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Optimal wind energy bidding strategies in real-time electricity market with multi-energy sources

机译：具有多种能源的实时电力市场中的最佳风能竞标策略

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摘要

This study investigates optimal wind power generator bidding strategies in the real-time electricity market. The goal is to maximise its operating profit by determining the optimal amount of wind power to bid in the real-time market. A bi-level stochastic optimisation model is proposed in which the upper-level problem is minimising the negative profit of wind power producers, while the low-level problem clears the real-time market. The uncertainties in the wind power production, thermal power, hydro power, demand, and energy storage are considered in the stochastic model. This study utilises a mathematical programming problem with equilibrium constraints (MPEC) and Karush-Kuhn-Tucker (KKT) conditions to transform the bi-level problem into an equivalent single-level mixed-integer linear problem (MILP). Case studies obtained with the IEEE RTS-24 Bus system demonstrate the effectiveness of the proposed model and the effect of scenarios on the wind power producer's profit.
机译：本研究调查了实时电力市场中的最佳风力发电机竞标策略。目标是通过确定在实时市场上竞标的最佳风能来最大化其运营利润。提出了一种二级随机优化模型，其中上级问题是使风电生产商的负利润最小化，而下级问题则清除了实时市场。随机模型考虑了风力发电，火力发电，水力发电，需求和储能方面的不确定性。这项研究利用具有平衡约束（MPEC）和Karush-Kuhn-Tucker（KKT）条件的数学编程问题将双级问题转换为等效的单级混合整数线性问题（MILP）。通过IEEE RTS-24总线系统获得的案例研究证明了所提出模型的有效性以及情景对风电生产商利润的影响。

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