of

0.943 for the minimum voltage. The total reduction in percentage was 10.8% for

28

the effective DR and 16.1% for the traditional DR. The effective DR also involved

fewer consumers (3 per bus) of only 12 compared to 66.

The results show that effective DR management reduces the load reduction

quantity and the number of consumers involved. However, from the effective DR

management it was found that 10.363 kW were required to be reduced from a

single bus (LV bus A6), this bus was connected to another (LV bus A7) and thus

half the reduction was required. Also 7.913 kW was required to be reduced from

LV bus C7 which was almost 80% of the load. From this result, we can see that

with the effective DR management, not all the load can be reduced from one single

bus and thus more consumers need to be involved to split the load reduction

quantity. Also, with the application of effective DR the targeted Vp.u was 0.94 and

yet the simulated Vp.u was 0.943, this was above the required amount and thus it is

evident that the effect of load reduction was amplified as more than one bus was

reduced and each bus had a secondary effect on all other bus voltages.

Table 2: Peak load condition simulation results

Loads active 22

Load kW 10

Load scaling factor 1

Load P.f 0.95

PV active 0

Generation kW 0


Gen. P.f 0



29

Applying traditional DR:

Lowest voltage bus: LV bus A7

Figure 4: Voltage level against load scaling factor plot for feeder A buses

For LV bus A7:

| |

Target Vp.u for bus = 0.94; load scaling factor = 0.839

After the generation scaling factor of 0.839 was applied, the results were as

follows:

Table 3: Peak load condition simulation results after traditional DR application

Consumers involved 22

Total load reduction kW 35.4

Total load reduction % 16.1%



0.915

0.92

0.925

0.93

0.935

0.94

0.945

0.95

0.955

0.96

1 0.99 0.98 0.97 0.96 0.95

Vo

lta

ge

p.u

Load scaling factor

LV bus (A1)

LV bus (A2)

LV bus (A3)

LV bus (A4)

LV bus (A5)

LV bus (A6)

LV bus (A7)

30

Applying effective DR management:

Table 4: Violated buses and voltage values

Location V p.u

LV bus (A5) 0.934551

LV bus (A6) 0.930016

LV bus (A7) 0.930016

LV bus (C5) 0.934551

LV bus (C6) 0.934551

LV bus (C7) 0.932283

LV bus (B4) 0.936819

LV bus (B5) 0.936819

LV bus (B6) 0.934551

Load flow sensitivities of the most effective buses:

Table 5: Load flow sensitivity values

Location

dv/dP

(Vp.u/MW)

dv/dQ

(Vp.u/MVar)

LV bus (A6) 1.034035596 0.965557

LV bus (A7) 1.034035596 0.965557

LV bus (B6) 1.02092259 0.958599

LV bus (C7) 1.02539365 0.961473

| |

Load reduced in kW:

Table 6: Load reduction values

Location ΔP kW Reduction kW % Reduction

LV bus (A7) 10.323 5.162 51.62 %

LV bus (A6) 10.323 5.162 51.62 %

LV bus (B6) 5.563 5.563 55.63 %

LV bus (C7) 7.913 7.913 79.13 %

(As LV bus A6 and LV bus A7 are on the same node half the load reduction was applied to each)

Table 7: Peak load condition simulation results after effective DR application


Total load reduction kW 23.8

Total load reduction % 10.8%



31

4.2.3 Scenario 3: Average load condition with current PV penetration

values

For the average loading condition with current PV penetration values scenario, the

scenario loading condition was the same as scenario 1 but with the difference being

that PV generation was included. The PV generation scaling factor was raised to

0.3. This represented a grid PV penetration of 30%. The power factor of the PV

generation units was assumed to be 0.8 for ease of simulation purposes only, in the

real world this value is 1 or close to 1. From the results, it was observed that the

minimum and the maximum bus voltages were within the required limits and thus

the application of DR was unnecessary. Also, unlike scenario 1, the minimum and

maximum voltage limits were now raised to 1.002 and 1.006 respectively. This

indicates that with the current PV penetration levels in Australian LV networks, the

grid is being assisted in its power delivery.

Table 8: Average load condition with current PV penetration simulation results

Loads active 22

Load kW 10


Load P.f 0.95

PV inputs active 22

Generation kW 10

Gen. scaling factor 0.3

Gen. P.f 0.8



32

4.2.4 Scenario 4: Average load condition with future PV penetration

values

In this scenario, the load scaling factor was 0.4 and the PV penetration was raised

to 100%. This meant a generation factor of 1, which is an assumed value for future

PV penetration values. In this scenario, an overvoltage was present in the end buses

of feeders A, B and C. From this it was concluded that future PV penetration values

may occur complications to the grid if left unmanaged. The maximum bus voltage

measured at LV bus A6 and A7 was 1.072 Vp.u. The application of demand

response was necessary to reduce these voltages to the acceptable limit of 1.06 Vp.u.

A traditional and effective DR was then applied. For the traditional DR, the values

of voltage and load scaling factor were plotted against each other and a trend line

was inserted. A required generation scaling factor of 0.874 was calculated which

meant the PV generation output needed a reduction of 12.6% from the current

value. A uniform PV generation reduction was applied reducing all PV outputs

from 10 kW to 8.74 kW with a power factor of 0.8. The simulation was run again

with the changes to PV generation and the maximum bus voltage was now 1.060 at

LV bus A6 and A7. The same scenario was then repeated but with the application

of effective DR. The load flow sensitivities for the buses with the most violated

voltage levels were targeted first. The buses of LV bus A6, A7, B6 and C7 had the

most influence on the grid. The required PV generation reduction values calculated

from the load flow sensitivities were found to be 10.295, 10.295, 7.074 and 8.699

kW for buses A6, A7, B6 and C7 respectively. As LV bus A6 and LV bus A7 were

on the same node, half the generation reduction was applied to each bus. The

results after the application of effective DR show that the bus voltages were now

within acceptable limits. Also, less generation reduction was applied to the PV

33

generators than the traditional DR with a better result of 1.052 for the minimum

voltage. The total reduction in percentage was 11.85% for the effective DR and

12.6% for the traditional DR. The effective DR also involved fewer consumers (3

per bus) of only 12 compared to 66.

