Ex-ante Dynamic Capacity Withholding Assessment of Virtual Power Plants in Local Electricity Market

Document Type : Original Article

Author

Shahid Beheshti University

Abstract

This paper introduces an algorithm for the Local Electricity Market Operator (LMO) in distribution networks to assess dynamic capacity withholding by Virtual Power Plants (VPPs). Its main contribution is providing ex-ante indices to evaluate this withholding. The paper also quantitatively analyzes how LMO's risk aversion impacts the market power exerted by these withholding groups. The day-ahead market problem is tackled in three stages: estimating VPPs' optimal withholding strategy, determining optimal system scheduling, and analyzing network configuration changes to reduce market power. The results indicate that the exercise of market power by capacity-withholding groups increases the LMO's cost by an average of 35%. Furthermore, the simulation of collusion in the proposed model reveals that the market power of capacity-withholding groups increases by an average of 5% under the risk-averse behavior of LMO. Moreover, the results demonstrate that proactively restructuring the network according to the proposed algorithm on the 123-bus IEEE test system can reduce the market power of capacity-withholding groups and lower the average index to 25.12%.

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