Advanced Distribution System Operations to Support Decarbonization and Resiliency

Dr. Kevin Schneider (PNNL)

Dr. Anamika Dubey (WSU)

September 3, 2021

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Serious challenges to planning and operation of the

power systems including on the reliability and stability

of bulk power systems

Most of the changes at MV/LV

power distribution level (at the

grid-edge interfacing)

Solution -

Effectively leverage the grid-edge

resources to ensure efficient,

resilient and reliable grid

operations

Motivation: Advanced Distribution System Operations

Changing nature and requirements of the grid at the edge interfacing:

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WSU and PNNL have been collaborating on multiple projects in this problem space

Motivation: Advanced Distribution System Operations

• Increasing Distribution System

Resiliency using Flexible DER

and Microgrid Assets Enabled by

OpenFMB

• CITADELS – Advanced

operations for networked

microgrids

• Opensource Advanced

Distribution Management

System – GridAPPS-D platform

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Control and Optimization: Active

Power Distribution Systems

Control and Optimization of Active Power Distribution Systems

Addressing Nonlinearity, heterogeneity, time-scale separation, real-time data

Goals Optimize

Resilience

Reliability

Efficiency

Improve

Distribution Grid Optimization at-the-edge-

interfacing

✓ Algorithmic bottlenecks

✓ Ownership boundaries and privacy concerns

✓ Information unavailability and uncertainty

✓ Visibility and situational awareness

Network-level optimization to manage grid resources:

✓ Facilitated by the data environment from granular sensors such as

smart meters, micro-PMUs, smart inverters, etc.

✓ Facilitated by proliferation of controllable/active nodes including

distributed DERs, secondary voltage control devices. Etc.

Centralized Optimization Distributed Optimization

Integration with PNNL’s GridAPPS-D platform – an

opensource platform to develop ADMS applications

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Advanced Distribution Systems

Operations

Active collaboration with PNNL on this problem space

➢ Opensource Advanced Distribution Management System – GridAPPS-D

(Centralized and distributed coordination of grid-edge devices)

➢ CITADELS – Advanced Operations for Networked Microgrids (Distributed

coordination of networked microgrids for resilience and bulk-grid support)

Advanced Data-driven and Model-based Applications for Active Power Distribution Systems

Optimize distribution operations for improved reliability, resiliency, efficiency1

F-1

F-2

A 1

A 2

A 3

A 4

Advanced Distribution Management System: ADMS

Distributed Agent 2 Distributed

Agent 1

Distributed Agent 3

Distributed Agent 4

https://gridappsd-restoration.readthedocs.io/en/latest/

GridAPPS-D platform Layered coordination architecture for

distributed applications

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Research Contributions

• Distributed optimization

algorithms - Method to

coordinate decisions among

distributed areas to achieve

resilience requirements

• Co-simulation of power,

communication and controls

systems

• Fast distributed optimization

for time-sensitive applications

Network of Microgrids as Solution to Resiliency - CITADELS

Networked Microgrids:

• Distribution-level services (e.g., restoration)

• Bulk grid support (frequency and voltage regulation)

• Bulk grid support (black-start capability)

Substation

DER Assets Microgrid Controller Other controllable DERs Uncontrollable DERs

Customers Critical loads Loads with BTM PVs

Network Microgrid boundary Open switch Closed switch Conductor

Agent Interaction

Communication among Microgrid controllers

Microgrid controller to controllable nodes

Resilient Microgrids

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Resilient Microgrids

• The electrical infrastructure of the nation is moving toward a more decarbonized and distributed future.

• By the 2030-2050 timeframe 30%-50% of electricity production will be in the form of low/no emission generation. Generation will increasingly be located at the distribution level, with a reduced number of large central generators at the bulk power system.

• Power electronic devices will be ubiquitous and layered hierarchical control schemes using a combination of direct control and incentive signals will be used to provide the necessary system flexibility.

• End-use customer will have an increased level of participation both in generation and load response.

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Resilient Microgrids Cont.

• Microgrids have the potential to facilitate this future in multiple ways.

• The large number of distributed devices can be integrated into layered control structures for scalability.

• Operations at the edge reduce single points of failure and increase system flexibility.

• Coordination between networks of microgrids and centralized controls will provide increased operational options when grid connected.

• Networks of microgrids will be able to self-assemble when there is a loss of the bulk power system.

Increasing Distribution System Resiliency using Flexible DER and Microgrid Assets Enabled by OpenFMB

The primary goal of this project is to increase

distribution resiliency through flexible operating strategies. This will be accomplished by actively

engaging utility and non-utility assets as flexible

resources.