The results show that effective DR management reduces the necessary PV

generation reduction quantity and the number of consumers involved. However,

from the effective DR management it was found that the highest reduction required

from the buses was around 8.7 kW. This would be almost the entire PV generation

quantity. As consumers in Australia mostly receive a feed in tariff, this may reduce

the gains they receive from the installation of PV generation and in turn the

payback period of the PV system installed. This will need to be addressed and

agreed upon by the consumer and the aggregator managing the PV generation

system. Also with the application of effective DR the targeted Vp.u was 1.06 and

yet the simulated Vp.u was 1.052, this was considerably below the required amount

and thus it was evident that the effect of generation reduction was amplified as

more than one bus was reduced with each bus influencing all other bus voltages.

Table 9: Average load condition with future PV penetration simulation results

Loads active 22

Load kW 10


Load P.f 0.95

PV inputs active 22

Generation kW 10


Gen. P.f 0.8



34

Applying Traditional DR:

Highest voltage bus: LV bus A7

Figure 5: Voltage level against generation scaling factor plot for feeder A buses

For LV bus A7:

| |

Target Vp.u for bus = 1.06; PV generation scaling factor = 0.874

After the generation scaling factor of 0.874 was applied, the results were as

follows:

Table 10: Average load condition with future PV generation simulation results after traditional DR

application


Total Gen. reduction kW 27.72

Total Gen. reduction % 12.6%



1.03

1.035

1.04

1.045

1.05

1.055

1.06

1.065

1.07

1.075

1.08

1 0.99 0.98 0.97 0.96 0.95

Vo

lta

ge

p.u

Generation scaling factor

LV bus (A1)

LV bus (A2)

LV bus (A3)

LV bus (A4)

LV bus (A5)

LV bus (A6)

LV bus (A7)

35

Applying effective DR management:

Table 11: Violated buses and voltage values

Location V p.u

LV bus (A6) 1.068182

LV bus (A7) 1.068182

LV bus (C7) 1.066254

LV bus (C5) 1.064327

LV bus (C6) 1.064327

LV bus (A5) 1.064327

LV bus (B6) 1.064326

LV bus (B4) 1.062399

LV bus (B5) 1.062399

Load flow sensitivities of the most effective buses:

Table 12: Load flow sensitivity values

Location

dv/dP

(Vp.u/MW)

dv/dQ

(Vp.u/MVar)

LV bus (A6) 0.808264959 0.789635871

LV bus (A7) 0.808264959 0.789635871

LV bus (B6) 0.814306683 0.79576899

LV bus (C7) 0.812111712 0.79358049

| |

Generation reduced in kW:

Table 13: Required change in active power

Location ΔP kW

LV bus (A6) 10.295

LV bus (A7) 10.295

LV bus (B6) 7.0742

LV bus (C7) 8.6994

(As LV bus A6 and A7 are on the same node half the generation reduction was applied to each)

Table 14: Average load condition with future PV penetration value simulation results after effective DR

application


Total Gen. reduction kW 26.07

Total Gen. reduction % 11.85%



36

4.2.5 Scenario 5: Peak load condition with current PV penetration values

For the peak load with current PV penetration values scenario, the scenario loading

condition was the same as scenario 2 but the difference being that the current PV

generation value of 30% was considered. The PV generation scaling factor was

selected to be 0.3. From the results, it was found that the minimum and the

maximum bus voltages were within the required limits and thus the application of

DR was unnecessary. Also, it was found that the PV penetration values assisted in

maintaining the acceptable voltage limits. This indicates that with the current PV

penetration levels in Australian LV networks, PV generation is beneficial to the

grid when coinciding with peak loading conditions.

Table 15: Peak load condition with future PV penetration simulation results

Loads active 22

Load kW 10


Load P.f 0.95

PV inputs active 22

Generation kW 10

Gen. scaling factor 0.3

Gen. P.f 0.8



37

4.2.6 Scenario 6: Peak load condition with future PV penetration values

For this scenario, the loading and the PV generation was assumed to be at their

maximum. The scaling factors for both were increased to 1 representing 100%

loading and generation. From the results, it was found that the minimum and the

maximum bus voltages were within the required limits and thus the application of

DR was unnecessary. Also, future PV penetration values can assist in maintaining

the acceptable voltage limits under peak loading conditions.

Table 16: Peak load condition with future PV penetration simulation results

Loads active 22

Load kW 10


Load P.f 0.95

PV inputs active 22

Generation kW 10


Gen. P.f 0.8



38

4.3 Result Analysis

From the results of the scenarios, the following observations were made:

-From scenario 2 and scenario 4, it was found that the effective DR involved less

consumers and required less power reduction than traditional DR. This could be

beneficial to aggregators that are required to pay an incentive to consumers as they

can now pay incentives to a less number of people. This also allows aggregators to

install less direct load control devices, or if this was to become the norm for all

consumers in the future, it would inform aggregators which consumers to start with

in the installation process.

-From the scenarios above, only a change in active power was necessary to achieve

the required voltage level change when applying effective DR. Also, the reactive

sensitivities would not be used as it would not be conventional in the real world. It

would require a change in the power factor or the use of a power factor correction

tool which is not as practical as simply changing the active power of the loads by

turning them off.

