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Suppliers' optimal biding strategies in day-ahead electricity market using competitive coevolutionary algorithms

机译:使用竞争性协同进化算法在日前电力市场中供应商的最优投标策略

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The present paper investigates the use of competitive coevolutionary algorithm in order to find supplier's optimal strategies in a Day-Ahead Electricity Market. Market game was expressed as an optimization problem based on the definition of Nash Equilibrium strategies where the game is playing by evolutionary agents, adapting theirs strategies to maximize the profits in a competitive environment. Day-ahead market where the IS0 uses a daily load profile submitted by each Service Load to perform a DC-OPF to determine Location Marginal Price and quantities bids from each supplier generators. Market agents' (suppliers) take part in the Day-ahead transactions and act strategically in order to increase their profits from each hourly transaction.
机译:本文研究了竞争协同进化算法的使用,以便在日前电力市场中找到供应商的最优策略。根据纳什均衡策略的定义,市场博弈被表达为优化问题,在这种情况下,演化主体在玩博弈,调整其策略以在竞争环境中获得最大的利润。日前市场,IS0使用每个服务负载提交的每日负载配置文件执行DC-OPF,以确定每个供应商生成的位置边际价格和数量竞标。市场代理商(供应商)参与日前交​​易,并采取策略性行动,以增加每小时交易的利润。

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