mas²tering workshop #2 : managing flexibility september 2015 maryse anbar, r&d project manager...
Post on 16-Jan-2016
215 Views
Preview:
TRANSCRIPT
Mas²tering workshop #2 : managing flexibility
September 2015
Maryse Anbar, R&D project Manager
Agenda
Greenlys : the agregator model and lessons learned on its implementation
Mas²tering : decentralized solution for decentralized production
00/00/2015TITRE DE LA PRESENTATION ( MENU "INSERTION / EN-TETE ET PIED DE PAGE")
2
A smart grid reference project covering the complete value chain
Exploring the role of the agregator
An ambitious project, complementary partners
1st French urban real scale Smart Grid demonstrator (Grenoble and Lyon)
43 M€ investment thanks to ADEME subsidies
4 years experiment 2012-2016
Complementary partners representative of the French energy landscape
4
TSO / DSO
ProducerRetailer
Academics Manufacturers ITNon profit
Organizations
Cir
cle
1C
ircl
e 2
With residential and commercial customers
Two complementary test areas:
Lyon and nearby cities4e, 5e, 6e et 9e districts and Confluence
Saint Didier au Mont d’Or, Charbonnières les Bains, Collonges au Mont d’Or, Saint Cyr au Mont d’Or, Sathonay Camp
GrenobleInitially Caserne de Bonne and presqu’ile scientific districts
Enlargement to the whole city
Two experimental cities
20112012
Nov 2013
5
Concrete solutions tested on the whole power value chain
EV Integration
DSM tools + curtailement
Smart grid management(metering, observability, analysis, self healing)
Renewables and CHP integrationCost / Benefits
Analysis
Flexibility agregation
Smart functionnalitiesthanks to smart meter (Linky)
6
A flexible and
reconfigurable grid
Means of mobilization and control downstream
meters
Aggregation tools
Recherche d’un
optimum
global
Final customer
• Reduce its electricity bill and manage its carbon footprint
Provider and
producer
• Opportunities of different bill offers and of investments optimization
DSO and TSO
• Management and investments optimization, DER integration, grid reliability
Community
• Achievement of DERs objectives, and conservation of energy with a global economic optimum
Highlighting models of value creation
7
Flexibility in the home
8
> 60 000 curtailments
The Aggregator new actor of the Smart Grid system
The operator who manages the flexibility (load curtailments, decentralized power productions and storage), to assist the electrical
network
Using an operational control command chain
In interaction with the other actors of the system: network operators, producers, providers, consumers
With the requirement to maintain the user’s comfort
9
10
IT
IT
Admin interface
CRM
AggregatorIT
Call Centre
Schneider customers
XX Customers
Customer interface
XX
An operationnal B2C curtailment IT system
Progression :• More than 60 000 curtailments carried out during the three last heating seasons• Data acquisition in order to build predictive models
• Technical characterization of curtailments: rebound and payback effects
• An analysis of the impact of these curtailments on user comfort
• Flexibility forecasting and curtailment optimization algorithms
• First interaction tests with the Distribution System Operator
11
The Aggregator experimental results of curtailments
Typical curtailment
Mini-cogeneration of 50kV installed in Grenoble and remotely controlled by an agregator platform
12
An installation done on a collective residential site
• A boiler sized for an annual need for 700 MWh, integrating a thermal solar installation and 2 conventional gas boilers ,
• A connecting with an obligation purchase contract
— The technical characteristics of the module
• An internal combustion engine Cogengreen, fed in the natural gas
• Nominal electric power of 50 kWe (33 % of yield(efficiency))
• Nominal thermal power of 86 kWth (57 % of yield(efficiency))
• Commitment of the manufacturer on a rate of 95 % availability
• The cogeneration is coupled with aero-thermic allowing to dissipate a possible surplus of heat consumed by the site
=> Limit electric peak, good feedback from customer (comfort ensured)
project co-funded by the European Commission within the 7th Framework Program (Grant Agreement No. 619682)
Mas²tering project :decentralized ‘intelligence’
for decentralized energy sources
A STEP TOWARDS MORE DECENTRALIZED INTELLIGENCE
MAS2TERING CHALLENGES
Enhancing interoperability – to allow for convergence of network (ICT) and transmission (grid) protocols;
Ensuring reliability and security – for trusted services provision and enhanced resilience;
Enhanced flexibility and increased resilience – through decentralized and self-organizing architectures;
Optimal grid monitoring and management – thanks to smart ICT components;
Upgrading energy infrastructure – releasing investment thanks to innovative cross-domain business models
USE CASE #2 (DISTRICT-LEVEL)
Research focuses Expected outcomes
• Multi-scale hierarchical management of dispersed & heterogeneous sources and loads
• Data access control & security• Data transp. reliability & performances• Prediction reliability
• Peak load reduction & energy savings (up to 12-15%)
• Effective data integrity assurance techniques
• Effective sabotage prevention techniques
Decentralized energy management in a local area with Multi-Agents
Increasingly decentralized energy production in Europe (district-scale)
MULTI-AGENTS DECISION MAKING TO ACT OPTIMALLY WITH ‘MINIMUM’ INFORMATION
Optimize global welfare and reconciliate possible antagonist objectives
Distributed management,control and optimization of the grid
Perform business operations and simulate/test new business
ideas and services
What if the architecture is totally decentralized ?