-From scenario 2 and scenario 4, it was found that the effective DR management

was applied the reduction in PV generation yielded a larger change in the voltage

level than that of reducing the loads. This could be due to the lower power factor in

the PV generation units. The change in the apparent power by reducing the PV

generation’s active power is larger than the change in apparent power of reducing

the loads.

39

-From the simulations, it was observed that the end buses were the most sensitive

to changes and in turn the most effective for the application of DR. This is evident

as the calculation of the Jacobian matrix process attracts a greater value change as

the bus increases in series.

-From scenarios 4 and 6, the predicted future PV penetration levels in Australian

LV networks were found to assist the grid under peak loading conditions but the

PV generation output needed management as they raise voltages at end buses

beyond the acceptable limits.

-From the results in scenarios 3 and 5, it was found that the current PV penetration

values are not of a concern to the operation of the grid in fact assist the grid at high

peak demand periods. However, their effect to change voltage levels cannot be

overlooked as they have a large influence when they operate collectively.

-In scenario 4, it was assumed that traditional DR can be used to reduce the PV

generation output. However, in the real world this is not that case as PV generation

can only be switched on or off at the consumer end by the consumers. Even if the

inverters were equipped with PV generation level controllers it would not be

practical to expect consumers to use them or to know when to reduce their PV

generation outputs. It is also a time when businesses are operating, requesting a PV

generation drop from a business during working hours would be counterproductive

as the business would generally consume most of the PV generation output.

-In scenarios 2 and 4, the effective DR load and generation were over-reduced from

the sensitivities calculated. This is due to the fact that any change to any bus has an

extended effect on the rest of the buses in the grid. Also, this could be due to the

reactive powers present in the grid.

41

Chapter 5- Conclusion

5.1 Overview

This chapter will draw the conclusions from the project, the difficulties

encountered and future recommendations.

5.2 Conclusion

The project objectives were achieved with satisfactory results. The use of

traditional and effective DR management was investigated and the difference in

performance was illustrated through several scenarios. The results were consistent

throughout the simulation process thus supporting the findings.

From the results, it was found that DR was a beneficial strategy to maintaining bus

voltage limits. The use of an effective DR strategy proved to be a more efficient

strategy than traditional DR in maintaining bus voltages. However, the amount of

reduction from each bus needs to be limited to a maximum value as was seen

necessary from the results.

PV generation was found to be beneficial to bus voltage regulation in peak loading

scenarios. As future PV generation increases and PV penetration values rise,

regulations and strategies will be required to maintain bus voltages within limits at

peak PV generation periods.

It can be seen that the effective DR management method is a less resource-

demanding solution to the correction of bus voltage violation. This is beneficial in

reducing the need to overproduce electricity and therefore reduces the cost of

electricity bills of consumers. The environmental benefit is also an important

aspect, as less energy production equates to less carbon emissions.

42

5.3 Obstacles and difficulties

The first obstacle was faced at the beginning of the project when searching for an

Australian LV grid to apply DR scenarios on. It was extremely difficult to find a

current operational grid to use for the project as most grids found lacked technical

information and parameters. This forced a new grid to be constructed by relying on

the manuals and standards used in Australia. The difficulty encountered when

constructing the grid was that the current grids operating in Australia varied in

some aspects from the standards highlighted by Horizon Power and Western

Power. For example, the voltage of a three phase LV network defined by Horizon

Power and Western Power is 415V, yet the grid details found for the Perth solar

city project expressed the voltage of the grid to be 400V. Also, the required voltage

limits of the buses in a grid differed as sources claimed a tolerance of +10% and -

6% volts while others required ±6 %.

Another challenge was component sizing. In technical manuals and standards, it

was required that components such as transformers and cables be sized to meet the

grid’s expected loadings. This was difficult as the loadings and lengths of cables

themselves had to be assumed for the project. This resulted in a design with

multiple variables which required many simulations using a lengthy trial and error

approach.

Another major obstacle was the use of the DIgSILENT PowerFactory software.

This software considers many parameters when conducting simulations. Most of

these parameters can be left as standard, however an extensive study of the user

manual is required to be able to understand the effects each parameter has on the

calculation output. Also, the software itself is not the most user-friendly and

requires some experience to use.

43

5.4 Future recommendations

As a large portion of the project time was spent on grid construction, finding a

ready-built grid would be beneficial for future projects as this allows more focus

towards DR simulations. In this project, different scenarios were examined using

the same grid. Future studies could investigate the outcomes of using the same

scenario on different grids to expand the scenario spectrum of DR. The addition of

battery banks and large scale renewable DER’s could be added in future projects to

examine the use of DR in conjunction with these elements added to the grid.

From the effective DR management, it was noticed that there tended to be an over-

reduction of loads or PV generation. For future projects the effect of reactive power

on the DR process could be investigated. Also, the sensitivity calculation of the

effective DR process could include the sensitivities of each bus and its effect on

other buses in the grid for increased accuracy of load reduction values.

The system used for this project was a three-phase balanced system. Future projects

could investigate a three-phase unbalanced system which resembles a closer system

to the real world. Also, special conditions could be investigated in future projects,

such as DR under fault or line maintenance conditions where DR could be used to

assist the performance of the grid.

44

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47

Appendix A: Project grid parameters

The following parameters were used in the construction of the grid.

