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中长期市场下发电企业发电与购煤安排两阶段决策模型 被引量:6

Two-stage Decision-making Model of Power Generation and Coal Purchase Arrangement for Power Generation Companies in Medium-and Long-term Market
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摘要 目前针对市场环境下发电企业生产决策的研究往往仅考虑电力市场的相关因素,但实际上燃煤作为发电企业的主要可变成本早已市场化,企业亟需紧密结合电力市场和煤炭市场,对多种市场交易类型中的发电量与购煤量进行时序优化,以提升利润降低风险。针对该问题,提出一种基于条件风险价值(conditional value at risk,CVaR)的发电企业发电与购煤安排两阶段决策模型。首先介绍中长期市场下包括年前优化、年内滚动优化的两阶段决策框架;其次建立基于CVaR的发电与购煤安排两阶段决策模型,对每月多市场中的发电量和购煤量进行决策;最后以某燃煤发电企业为研究对象进行算例分析,结果表明:所提模型可以实现发电企业发电与购煤安排的协调时序优化,通过将全年发电量和购煤量在年度合约市场和月度市场中进行合理分配,可以在控制CVaR风险的同时获得全年利润的最大化。 The current research on the decision-making of power generation companies under the market environment only considers the factors in electricity market.As the main variable cost,however,the coal has been deregulated for a long time.Companies need to closely combine the electricity market and the coal market,and optimize the timing of power generation and coal purchase in various market transactions.To solve this problem,a two-stage decision-making model of power generation and coal purchase arrangement based on conditional value at risk(CVaR)is proposed.Firstly,a two-stage decision-making framework including year-ahead optimization and rolling optimization within a year is established.Secondly,a decision-making model based on CVaR is proposed to determine the amount of power generation and coal purchase in multiple markets.Finally,a case study of one coal-fired power generation company is analyzed.The result shows that the proposed model can realize the timing optimization of power generation and coal purchase arrangement.By allocating power generation and coal purchase in annual and monthly markets,the profits can be maximized while the risk is controlled.
作者 王旭东 高赐威 WANG Xudong;GAO Ciwei(School of Electrical Engineering,Southeast University,Nanjing 210096,Jiangsu Province,China)
出处 《电网技术》 EI CSCD 北大核心 2021年第10期3992-3999,共8页 Power System Technology
关键词 中长期市场 发电与购煤安排 条件风险价值 时序优化 滚动优化 medium-and long-term market power generation and coal purchase arrangement conditional value at risk timing optimization rolling optimization
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