Title: Event-Driven Demand Response for Electric Vehicles in Multi-aggregator Distribution Grid Settings (Eventgebaseerde vraagsturing voor elektrische voertuigen in distributienetten met meerdere aggregatoren)
Other Titles: Event-Driven Demand Response for Electric Vehicles in Multi-aggregator Distribution Grid Settings
Authors: De Craemer, Klaas
Issue Date: 10-Jul-2014
Abstract: In the search to accommodate increasing shares of renewable energy into today's electricity system, demand response has received renewed research attention. At the same time, the introduction of charging electric vehicles (EVs) at residential locations highlights the fact that current distribution grids were not dimensioned for the coinciding activation of such large loads. Solutions are needed that safeguard the state of distribution grids and at the same time allow large-scale demand response based on market objectives.In this thesis, scenarios are investigated where demand response of EVs is problematic for the state of the grid, and an algorithm is developed for demand response of charging EVs. This agent-based algorithm allows to integrate typical market objectives with the hard constraints at the distribution grid level. Through simulations, the severity of the conflict between market and technical objectives is examined, and the use of voltage droop control as possible solution is evaluated.
Table of Contents: 1 Introduction
1.1 Smart grids
1.2 Demand Response
1.3 Ancillary services
1.4 Challenges & requirements
1.5 Outline & context
2 Electric Vehicles & Communication
2.1 Charging of EVs and limitations
2.2 Standardization efforts
2.3 Vehicle-grid communication
2.4 Conclusion
3 Algorithms for Demand Response of Electric Vehicles
3.1 Distributed DR algorithms
3.2 Centralized DR algorithms
3.3 Aggregate & dispatch DR algorithms
3.4 Conclusion on the DR algorithms
3.5 Distribution grid congestion
3.6 Ancillary services and grid support
3.7 Conclusion
4 Simulator for Demand-Response Interaction
4.1 Structure overview
4.2 Data logging and Matlab interface
4.3 Loadflow simulation
4.4 Data models
4.5 Conclusion
5 Multi-Agent Market-Based Control for Electric Vehicle Charging
5.2 Multi-agent MBC with planning
5.3 Shortcomings
5.4 Conclusion
6 Event-based Multi-Agent Market-Based Control: RT-MBC
6.1 Introduction
6.2 Dual coordination
6.3 Event-based interaction
6.4 Energy compensation
6.5 Conclusion
7 Validation
7.1 Demand function evaluation
7.2 Communication limitations
7.3 Conclusion
8 Market-setting Applications
8.1 Problem description
8.2 Grid topology and agent structure
8.3 ToU coordinated charging
8.4 ToU coordinated charging, passive distribution grid
8.5 ToU coordinated charging, active distribution grid
8.6 Balancing case
8.7 Balancing case, passive distribution grid
8.8 Balancing case, active distribution grid
8.9 Multi-aggregator case
8.10 Multi-aggregator case with active distribution grid
9 Conclusions and Future Work
9.1 Summary of the chapters
9.2 Conclusions regarding the research objectives
9.3 Future work
A Extended Load Flow Results
B Balancing case
Publication status: published
KU Leuven publication type: TH
Appears in Collections:ESAT - ELECTA, Electrical Energy Computer Architectures

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