Table 17: Project transformer parameters

Transformer parameters

Rated power 200 kVA

Voltage step 22 kV /415 V

Rating factor 98.94%

Vector group YN / D

Positive sequence impedance

Short-circuit Voltage uk 4.30%

Copper losses 2.963 kW

Zero sequence impedance

Short-circuit Voltage uk0 0.614%

SHC-Voltage uk0r 0%

Magnetising impedance

No load current 0.10%

No load losses 0.424 kW

Table 18: Project transformer parameters

Nexans Olex Mercury

Aluminium

Overhead 3 phase lines 7/4.50 mm

Rated current rural 196 A

Impedance 0.315 R + j 0.259 X

Overall diameter 13.5 mm

Cross sectional area 111 mm2

48

Table 19: Project cable lengths

From To Length m

Feeder Bus A 1 100

Feeder Bus B 1 100

Feeder Bus C 1 100

Feeder Bus D1 100

Bus W 1 LV bus (A1) 50

Bus X 2 LV bus (B3) 50



Bus Y 3 LV bus (C5) 50













Bus Z1 LV bus (D1) 50

Bus Z 2 LV bus (D2) 50




Bus W 1 Bus W 2 100

Bus W 2 Bus W 3 100

Bus W 3 Bus W 4 100

Bus X 1 Bus X 2 100

Bus X 2 Bus X 3 100

Bus X 3 Bus X 4 100

Bus Y 1 Bus Y 2 100

Bus Y 2 Bus Y 3 100

Bus Y 3 Bus Y 4 100

Bus Z1 Bus Z 2 100

49

Table 20: Project bus parameters

Bus

Nominal

voltage V

Phase technology

Max voltage limit %

Min voltage limit %

22 kV 22000 ABC-N 6 -6

Bus W 1 415 ABC-N 6 -6

Bus W 2 415 ABC-N 6 -6

Bus W 3 415 ABC-N 6 -6

Bus W 4 415 ABC-N 6 -6

Bus X 1 415 ABC-N 6 -6

Bus X 2 415 ABC-N 6 -6

Bus X 3 415 ABC-N 6 -6

Bus X 4 415 ABC-N 6 -6

Bus Y 1 415 ABC-N 6 -6

Bus Y 2 415 ABC-N 6 -6

Bus Y 3 415 ABC-N 6 -6

Bus Y 4 415 ABC-N 6 -6

Bus Z 2 415 ABC-N 6 -6

Bus Z 1 415 ABC-N 6 -6

Feeder 415 ABC-N 6 -6

LV bus (A1) 415 ABC-N 6 -6

LV bus (A2) 415 ABC-N 6 -6

LV bus (A3) 415 ABC-N 6 -6

LV bus (A4) 415 ABC-N 6 -6

LV bus (A5) 415 ABC-N 6 -6

LV bus (A6) 415 ABC-N 6 -6

LV bus (A7) 415 ABC-N 6 -6

LV bus (B1) 415 ABC-N 6 -6

LV bus (B2) 415 ABC-N 6 -6

LV bus (B3) 415 ABC-N 6 -6

LV bus (B4) 415 ABC-N 6 -6

LV bus (B5) 415 ABC-N 6 -6

LV bus (B6) 415 ABC-N 6 -6

LV bus (C1) 415 ABC-N 6 -6

LV bus (C2) 415 ABC-N 6 -6

LV bus (C3) 415 ABC-N 6 -6

LV bus (C4) 415 ABC-N 6 -6

LV bus (C5) 415 ABC-N 6 -6

LV bus (C6) 415 ABC-N 6 -6

LV bus (C7) 415 ABC-N 6 -6

LV bus (D1) 415 ABC-N 6 -6

LV bus (D2) 415 ABC-N 6 -6

50

Table 21: Project loads and PV generators, locations and values

Located at

PV

generator

Gen. Active

power kW

Gen. P.f

absorbing Load

Load Active

power kW

Load P.f

absorbing

LV bus (A1) A-PV 1 10 0.8 A-Load 1 10 0.95

LV bus (A2) A-PV 2 10 0.8 A-Load 2 10 0.95

LV bus (A3) A-PV 3 10 0.8 A-Load 3 10 0.95

LV bus (A4) A-PV 4 10 0.8 A-Load 4 10 0.95

LV bus (A5) A-PV 5 10 0.8 A-Load 5 10 0.95

LV bus (A6) A-PV 6 10 0.8 A-Load 6 10 0.95

LV bus (A7) A-PV 7 10 0.8 A-Load 7 10 0.95

LV bus (B1) B-PV 1 10 0.8 B-Load 1 10 0.95

LV bus (B2) B-PV 2 10 0.8 B-Load 2 10 0.95

LV bus (B3) B-PV 3 10 0.8 B-Load 3 10 0.95

LV bus (B4) B-PV 4 10 0.8 B-Load 4 10 0.95

LV bus (B5) B-PV 5 10 0.8 B-Load 5 10 0.95

LV bus (B6) B-PV 6 10 0.8 B-Load 6 10 0.95

LV bus (C1) C-PV 1 10 0.8 C-Load 1 10 0.95

LV bus (C2) C-PV 2 10 0.8 C-Load 2 10 0.95

LV bus (C3) C-PV 3 10 0.8 C-Load 3 10 0.95

LV bus (C4) C-PV 4 10 0.8 C-Load 4 10 0.95

LV bus (C5) C-PV 5 10 0.8 C-Load 5 10 0.95

LV bus (C6) C-PV 6 10 0.8 C-Load 6 10 0.95

LV bus (C7) C-PV 7 10 0.8 C-Load 7 10 0.95

LV bus (D1) D-PV 1 10 0.8 D-Load 1 10 0.95

LV bus (D2) D-PV 2 10 0.8 D-Load 2 10 0.95

51

Appendix B: Simulation parameters and results

Scenario 1

Table 22: Scenario 1 parameters and simulation results

Load scale factor 0.4 Component Loading %

PV Gen. factor 0 Transformer 47.012

Feeder A 20.920

Feeder B 17.932

Feeder C 20.920

Feeder D 5.977

Bus

Bus

Vp.u

Load

kW

Load

kVAr

Gen

kW

Gen

kVAr

LV bus (A1) 0.981 4.00 1.31 0.00 0.00

LV bus (A2) 0.981 4.00 1.31 0.00 0.00

