| 引用本文: | 胡晓静,李 慧,崔 晖,等.考虑灵活爬坡辅助服务和弃风惩罚的现货电能量市场出清模型[J].电力系统保护与控制,2024,52(4):133-143.[点击复制] |
| HU Xiaojing,LI Hui,CUI Hui,et al.Cleaning model of a spot electric energy market considering flexible ramping auxiliaryservices and wind curtailment penalty[J].Power System Protection and Control,2024,52(4):133-143[点击复制] |
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| 摘要: |
| 为解决风电不确定性引起的系统爬坡能力不足、高比例风电接入时系统总运营成本偏高等问题，提出了计及改进灵活爬坡辅助服务和弃风惩罚的现货电能量市场出清模型。首先，分析了单台机组在出力状态、投入/退出过程中需要满足的爬坡速率约束，以及系统因净负荷波动需要满足的爬坡能力约束，提出了改进的灵活爬坡辅助服务产品。然后，以发电计划和机组状态为决策变量，构建了计及灵活爬坡辅助服务和弃风惩罚的目标函数。最后，通过两个算例从风电预测误差、风电渗透率和弃风惩罚成本等不同角度进行深入分析，验证所提出清模型的有效性。算例结果表明，所提出清模型既提高了系统运行的灵活性和经济性，又提升了高比例风电的消纳能力。 |
| 关键词: 现货市场 风电消纳 灵活爬坡 弃风惩罚 出清模型 |
| DOI：10.19783/j.cnki.pspc.231023 |
| 投稿时间：2023-08-08修订日期：2023-12-28 |
| 基金项目:国家重点研发计划资助(2022YFB2403400)；北京市重点实验室开放基金项目资助(DZ80-22-001) |
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| Cleaning model of a spot electric energy market considering flexible ramping auxiliaryservices and wind curtailment penalty |
| HU Xiaojing1,LI Hui2,CUI Hui1,LIU Sijia2,YE Lin3,LU Yi1,DING Qiang1 |
| (1. Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology (China
Electric Power Research Institute), Beijing 100192, China; 2. School of Automation, Beijing Information Science &
Technology University, Beijing 100192, China; 3. College of Information and Electrical Engineering,
China Agricultural University, Beijing 100083, China) |
| Abstract: |
| A cleaning model of a spot electric energy market considering modified flexible ramping auxiliary service and wind curtailment penalty is presented to solve issues such as insufficient system ramping capacity caused by wind power uncertainty and high total operating costs caused by a high penetration of wind power. First, a modified flexible ramping auxiliary service is proposed. This is done by analyzing the flexible ramping speed constraints that a single-unit needs to meet during output, startup and shutdown processes, and the flexible ramping ability constraints that the system needs to meet because of net load fluctuations. Secondly, an objective function that takes into account the modified flexible ramping auxiliary service and wind curtailment penalty is established. It uses output plans and the status of generators as decision variables. Finally, two examples are given to verify the effectiveness of the proposed cleaning model through in-depth analysis from different perspectives such as wind power forecasting error, penetration ratio, and curtailment penalty cost. The simulation results show that the presented model not only improves system flexibility and economy of system operation, but also enhances the consumptive ability of a high proportion of wind power. |
| Key words: spot market wind power consumption flexible climbing wind curtailment penalty cleaning model |