Value Proposition

➢ DER deployments at moderate- to high-

penetration levels prevent a “business-as-usual”

approach

➢ Duke Energy has halted some self-healing

systems deployments due to moderate/high-

penetration PV concerns

➢ What is needed is a way to coordinate the

operation of DER, to make it a resource, and not

an obstacle

Project Objectives

➢ Develop flexible operating strategies that integrate

centralized and decentralized control systems (e.g., self-

healing/PV)

➢ Engage utility and non-utility assets to increase the

resiliency of critical end-use loads to all hazard's events

➢ Develop, and deploy, a layered control architecture

using commercial-off-the-shelf (COTS) equipment and

open-source code

Devices and Integrated Systems

Testing

Develop precise

models of emerging systems

Conduct device

testing and validation

Multi-Scale System

Integration and Testing

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OpenFMB Overview

Increasing Distribution System Resiliency using Flexible DER and Microgrid Assets Enabled by OpenFMB

A layered control structure with elements of a laminar control architecture developed to coordinate self-healing, microgrids, and DERs.

Concept of Operations (CONOPS) has been completed, including 12 use-cases

➢ Protection operates autonomously at the device level, using local set point groups

➢ OpenFMB maintains protection coordination after system changes (publish & subscribe)

➢ Central DMS determines “optimal” topology post event, issues commands

➢ DMS can engage transactive to incentivize non-utility assets to generate additional switching options

➢ Operations across layers are coordinated, enabling effective centralized and distributed system operations

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Overview and Problem Statement

➢ The bulk electric system is subject to a range of threats, which

could be mitigated by networks of microgrids collaboratively

interacting to distributedly achieve global objectives.

✓ During abnormal conditions (e.g., voltage collapse and/or

cascading events) microgrids can provide voltage and

frequency support to prevent the collapse of the bulk system.

✓ When a collapse cannot be avoided, networks of microgrids

can support critical end-use loads and the post event

restoration of the bulk system.

➢ In these roles, networks of microgrids act as the last line of

defense to safe-guard the bulk system, support critical end-use

loads, and serve as hardened points from which the bulk system

can be restored after an extreme event.

CITADELS Project Overview

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Objectives of Project

➢ Implement peer-to-peer control between microgrids using OpenFMB, leveraging

the DOE microgrid program and the Duke Resilient Distribution System project.

✓ Leverage OpenFMB which was designed to facilitate the distributed

coordination of large numbers of DERs in a peer-to-peer architecture

(diesel generators, fuel cells, PV, storage, and other modular generation).

✓ Implemented in commercially available equipment, which is highly

scalable.

➢ Apply collaborative autonomy concepts to coordinate the operation of

microgrids, leveraging the CleanStart DERMS Resilient Distribution System

project.

✓ Utilize grid-forming inverters to black start small- to moderate-sized

microgrids, and/or modular generation units.

✓ Coordinate the operation of microgrids to support bulk system operations.

✓ Enable self-assembling capabilities that can operate autonomously when

necessary.

✓ Utilize collaborative autonomy concepts such as “expert nodes” for federal

facilities.

CITADELS Project Overview

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➢ Scenario: There has been a loss of the bulk power system and microgrids are operating independently to support end-use loads.

➢ Goal: Interconnect islanded microgrids to increase the runtime of critical loads system wide➢ Microgrids will have varying levels of willingness/ability to participate➢ Critical loads can have tiers or priority levels

➢ Step 1: Data: Exchanged between microgrid controllers via an OpenFMB Harness

➢ Step 2: Calculation: Each microgrid calculates individual run-time of critical loads given available resources

➢ Step 3: Local Result: Each microgrid generates a list of what would be the “optimal” interconnection with other microgrids to increase runtime of critical loads

➢ Step 4: Consensus: The rank ordered lists are compared and a consensus of the first “best” set to interconnect is determined

➢ Step 5: Operation: Control signals are issues to reconfigure the system

Technical Approach Cont. (Self-Assembly Example)

Example Data to be Exchanged by a Microgrid

Example Operational Modes

Directly Measured Calculated or Derived

Collaborative Indicators

Normal Abnormal

Support critical load Restoration

Τ

Quality =

Validity

Authority =

x

y

z

=

16

Further Reading

• A. Dubey, A. Bose, M. Liu and L. N. Ochoa, "Paving the Way for Advanced Distribution Management Systems Applications: Making the Most of Models and Data," published in IEEE Power and Energy Magazine, vol. 18, no. 1, pp. 63-75, Jan-Feb 2020.