LV bus (A3) 0.976 4.00 1.31 0.00 0.00

LV bus (A4) 0.976 4.00 1.31 0.00 0.00

LV bus (A5) 0.973 4.00 1.31 0.00 0.00

LV bus (A6) 0.972 4.00 1.31 0.00 0.00

LV bus (A7) 0.972 4.00 1.31 0.00 0.00

LV bus (B1) 0.982 4.00 1.31 0.00 0.00

LV bus (B2) 0.977 4.00 1.31 0.00 0.00

LV bus (B3) 0.977 4.00 1.31 0.00 0.00

LV bus (B4) 0.974 4.00 1.31 0.00 0.00

LV bus (B5) 0.974 4.00 1.31 0.00 0.00

LV bus (B6) 0.973 4.00 1.31 0.00 0.00

LV bus (C1) 0.981 4.00 1.31 0.00 0.00

LV bus (C2) 0.981 4.00 1.31 0.00 0.00

LV bus (C3) 0.976 4.00 1.31 0.00 0.00

LV bus (C4) 0.976 4.00 1.31 0.00 0.00

LV bus (C5) 0.973 4.00 1.31 0.00 0.00

LV bus (C6) 0.973 4.00 1.31 0.00 0.00

LV bus (C7) 0.972 4.00 1.31 0.00 0.00

LV bus (D1) 0.985 4.00 1.31 0.00 0.00

LV bus (D2) 0.984 4.00 1.31 0.00 0.00

52

Scenario 2


Load scale factor 1 Component Loading %


Feeder W 52.301

Feeder X 44.829

Feeder Y 52.301

Feeder Z 14.943

Bus

Bus

Vp.u

Load

kW

Load

kVAr

Gen

kW

Gen

kVAr

LV bus (A1) 0.953 10.01 3.24 0.00 0.00

LV bus (A2) 0.953 10.01 3.24 0.00 0.00

LV bus (A3) 0.941 10.01 3.22 0.00 0.00

LV bus (A4) 0.941 10.01 3.22 0.00 0.00

LV bus (A5) 0.935 10.01 3.21 0.00 0.00

LV bus (A6) 0.930 10.00 3.20 0.00 0.00

LV bus (A7) 0.930 10.00 3.20 0.00 0.00

LV bus (B1) 0.955 10.01 3.25 0.00 0.00

LV bus (B2) 0.944 10.01 3.23 0.00 0.00

LV bus (B3) 0.944 10.01 3.23 0.00 0.00

LV bus (B4) 0.937 10.01 3.21 0.00 0.00

LV bus (B5) 0.937 10.01 3.21 0.00 0.00

LV bus (B6) 0.935 10.01 3.21 0.00 0.00

LV bus (C1) 0.953 10.01 3.24 0.00 0.00

LV bus (C2) 0.953 10.01 3.24 0.00 0.00

LV bus (C3) 0.941 10.01 3.22 0.00 0.00

LV bus (C4) 0.941 10.01 3.22 0.00 0.00

LV bus (C5) 0.935 10.01 3.21 0.00 0.00

LV bus (C6) 0.935 10.01 3.21 0.00 0.00

LV bus (C7) 0.932 10.01 3.21 0.00 0.00

LV bus (D1) 0.964 10.01 3.26 0.00 0.00

LV bus (D2) 0.962 10.01 3.25 0.00 0.00

53

Table 24: Scenario 2 Change in bus voltage due to change in scaling factor

V p.u

Scaling factor

1 0.99 0.98 0.97 0.96 0.95

LV bus (A1) 0.95273 0.95319 0.95365 0.95412 0.95458 0.95504

LV bus (A2) 0.95273 0.95319 0.95365 0.95412 0.95458 0.95504

LV bus (A3) 0.94136 0.94193 0.94250 0.94308 0.94365 0.94422

LV bus (A4) 0.94136 0.94193 0.94250 0.94308 0.94365 0.94422

LV bus (A5) 0.93455 0.93519 0.93583 0.93647 0.93710 0.93774

LV bus (A6) 0.93002 0.93070 0.93138 0.93206 0.93275 0.93343

LV bus (A7) 0.93002 0.93070 0.93138 0.93206 0.93275 0.93343

LV bus (B1) 0.95501 0.95545 0.95589 0.95633 0.95677 0.95720

LV bus (B2) 0.94363 0.94418 0.94473 0.94528 0.94583 0.94638

LV bus (B3) 0.94363 0.94418 0.94473 0.94528 0.94583 0.94638

LV bus (B4) 0.93682 0.93744 0.93805 0.93867 0.93928 0.93990

LV bus (B5) 0.93682 0.93744 0.93805 0.93867 0.93928 0.93990

LV bus (B6) 0.93455 0.93519 0.93583 0.93647 0.93710 0.93774

LV bus (C1) 0.95273 0.95319 0.95365 0.95412 0.95458 0.95504

LV bus (C2) 0.95273 0.95319 0.95365 0.95412 0.95458 0.95504

LV bus (C3) 0.94136 0.94193 0.94250 0.94308 0.94365 0.94422

LV bus (C4) 0.94136 0.94193 0.94250 0.94308 0.94365 0.94422

LV bus (C5) 0.93455 0.93519 0.93583 0.93647 0.93710 0.93774

LV bus (C6) 0.93455 0.93519 0.93583 0.93647 0.93710 0.93774

LV bus (C7) 0.93228 0.93294 0.93360 0.93426 0.93492 0.93559

LV bus (D1) 0.96413 0.96448 0.96483 0.96518 0.96553 0.96588

LV bus (D2) 0.96185 0.96222 0.96259 0.96296 0.96334 0.96371

Figure 6: Scenario 2 Voltage VS Scaling factor plot

0.92

0.93

0.93

0.94

0.94

0.95

0.95

0.96

0.96

0.97

0.97

1 0.99 0.98 0.97 0.96 0.95

Vo

lta

ge

p.u

Scaling factor

LV bus (A1) LV bus (A2) LV bus (A3) LV bus (A4) LV bus (A5) LV bus (A6) LV bus (A7) LV bus (B1) LV bus (B2) LV bus (B3) LV bus (B4) LV bus (B5) LV bus (B6) LV bus (C1) LV bus (C2) LV bus (C3) LV bus (C4) LV bus (C5) LV bus (C6) LV bus (C7) LV bus (D1) LV bus (D2)

