Dynamic bidding strategy for a demand response aggregator in the frequency regulation market

As a low-cost flexible resource, dynamic controllable load on the demand side offers potential for great appli-cation prospects in power system frequency regulation. To overcome the risks of various uncertain factors in electricity markets and realize the economic benefits of demand response, this study proposed a dynamic bidding strategy for demand-side resources to participate in the frequency regulation market by a demand response (DR) aggregator. A correlative uncertainty model of the market price and frequency regulation demand was con-structed employing the copula function, while the corresponding copula conditional value-at-risk model was used as a market risk measurement index to quantify the DR aggregator's decision risk. Consequently, an objective function that maximises the profit of the DR aggregator was established. Simultaneously, based on the analysis of the response potential of demand-side resources, a time-varying compensation method for the DR was proposed, and the bidding decision of the DR aggregator was dynamically optimised considering load deviation. Finally, case studies demonstrated that the accuracy and rationality of the uncertainty modelling are improved. The proposed dynamic optimisation method resulted in an increase of 16 % in operating profits. In addition, the revenue of users increased by 12 %. The impact of different risk preferences and the correlation between the stochastic electricity price and frequency regulation demand on the optimal decision result was analysed, based on which the manager of the DR aggregator can make decisions under different situations.

Automated summary

This study proposed a dynamic bidding strategy for demand-side resources to participate in the frequency regulation market through demand response aggregators. It constructed an uncertainty model for market price and frequency regulation demand, and used tools to measure market risks. The dynamic optimization method resulted in increased operating profits and user revenue.