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A Fuzzy Bilevel Model and a PSO-Based Algorithm for Day-Ahead Electricity Market Strategy Making

机译:提前电力市场战略制定的模糊双层模型和基于PSO的算法

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This paper applies bilevel optimization techniques and fuzzy set theory to model and support bidding strategy making in electricity markets. By analyzing the strategic bidding behavior of generating companies, we build up a fuzzy bilevel optimization model for day-ahead electricity market strategy making. In this model, each generating company chooses the bids to maximize the individual profit. A market operator solves an optimization problem based on the minimization purchase electricity fare to determine the output power for each unit and uniform marginal price. Then, a particle swarm optimization (PSO)-based algorithm is developed for solving problems defined by this model.
机译:本文应用双层优化技术和模糊集理论对电力市场中的投标策略制定进行建模和支持。通过分析发电公司的战略竞标行为,我们建立了一个模糊的双层优化模型,用于日前电力市场战略制定。在此模型中,每个发电公司都选择出价以最大化单个利润。市场运营商基于最小化购买电价来解决优化问题,以确定每个单元的输出功率和统一的边际价格。然后,开发了一种基于粒子群优化(PSO)的算法来解决该模型定义的问题。

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