54

Table 25: Scenario 2 load flow sensitivities

Bus

dv/dP

(Vp.u/MW)

dv/dQ

(Vp.u/MVar)

LV bus (A1) 0.391 0.457

LV bus (A2) 0.391 0.457

LV bus (A3) 0.606 0.627

LV bus (A4) 0.606 0.627

LV bus (A5) 0.821 0.797

LV bus (A6) 1.034 0.966

LV bus (A7) 1.034 0.966

LV bus (B1) 0.388 0.455

LV bus (B2) 0.603 0.625

LV bus (B3) 0.603 0.625

LV bus (B4) 0.817 0.794

LV bus (B5) 0.817 0.794

LV bus (B6) 1.021 0.959

LV bus (C1) 0.391 0.457

LV bus (C2) 0.391 0.457

LV bus (C3) 0.606 0.627

LV bus (C4) 0.606 0.627

LV bus (C5) 0.821 0.796

LV bus (C6) 0.821 0.796

LV bus (C7) 1.025 0.961

LV bus (D1) 0.377 0.449

LV bus (D2) 0.572 0.607

55

Scenario 3



PV Gen. factor 0.3 Transformer 15.380

Feeder W 6.803

Feeder X 5.831

Feeder Y 6.803

Feeder Z 1.944

Bus

Bus

Vp.u

Load

kW

Load

kVAr

Gen

kW

Gen

kVAr

LV bus (A1) 1.002 4.00 1.31 3.00 2.25

LV bus (A2) 1.002 4.00 1.31 3.00 2.25

LV bus (A3) 1.002 4.00 1.32 3.00 2.25

LV bus (A4) 1.002 4.00 1.32 3.00 2.25

LV bus (A5) 1.002 4.00 1.32 3.00 2.25

LV bus (A6) 1.002 4.00 1.32 3.00 2.25

LV bus (A7) 1.002 4.00 1.32 3.00 2.25

LV bus (B1) 1.002 4.00 1.31 3.00 2.25

LV bus (B2) 1.002 4.00 1.32 3.00 2.25

LV bus (B3) 1.002 4.00 1.32 3.00 2.25

LV bus (B4) 1.002 4.00 1.32 3.00 2.25

LV bus (B5) 1.002 4.00 1.32 3.00 2.25

LV bus (B6) 1.002 4.00 1.32 3.00 2.25

LV bus (C1) 1.002 4.00 1.31 3.00 2.25

LV bus (C2) 1.002 4.00 1.31 3.00 2.25

LV bus (C3) 1.002 4.00 1.32 3.00 2.25

LV bus (C4) 1.002 4.00 1.32 3.00 2.25

LV bus (C5) 1.002 4.00 1.32 3.00 2.25

LV bus (C6) 1.002 4.00 1.32 3.00 2.25

LV bus (C7) 1.002 4.00 1.32 3.00 2.25

LV bus (D1) 1.002 4.00 1.31 3.00 2.25

LV bus (D2) 1.002 4.00 1.31 3.00 2.25

56

Scenario 4




Feeder W 42.816

Feeder X 36.699

Feeder Y 42.816

Feeder Z 12.233

Bus

Bus

Vp.u

Load

kW

Load

kVAr

Gen

kW

Gen

kVAr

LV bus (A1) 1.052 3.99 1.31 9.99 7.47

LV bus (A2) 1.052 3.99 1.31 9.99 7.47

LV bus (A3) 1.063 3.99 1.30 9.98 7.46

LV bus (A4) 1.063 3.99 1.30 9.98 7.46

LV bus (A5) 1.069 3.98 1.30 9.97 7.45

LV bus (A6) 1.073 3.98 1.30 9.96 7.44

LV bus (A7) 1.073 3.98 1.30 9.96 7.44

LV bus (B1) 1.050 3.99 1.31 9.99 7.47

LV bus (B2) 1.061 3.99 1.30 9.98 7.46

LV bus (B3) 1.061 3.99 1.30 9.98 7.46

LV bus (B4) 1.067 3.99 1.30 9.97 7.45

LV bus (B5) 1.067 3.99 1.30 9.97 7.45

LV bus (B6) 1.069 3.98 1.30 9.97 7.45

LV bus (C1) 1.052 3.99 1.31 9.99 7.47

LV bus (C2) 1.052 3.99 1.31 9.99 7.47

LV bus (C3) 1.063 3.99 1.30 9.98 7.46

LV bus (C4) 1.063 3.99 1.30 9.98 7.46

LV bus (C5) 1.069 3.98 1.30 9.97 7.45

LV bus (C6) 1.069 3.98 1.30 9.97 7.45

LV bus (C7) 1.071 3.98 1.30 9.97 7.45

LV bus (D1) 1.042 4.00 1.31 9.99 7.48

LV bus (D2) 1.044 3.99 1.31 9.99 7.47

57

Table 28: Scenario 4 Change in bus voltage due to change in scaling factor

Scaling factor

V p.u 1 0.99 0.98 0.97 0.96 0.95

LV bus (A1) 1.05123 1.05054 1.04985 1.04916 1.04848 1.04779

LV bus (A2) 1.05123 1.05054 1.04985 1.04916 1.04848 1.04779

LV bus (A3) 1.06183 1.06100 1.06017 1.05934 1.05851 1.05768

LV bus (A4) 1.06183 1.06100 1.06017 1.05934 1.05851 1.05768

LV bus (A5) 1.06857 1.06766 1.06674 1.06582 1.06491 1.06399

LV bus (A6) 1.07363 1.07266 1.07169 1.07071 1.06974 1.06877

LV bus (A7) 1.07363 1.07266 1.07169 1.07071 1.06974 1.06877

LV bus (B1) 1.04885 1.04819 1.04753 1.04687 1.04621 1.04556

LV bus (B2) 1.05900 1.05820 1.05740 1.05660 1.05579 1.05499

LV bus (B3) 1.05900 1.05820 1.05740 1.05660 1.05579 1.05499

LV bus (B4) 1.06530 1.06441 1.06352 1.06264 1.06175 1.06086

LV bus (B5) 1.06530 1.06441 1.06352 1.06264 1.06175 1.06086

LV bus (B6) 1.06800 1.06708 1.06617 1.06525 1.06433 1.06342

LV bus (C1) 1.05100 1.05031 1.04963 1.04894 1.04825 1.04756

LV bus (C2) 1.05100 1.05031 1.04963 1.04894 1.04825 1.04756

LV bus (C3) 1.06138 1.06055 1.05972 1.05889 1.05806 1.05723

LV bus (C4) 1.06138 1.06055 1.05972 1.05889 1.05806 1.05723

LV bus (C5) 1.06790 1.06698 1.06607 1.06515 1.06424 1.06332

LV bus (C6) 1.06790 1.06698 1.06607 1.06515 1.06424 1.06332

LV bus (C7) 1.07094 1.06999 1.06905 1.06810 1.06716 1.06621

LV bus (D1) 1.04062 1.04008 1.03954 1.03899 1.03845 1.03790

LV bus (D2) 1.04255 1.04198 1.04141 1.04083 1.04026 1.03969

Figure 7: Scenario 2 Voltage VS Scaling factor plot

1.02

1.03

1.04

1.05

1.06

1.07

1.08

1 0.99 0.98 0.97 0.96 0.95

Vo

lta

ge

p.u

Generation scaling factor

LV bus (A1) LV bus (A2) LV bus (A3) LV bus (A4) LV bus (A5) LV bus (A6) LV bus (A7) LV bus (B1) LV bus (B2) LV bus (B3) LV bus (B4) LV bus (B5) LV bus (B6) LV bus (C1) LV bus (C2) LV bus (C3) LV bus (C4) LV bus (C5) LV bus (C6) LV bus (C7) LV bus (D1) LV bus (D2)

58

Table 29: Scenario 4 load flow sensitivities

Bus

dv/dP

(Vp.u/MW)

dv/dQ

(Vp.u/MVar)

