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首页> 外文期刊>Journal of Power and Energy Engineering >Bidding Strategy in Deregulated Power Market Using Differential Evolution Algorithm
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Bidding Strategy in Deregulated Power Market Using Differential Evolution Algorithm

机译:基于差分进化算法的放松管制电力市场竞价策略

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The primary objective of this research article is to introduce Differential Evolution (DE) algorithm for solving bidding strategy in deregulated power market. Suppliers (GENCOs) and consumers (DISCOs) participate in the bidding process in order to maximize the profit of suppliers and benefits of the consumers. Each supplier bids strategically by choosing the bidding coefficients to counter the competitors bidding strategy. Electricity or electric power is traded through bidding in the power exchange. GENCOs sell energy to power exchange and in turn ancillary services to Independent System Operator (ISO). In this paper, Differential Evolution algorithm is proposed for solving bidding strategy problem in operation of power system under deregulated environment. An IEEE 30 bus system with six generators and two large consumers is employed to demonstrate the proposed technique. The results show the adaptability of the proposed method compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Monte Carlo simulation in terms of Market Clearing Price (MCP).
机译:本研究文章的主要目的是介绍差分进化(DE)算法,以解决管制市场中的出价策略。供应商(GENCO)和消费者(DISCO)参与投标过程,以使供应商的利润和消费者的利益最大化。每个供应商都通过选择投标系数来与竞争对手的投标策略相对应地进行战略性投标。电力或电力通过投标在电力交换中进行交易。 GENCO将能量出售给电力交换,然后将辅助服务出售给独立系统运营商(ISO)。本文提出了差分进化算法,用于解决电力系统在管制环境下的投标策略问题。具有六个发电机和两个大型用户的IEEE 30总线系统用于演示所提出的技术。结果表明,与市场清算价格(MCP)相比,该方法与粒子群优化(PSO),遗传算法(GA)和蒙特卡洛模拟相比具有较高的适应性。

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