基于上下游市场联动的燃煤电厂两阶段决策模型OA北大核心CSTPCD
A Two-stage Decision Model for Coal-fired Power Plants Based on Upstream and Downstream Market Linkages
随着大宗能源价格大幅波动及新能源上网冲击,作为现阶段不可或缺的燃煤电厂经营举步艰难.对上游燃料采购及仓储成本进行优化管控的同时,对下游电力市场竞价上网进行联动决策,可在一定程度上提高双碳背景下火力发电企业的生存空间.针对上下游市场联动决策周期不一致以及固定发电成本二次曲线无法反映发电成本变动的问题,提出一种基于上下游市场联动的购煤与竞价燃煤电厂两阶段优化决策模型.首先提出燃煤电厂上下游市场的联动模型;其次建立购煤与竞价策略两阶段决策模型,并讨论条件风险价值对决策的影响;最后以燃煤电厂 A 进行算例分析和两阶段决策模型的有效性验证.算例结果表明,所提两阶段决策模型可以解决上述问题,实现利润最大化.
With the sharp fluctuations in bulk energy prices and the impact of new energy on the grid,the operation of coal-fired power plants,which are indispensable at this stage,is difficult.While optimizing the management and control of upstream fuel procurement and storage costs,the linkage decision-making for the downstream power market bidding and grid connection can improve the living space of thermal power generation enterprises under the carbon peak and carbon neutrality background to a certain extent.Aiming at the problems of inconsistent decision-making cycles in the linkage between upstream and downstream markets and the fact that the fixed power generation cost quadratic curve cannot reflect the changes in power generation costs,this paper proposes a two-stage optimization decision-making model for coal-fired power plants based on the linkage of upstream and downstream markets.First,the linkage model of upstream and downstream markets of coal-fired power plants is proposed.Then,a two-stage decision-making model of coal purchase and bidding strategy is established,and the influence of conditional value-at-risk on decision-making is discussed.Finally,the coal-fired power plant A is used to analyze an example and verify the validity of the two-stage decision-making model.The calculation example shows that the two-stage decision-making model proposed in this paper can solve the above problems and maximize profits.
廖志伟;郑广昱;谢汛恺;王博文;张文锦
华南理工大学电力学院,广东省 广州市 510640
经济学
电煤市场日前电力市场条件风险价值滚动优化两阶段决策
coal marketday-ahead power marketconditional value-at-riskrolling optimizationtwo-stage decision
《中国电机工程学报》 2024 (008)
3036-3045,中插8 / 11
国家自然科学基金项目(51437006). Project Supported by National Natural Science Foundation of China(51437006).
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