LV bus (A1) 0.320 0.395

LV bus (A2) 0.320 0.395

LV bus (A3) 0.483 0.526

LV bus (A4) 0.483 0.526

LV bus (A5) 0.645 0.657

LV bus (A6) 0.808 0.790

LV bus (A7) 0.808 0.790

LV bus (B1) 0.321 0.396

LV bus (B2) 0.484 0.527

LV bus (B3) 0.484 0.527

LV bus (B4) 0.647 0.659

LV bus (B5) 0.647 0.659

LV bus (B6) 0.814 0.796

LV bus (C1) 0.320 0.395

LV bus (C2) 0.320 0.395

LV bus (C3) 0.483 0.526

LV bus (C4) 0.483 0.526

LV bus (C5) 0.645 0.657

LV bus (C6) 0.645 0.657

LV bus (C7) 0.812 0.794

LV bus (D1) 0.327 0.402

LV bus (D2) 0.500 0.544

59

Scenario 5



PV Gen. factor 0.3 Transformer 78.881

Feeder W 35.160

Feeder X 30.137

Feeder Y 35.160

Feeder Z 10.046

Bus

Bus

Vp.u

Load

kW

Load

kVAr

Gen

kW

Gen

kVAr

LV bus (A1) 0.974 10.01 3.27 3.01 2.25

LV bus (A2) 0.974 10.01 3.27 3.01 2.25

LV bus (A3) 0.967 10.01 3.26 3.01 2.24

LV bus (A4) 0.967 10.01 3.26 3.01 2.24

LV bus (A5) 0.963 10.01 3.26 3.01 2.24

LV bus (A6) 0.960 10.01 3.25 3.01 2.24

LV bus (A7) 0.960 10.01 3.25 3.01 2.24

LV bus (B1) 0.975 10.01 3.27 3.01 2.25

LV bus (B2) 0.968 10.01 3.26 3.01 2.24

LV bus (B3) 0.968 10.01 3.26 3.01 2.24

LV bus (B4) 0.964 10.01 3.26 3.01 2.24

LV bus (B5) 0.964 10.01 3.26 3.01 2.24

LV bus (B6) 0.963 10.01 3.26 3.01 2.24

LV bus (C1) 0.974 10.01 3.27 3.01 2.25

LV bus (C2) 0.974 10.01 3.27 3.01 2.25

LV bus (C3) 0.967 10.01 3.26 3.01 2.24

LV bus (C4) 0.967 10.01 3.26 3.01 2.24

LV bus (C5) 0.963 10.01 3.26 3.01 2.24

LV bus (C6) 0.963 10.01 3.26 3.01 2.24

LV bus (C7) 0.961 10.01 3.25 3.01 2.24

LV bus (D1) 0.981 10.01 3.28 3.00 2.25

LV bus (D2) 0.979 10.01 3.28 3.00 2.25

60

Scenario 6




Feeder A 20.933

Feeder B 17.943

Feeder C 20.933

Feeder D 5.981

Bus

Bus

Vp.u

Load

kW

Load

kVAr

Gen

kW

Gen

kVAr

LV bus (A1) 1.023 9.99 3.29 9.99 7.50

LV bus (A2) 1.023 9.99 3.29 9.99 7.50

LV bus (A3) 1.027 9.99 3.29 9.99 7.51

LV bus (A4) 1.027 9.99 3.29 9.99 7.51

LV bus (A5) 1.029 9.99 3.30 9.99 7.51

LV bus (A6) 1.030 9.99 3.30 9.99 7.51

LV bus (A7) 1.030 9.99 3.30 9.99 7.51

LV bus (B1) 1.023 9.99 3.29 9.99 7.50

LV bus (B2) 1.026 9.99 3.29 9.99 7.51

LV bus (B3) 1.026 9.99 3.29 9.99 7.51

LV bus (B4) 1.028 9.99 3.30 9.99 7.51

LV bus (B5) 1.028 9.99 3.30 9.99 7.51

LV bus (B6) 1.029 9.99 3.30 9.99 7.51

LV bus (C1) 1.023 9.99 3.29 9.99 7.50

LV bus (C2) 1.023 9.99 3.29 9.99 7.50

LV bus (C3) 1.027 9.99 3.29 9.99 7.51

LV bus (C4) 1.027 9.99 3.29 9.99 7.51

LV bus (C5) 1.029 9.99 3.30 9.99 7.51

LV bus (C6) 1.029 9.99 3.30 9.99 7.51

LV bus (C7) 1.029 9.99 3.30 9.99 7.51

LV bus (D1) 1.020 10.00 3.29 9.99 7.50

LV bus (D2) 1.021 10.00 3.29 9.99 7.50

61

Appendix C

Definitions:

PV penetration value

The ratio between the total peak PV power generated and the peak load apparent

power on a feeder in a network is referred to as the PV penetration value (Hoke,

2012).

Voltage drop

The reduction of voltage due a current moving through an element with electrical

impedance is referred to as voltage drop. In a distribution system, the voltage drop

at a node is proportional to the distance from the energy source (Willis, 2004).

Voltage rise

Opposite to a voltage drop, a voltage rise is referred to as the increase in voltage at

a given node in a circuit in comparison to the energy source. In a distribution

system, a voltage rise occurs at a node where an additional energy source is

connected (Willis, 2004).

Peak to average load demand ratio