What if a district manager drives the optimization ?
1. Implement agents + holonic organization + data models
2. Situation assessment and prediction ICT components
3. MAS based grid optimization and self-healing components
Decentralized Optimization
District Manager
WP3 GAIA method Jade Framework
JADE Container
Hardware device
Age
nt
Man
agem
ent
Ser
vice
Age
nt
Dire
cto
ry
Fac
ilita
tor
Socio
Econ
om
ic
Ag
en
t
Security management (JADE extension)
Obj
ect
Log
ging
Co
ntr
ol
Ag
ent
JADE extensions
Agent Communication
Channel Java C
lasses
(Ph
ysic
al A
gen
t)
3-rd
par
ty s
oft
war
e
JADE Agents
PROJECT DIRECTION : DEVELOP ENERGY MANAGEMENT SYSTEM BASED ON ‘MULTI-AGENTS’ PLATFORM GENERIC COMPONENTS OF ‘JADE’
BOTTOM-UP APPROACH THROUGH PHYSICAL TEST : WHAT REMOTE CONTROL AT DISTRICT LEVEL
Explore direct communication opportunities and energy management
adaptation to critical events
Protocols : WMbus ? Meshed network ? (Sigfox ?)Orders : on/off, voltage regulation ?
Multi-agents in the cloud or in the on-site M2M ? Hybrid ?
Emergency mode
TOP DOWN APPROACH THROUGH SIMULATION : ASSESSING VALUE OF FLEXIBILITY FOR LV GRID AND DEFINING ECONOMIC SIGNALS
Projected grids
Simulations
1) Standard grid
2) Projected grid
3) Smart grid (with local MAS optimization)
21
Agregator has technically proved its ability to manage different kind of flexibility and answer to wholesale market price signals
Multi-agents techniques offering the opportunity to explore a decentralized solution for decentralized flexibility sources aiming to provide a technical framework to think resilient, reactive and secured local energy management
It can be an innovative and efficient way to complete the agregator services panel, and more generally the one of utility from the installation to the energy management services in a context of emergence of ‘prosumers’
Behind this two projects, the opportunity to explore what level of centralization of data and the intelligence for energy management
22
Energy Transition is on his way creating a need for flexibility at different scale
23
Source : SDET
24
Organized market at supra and national level
Generators bid power plants at marginal cost, from the cheapest to the most expensive one (merit order)
Intersection between supply and demand determines the assets that will be offered and the power price for each hour of the next day
Forward demand-supply balance
Merit-order and price setting
Real-time balancing
We used to have 3 kind of reserve to answer unplanned events
RES intermittency impact
25
Capacity market as one of the answer in France
Price signals for national flexibility needs
With digitalization, door is open to new energy services with among other flexibility management
26
Datamanagement
Energy
Telecom
Smart grid are at the corner of energy, telecom and data management
Technical Drivers Social will
Increasing levels of Hybrid and Electric Vehicle
More active operation of the distribution networks
Much greater active control of the distribution networks
ICT and storage
Increase the potential for load management
Huge increase in amount of data
Ensuring access to consumer consumption data
Increasing levels of micro-cogeneration, hybrid boilers, …
Data protection and accuracy issues
Changes at local scale
27New Business Models towards Energy Decentralised Management (Micro-Grids)
Introduction of small
distributed generation
More renewables, intermittent production
Energy Efficiency
Data management
Smart Metering
Smart grid Technology (energy box for remote control, link boxes, …)
Lower battery cost
top related