Bi‐level optimal bidding strategy of an aggregator in competition with rival aggregators. Issue 6 (3rd December 2020)

• Record Type: Journal Article
• Authors: Abbasi, Mohammad Hossein; Taki, Mehrdad; Zhang, Jiangfeng
• Is Part Of: IET smart grid. Volume 3:Issue 6(2020)
• Page Start: 898
• Page End: 905
• Publication Date: 2020-12-03
• Subjects: power markets -- pricing -- stochastic programming -- numerical analysis -- procurement -- cost reduction; two‐settlement pool‐based market -- energy procurement cost reduction -- energy bids -- price‐maker economic bidding problem -- stochastic Bi‐level optimal bidding strategy -- rival aggregator profit -- optimisation model -- numerical results; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2019.0360
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : This study formulates a stochastic bi‐level optimisation model for an aggregator participating in a two‐settlement pool‐based market while competing with rival aggregators. The market structure comprises a day‐ahead and a balancing market. The upper level problem maximises the profit of the aggregator, while the lower level problem minimises the cost of energy procurement. The novelty of this work is that the aggregator is considered as a price‐maker in both markets in which it participates in the day‐ahead market by offering energy and price bids, and in the balancing market by offering only energy bids. Therefore, this study formulates an optimisation model where the price‐maker economic bidding problem is considered without simplification, and serves as a reference for future studies. The proposed formulation is non‐linear due to its bi‐level structure and price‐maker offers. The problem is then properly linearised into a single‐level problem. The concept of conditional value at risk (CVaR) has been applied in the problem formulation to maximise average profit under worst scenarios. Finally, numerical results are presented through an illustrative case study to assess the performance of the proposed model. The results show that the profit of economic bidding is over 100% more than that of self‐schedule in low risk cases.