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计及火电机组深度调峰成本的大规模风电并网鲁棒优化调度
作者:
作者单位:

1.强电磁工程与新技术国家重点实验室,华中科技大学,湖北省武汉市 430074;2.湖北省电力公司电力科学研究院,湖北省武汉市 430077

作者简介:

王淑云(1995—),女,硕士,主要研究方向:电力系统规划与优化运行。E-mail:wangshuyun@hust.edu.cn
娄素华(1974—),女,通信作者,教授,主要研究方向:电力系统规划与优化运行,新能源发电与电力技术经济。E-mail:shlou@hust.edu.cn
吴耀武(1963—),男,博士,副教授,主要研究方向:电力系统规划与运行优化。E-mail:ywwu@mail.hust.edu.cn

通讯作者:

基金项目:

国家自然科学基金资助项目(51677076);国家重点研发计划资助项目(2016YFB0900100);国家电网公司科技项目(521532190003)。


Robust Optimal Dispatch of Large-scale Wind Power Integration Considering Deep Peak Regulation Cost of Thermal Power Units
Author:
Affiliation:

1.State Key Laboratory of Advanced Electromagnetic Engineering and Technology,Huazhong University of Science and Technology, Wuhan 430074, China;2.Electric Power Research Institute of State Grid Hubei Electric Power Company, Wuhan 430077, China

Fund Project:

This work is supported by National Natural Science Foundation of China (No. 51677076), National Key R&D Program of China(No. 2016YFB0900100) and State Grid Corporation of China (No. 521532190003).

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    摘要:

    规模风电并网背景下,电力系统加大火电机组的调峰深度,充分挖掘现有下调备用空间,将是应对风电出力不确定性的有效方式之一。文中考虑火电机组工作在深度调峰(DPR)方式下的附加煤耗损失和机组寿命损耗,提出了计及火电机组DPR成本的规模风电并网鲁棒优化调度模型。考虑风电出力不确定性,建立了包括基于风电出力预测场景的调度主问题和基于极端场景的调控子问题的两阶段鲁棒优化模型,并引入不确定度参数控制调度计划的保守性,最终优化出经济性最优的鲁棒日前调度方案。基于算例分析证明所述模型的合理性与有效性。

    Abstract:

    Under the background of large-scale wind power integration, the power system raises the deep peak regulation (DPR) of the thermal power unit to fully exploit the existing downward spinning reserve capacity, which will be one of the effective ways to deal with the uncertainty of wind power. Considering the additional coal loss and unit life loss of the thermal power units which work in the DPR state, a robust optimal dispatching model taking the DPR cost of the thermal power unit into account is established in this paper. Considering the uncertainty of wind power output, a two-stage robust optimal model consisting of the main scheduling problem in forecasting scenes and the control sub-problem in extreme scenes is established, and the uncertain parameter is introduced to control the conservativeness of scheduling scheme. Finally, the economical optimal robust day-ahead scheduling plan is obtained. The rationality and effectiveness of the model are proved by case analysis.

    表 3 2种方案下优化结果对比Table 3 Comparison of optimization results with two schemes
    表 1 火电机组参数Table 1 Parameters of thermal power units
    表 4 方案3系统优化调度策略Table 4 Dispatching strategy of system optimization in scheme 3
    表 5 方案4系统优化调度策略Table 5 Dispatching strategy of system optimization in scheme 4
    图1 负荷与风电出力预测曲线Fig.1 Forecasting curve of load and wind power output
    图2 不同不确定度下优化结果对比Fig.2 Result comparison of optimization with different uncertainty
    表 2 传统调度和鲁棒调度的各项成本对比Table 2 Cost comparison between traditionaldispatching method and robust dispatching method
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引用本文

王淑云,娄素华,吴耀武,等.计及火电机组深度调峰成本的大规模风电并网鲁棒优化调度[J].电力系统自动化,2020,44(1):118-125. DOI:10.7500/AEPS20190128007.
WANG Shuyun,LOU Suhua,WU Yaowu,et al.Robust Optimal Dispatch of Large-scale Wind Power Integration Considering Deep Peak Regulation Cost of Thermal Power Units[J].Automation of Electric Power Systems,2020,44(1):118-125. DOI:10.7500/AEPS20190128007.

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  • 收稿日期:2019-01-28
  • 最后修改日期:2019-06-27
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  • 在线发布日期: 2020-01-04
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