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| Generator Strategic Bidding Based on Bounded Rationality Model of BSV and Breakpoints Optimization |
| Liu Congcong1,2, Li Zhengshuo1,2, Zhang Li1,2, Han Xueshan1,2, Lü Tianguang1,2 |
1. School of Electrical Engineering Shandong University Jinan 250061 China;
2. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan 250061 China |
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Abstract In the real-time market, generators can improve their profits through strategic bidding. In the classic strategic bidding model, generators optimize their own bidding strategies by estimating opponents' bidding behaviors. However, the model usually assumes that opponents' bidding behaviors obey a particular probability distribution. Therefore, how to reasonably estimate opponents' bidding behavior, remains to be further studied. In this regard, this paper improves the classic strategic bidding model of generators. By constructing a behavioral model of opponents based on the "bounded rationality model of Barberis, Shleifer, and Vishny (BSV)", the model reflects the reality that opponents are "realistic men" and have cognitive biases, in order to further improve the rationality of the bidding strategy.
Firstly, the bidding behavior model of the opponents is established by the bounded rationality model of BSV. Then, a bi-level optimization model is established for the generator to yield an optimal bidding strategy. The upper-level model is a bidding decision model that considers the bidding curve's "breakpoints optimization". The lower-level model is a market clearing model of the independent system operator (ISO), which considers the bidding behaviors of opponents. The lower-level model gives feedback to the upper-level model on the expected winning power output and the nodal price of the generator in the market under different bidding strategies. The bi-level optimization model can be transformed into a single-level optimization problem through methods such as Karush-Kuhn-Tucker (KKT) conditions, strong duality theorem, and special ordered sets. The transformed model is a mixed integer linear programming problem and can be directly solved by solvers.
Simulation results show that, when adopting the generator strategic bidding model based on the bounded rationality model, the profit of the generator is 20%~30% higher than the classical strategic bidding model, which illustrates the rationality of the bounded rationality model of BSV to estimate the opponents' behaviors. Meanwhile, when considering the breakpoints optimization, the generator's profit increases from $12.7 to $83, which proves that it can further improve the generator's profit. When a strategic generator is a marginal unit, the generator adjusts the bidding price of the winning segment to a price slightly lower than the lowest bidding price of the unsuccessful segment; otherwise, the generator adjusts the bidding price to any value between the cost and the clearing price. And the bidding price of the unsuccessful segment needs to be higher than or equal to the cost. Finally, a sensitivity analysis of the bounded rationality model's parameters and the segments' upper limit is performed, and the generator's estimation accuracy will affect the generator's bidding strategy with a computational cost of less than 30 s, which can satisfy the normal bidding process.
The following conclusions can be drawn from the simulation analysis: (1) The proposed model adopts the bounded rationality model to describe the bidding behaviors of different opponents more rationally, and develops a tailored bidding strategy. (2) Compared with the classical strategic bidding models that estimate the opponents are non-strategic bidding or strategic bidding, the proposed model improves the rationality of the generator's bidding strategy. (3) The proposed model can effectively adjust the total number of segments, segment capacities, and bidding prices of the generator's supply curve by breakpoints optimization strategy, further increasing the profit.
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Received: 04 May 2022
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2023, Vol. 38 