• Ronald B. Melton et. al., “Leveraging Standards to Create an Open Platform for the Development of Advanced Distribution Applications,” IEEE Access, vol. 6, pp. 37361-37370, 2018.

• S. Poudel, A. Dubey, P. Sharma, and Kevin P. Schneider, “Advanced FLISR with Intentional Islanding Operations in an ADMS Environment Using GridAPPS-D,” IEEE Access, vol. 8, pp. 113766-113778, 2020.

• Shiva Poudel, Anamika Dubey, and Kevin P. Schneider, “A Generalized Framework for Service Restoration in a Resilient Power Distribution System,” IEEE Systems Journal, early access, Aug 2019.

• Shiva Poudel and Anamika Dubey, “Critical Load Restoration using Distributed Energy Resources for Resilient Power Distribution System,” IEEE Transactions on Power Systems, vol. 34, no. 1, pp. 52-63, Jan. 2019.

• Rahul Ranjan Jha, Anamika Dubey, Chen-Ching Liu, Kevin, P. Schneider, “Bi-Level Volt-VAR Optimization to Coordinate Smart Inverters with Voltage Control Devices,” IEEE Transactions on Power Systems, vol. 34, no. 3, pp. 1801-1813, May 2019.

• R. Sadnan and A. Dubey, "Distributed Optimization using Reduced Network Equivalents for Radial Power Distribution Systems," in IEEE Transactions on Power Systems

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Further Reading (cont.)

• W. Du, F. K. Tuffner, K. P. Schneider, R. H. Lasseter, J. Xie, Z. Chen, and B. P. Bhattarai, “Modeling of Grid-Forming and Grid-Following Inverters for Dynamic Simulation of Large-Scale Distribution Systems,” IEEE Transactions on Power Delivery, vol. 36, no. 4, pp. 2035-2045, August 2021.

• P. Thekkumparambath Mana, K. P. Schneider, W. Du, M. Mukherjee, T. Hardy, and F. K. Tuffner, “Study of Microgrid Resiliency Through Co-simulation of Power System Dynamics and Communication Systems,” IEEE Transactions on Industrial Informatics, vol. 17 no. 3. pp. 1905-1915, March 2021.

• R. Jha, A. Dubey, and K. P. Schneider, “Conservation Voltage Reduction (CVR) via Two-Timescale Control in Unbalanced Power Distribution Systems,” IET Smart Grid, vol. 3, no. 6, pp.2515-2947, Dec. 2020.

• K. P. Schneider, C. Miller, S. Laval, W. Du, and D. Ton, “Networked Microgrid Operations to Support a Resilient Electric Power Infrastructure,” IEEE PES Electrification Magazine, vol. 8, no. 4, pp. 70-79, Dec. 2020.

• K. P. Schneider, N. Radhakrishnan, Y. Tang, F. K. Tuffner, C. C. Liu, J. Xie, and D. Ton, “Improving Primary Frequency Response to Support Networked Microgrid Operations,” IEEE Trans. on Power Systems, vol. 34, no. 1, pp. 659-667, Jan. 2019.

• K. P. Schneider, F. K. Tuffner, M. A. Elizondo, C. C. Liu, Y. Xu, S. Backhaus, and D. Ton, “Enabling Resiliency Operations across Multiple Microgrids with Grid Friendly Appliance Controllers,” IEEE Trans. on Smart Grid, vol. 9, no. 5, pp. 4755-4764, Sept. 2018.

• K. P. Schneider, F. K. Tuffner, M. A. Elizondo, C. C. Liu, Y. Xu, and D. Ton, “Evaluating the Feasibility to use Microgrids as a Resiliency Resource,” IEEE Trans. on Smart Grid, vol. 8, no. 2, pp. 687-696, March 2017.

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Acknowledgements

Students:

• Shiva Poudel (Ph.D., graduated May 2020, now with PNNL),

• Rahul Ranjan Jha (Ph.D., graduated Dec 2020, now with GE),

• Rabayet Sadnan (Ph.D. candidate)

• Nathan Gray (Ph.D. candidate)

• Dr. Kevin Schneider served in Ph.D. committees of Dr. Shiva Poudel, Dr. Rahul Ranjan Jha, and currently serving in Mr. Rabayet Sadnan’s PhD committee.

Gratefully acknowledge funding and support from DOE and PNNL

Thank you

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Questions?