Agent-based simulator for the German electricity wholesale market including wind power generation and widescale PHEV adoption

An agent-based model is applied to model the German electricity wholesale market with its four major German utility companies. The model is utilized to assess base and peak power spot prices for scenarios implying doubling or tripling wind generation capacity in Germany. Furthermore, the effect of 8 million Plug-In Hybrid Electric Vehicles (PHEVs), incorporating different charging/discharging patterns, on spot prices is evaluated. In the model the power generating units within the utilities are modeled by agents. These agents are trained to increase their profits by using a reinforcement learning approach combined with a genetic algorithm resulting in heuristically optimized bidding strategies. This approach allows to take into account strategic market behavior and the exercise of market power when analyzing future wind expansion and wide scale PHEV adoption scenarios. The wind generation is considered as an exogenous input to the model which estimates potential electricity prices and total cost for consumers.

[1]  Martin V. Butz,et al.  Rule-Based Evolutionary Online Learning Systems - A Principled Approach to LCS Analysis and Design , 2006, Studies in Fuzziness and Soft Computing.

[2]  Martin V. Butz,et al.  An algorithmic description of XCS , 2000, Soft Comput..

[3]  Jonn Axsen,et al.  The Early U.S. Market for PHEVs: Anticipating Consumer Awareness, Recharge Potential, Design Priorities and Energy Impacts , 2008 .

[4]  Marco Colombetti,et al.  What Is a Learning Classifier System? , 1999, Learning Classifier Systems.

[5]  Martin V. Butz,et al.  The XCS Classifier System , 2006 .

[6]  M O'Malley,et al.  Impact of optimal charging of electric vehicles on future generation portfolios , 2009, 2009 IEEE PES/IAS Conference on Sustainable Alternative Energy (SAE).

[7]  Eric Bonabeau,et al.  Agent-based modeling: Methods and techniques for simulating human systems , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Rashid A. Waraich.  Plug-in hybrid electric vehicles and smart grids: Investigations based on a micro-simulation , 2009 .

[9]  Goran Andersson,et al.  Investigating PHEV wind balancing capabilities using heuristics and model predictive control , 2010, IEEE PES General Meeting.

[10]  Brett David Williams,et al.  Commercializing light-duty plug-in/plug-out hydrogen-fuel-cell vehicles: , 2007 .

[11]  Thomas J. Overbye,et al.  Power System Level Impacts of PHEVs , 2009, 2009 42nd Hawaii International Conference on System Sciences.

[12]  G. Andersson,et al.  Demand Management of Grid Connected Plug-In Hybrid Electric Vehicles (PHEV) , 2008, 2008 IEEE Energy 2030 Conference.

[13]  Felix Müsgens,et al.  Market Power in the German Wholesale Electricity Market , 2004 .

[14]  G. Andersson,et al.  Evaluating congestion management schemes in liberalized electricity markets using an agent-based simulator , 2006, 2006 IEEE Power Engineering Society General Meeting.

[15]  Stewart W. Wilson.  Classifier Fitness Based on Accuracy , 1995, Evolutionary Computation.

[16]  Felix Müsgens,et al.  Quantifying Market Power in the German Wholesale Electricity Market Using a Dynamic Multi-Regional Dispatch Model , 2006 .

[17]  Goran Andersson,et al.  On integration of plug-in hybrid electric vehicles into existing power system structures , 2010 .

[18]  Daniel Veit,et al.  An Agent-Based Analysis of the German Electricity Market with Transmission Capacity Constraints , 2009 .

[19]  J. Bower,et al.  A model-based analysis of strategic consolidation in the German electricity industry , 2001 .

[20]  Goran Andersson,et al.  Integration of Plug-In Hybrid Electric Vehicles into energy networks , 2009, 2009 IEEE Bucharest PowerTech.

[21]  David M Newbery,et al.  Power Markets and Market Power* , 1995 .

[22]  Petr Kadurek,et al.  Electric Vehicles and their impact to the electric grid in isolated systems , 2009, 2009 International Conference on Power Engineering, Energy and Electrical Drives.

[23]  Filip Johnsson,et al.  Plug-in hybrid electric vehicles as regulating power providers: Case studies of Sweden and Germany , 2010 .