The ratio between the hourly average power demand and the peak hourly power

demand of a given network is referred to as peak to average demand ratio. This

ratio is an indicator to the variability of the power demand in a network (Daintith,

2008)

AC power

Power in a power distribution system is measured by the rate of flow of energy

passing through a certain point. AC power in a grid is made up of active and

62

reactive power. The active power, often referred to as real power (P), is measured

in Watts (W). The reactive power, often referred to as reactive power (Q), is

measured in reactive Volt-Amps (Var). Theses powers are added as vectors taking

into consideration a phase angle between them. The sum of these powers makes up

the overall power referred to as the apparent power (S) which is measured in Volt

Amps (VA). The absolute value of the cosine of the apparent power is referred to

as the power factor (P.f). For a well performing grid the aim is to increase the P.f as

close to 1 as possible by reducing the reactive power. This reduces the line losses

in the grid and thus betters the overall performance and efficiency (Beaty, 1998)

Bus voltage limit

The voltage at a bus in comparison to the voltage at the energy source is referred to

as bus voltage. Bus voltages must remain within a certain limit to maintain the

appropriate power quality in a power delivery system (Beaty, 1998).

Electrical impedance

The extent of opposition that a circuit imposes on an electrical current when a

voltage is applied is referred to as electrical impedance. Electrical impedance

occurs with the flow of DC or AC currents. For a DC current the impedance is

purely resistive as only impedance magnitude is present. For an AC current, the

impedance possesses a magnitude and a phase angle. This adds a reactive element

to the impedance know as reactance. The reactive element of the impedance is

influenced by the component the AC current passes through. If the AC current

passes through an inductor, the reactance is referred to as inductance and is

measured in the form of positive imaginary impedance. If the AC current passes

63

through a capacitor, the reactance is referred to as capacitance and is measured in

the form of negative imaginary impedance (Beaty, 1998).

Newton-Raphson load flow equations

The Newton-Raphson load flow equations for active and reactive powers used by

DIgSILENT PowerFactory 15.2 to calculate the bus voltages.

∑ | | | | | |

∑ | | | | | |

Where Pi is the active power of the ith

bus,

Qi is the reactive power of the ith

bus,

Yin∠θin is the admittance of the line from the ith

to the nth

bus,

Vi is the voltage magnitude if the ith bus,

δi is the voltage angle of the ith

bus

64

Jacobian Matrix load flow sensitivity equations

[

]

[

]

Where f is a function of x,

For the load flow sensitivity analysis, the change in voltage is a function of the

change in active and reactive power. For the sensitivity of a bus voltage the

expression of J in Eq.3 is set up using:

f = the active power (P) or reactive power (Q)

x = the bus voltage magnitude (V) and angle of voltage vector (δ)

The J matrix becomes:

[

| |

| |

| |

| |

| |

| |

| |

| |

]

65

The inverse of the Jacobian matrix shown in Eq.4 is then combined with Eq5.

A simplified expression for the change in voltage magnitude as a function of the

change in active and reactive powers is shown in Eq.6.

[

| || |

| || | ]

[

]

| | ∑ | |

| |