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| 考虑多种电价场景的水电机组参与日前市场双层报价模型 |
| Consider the participation of hydropower units in the day-ahead market two-layer quoting model under multiple electricity price scenarios |
| 投稿时间：2025-06-24 修订日期：2025-12-10 |
| DOI： |
| 中文关键词: 阶梯式报价曲线 日前市场 双层模型 短期优化调度 机组报价 |
| 英文关键词: Tiered quote curves day-ahead market Two-tier model Optimize scheduling in the short term Unit quotation |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目）；中央高校基本科研业务费专项资金资助 |
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| 中文摘要: |
| 为了制定出符合水电站及水电机组约束的各机组阶梯式报价曲线,从而达到促使水电站在价格不确定的日前市场中收益最大化的目的,本文建立了一种考虑多种电价场景的水电机组参与日前市场双层报价模型。该模型由考虑水电站发电调度的外层模型及考虑机组报价的内层模型嵌套构成,其中外层模型考虑水电站调度约束并结合内层模型返回的期望收益,并利用动态规划优化水电站短期优化调度,从而实现水电整体收益最大化；内层模型首先利用多种电价场景描述电价的不确定性,其次在机组优化分配的基础上,给出了考虑水电机组约束和中长期合约电量的阶梯式报价生成策略,并利用遗传算法优化并生成各机组的阶梯式报价曲线,最后以电站期望收益作为适应度值返回给外层模型。算例分析结果表明,该模型相对传统的保守报价方式,水电站期望收益提高了2.4%,能够在兼顾水电机组运行及水电站运行的物理约束的同时,科学得出各机组的报价曲线,为水电站参与日前市场报价提供了决策参考。 |
| 英文摘要: |
| In order to formulate a tiered quotation curve for each unit that meets the constraints of hydropower stations and hydropower units, so as to maximize the revenue of hydropower stations in the uncertain day-ahead market, this paper establishes a two-tier quotation model for hydropower units to participate in the day-ahead market considering multiple electricity price scenarios. The model is composed of an outer model considering the power generation scheduling of hydropower stations and an inner model considering unit quotations, in which the outer model considers the scheduling constraints of hydropower stations and combines the expected revenue returned by the inner model, and uses dynamic programming to optimize the short-term optimal scheduling of hydropower stations, so as to maximize the overall revenue of hydropower. The inner model firstly uses a variety of electricity price scenarios to describe the uncertainty of electricity prices, and secondly, on the basis of the optimal allocation of units, a stepwise quotation generation strategy considering the constraints of hydropower units and the medium and long-term contract electricity is given, and the genetic algorithm is used to optimize and generate the stepped quotation curves of each unit, and finally the expected income of the power station is returned to the outer model as the fitness value. The results show that compared with the traditional conservative quotation method, the expected income of hydropower stations is increased by 2.4%, and the quotation curves of each unit can be scientifically obtained while taking into account the physical constraints of hydropower unit operation and hydropower station operation, which provides a decision-making reference for hydropower stations to participate in the day-ahead market quotation. |
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