中国电力 ›› 2016, Vol. 49 ›› Issue (5): 163-170.DOI: 10.11930/j.issn.1004-9649.2016.05.163.08

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基于风险约束的风电和水电联合日前调度优化模型

张玮,李丹,张翔宇,李佳宇,谭忠富   

  1. 华北电力大学能源经济与环境研究所,北京102206
  • 收稿日期:2016-02-04 出版日期:2016-05-16 发布日期:2016-05-16
  • 作者简介:张玮(1971—),男,山东潍坊人,高级工程师,从事电力经济、政策体制、战略管理相关研究。E-mail: zhangwei03@sina.com
  • 基金资助:
    国家自然科学基金资助项目(71273090,71573084)

Risk-Constrained Day-Ahead Scheduling Optimization Model of Hydro-Wind Power Generation

ZHANG Wei, LI Dan, ZHANG Xiangyu, LI Jiayu, TAN Zhongfu   

  1. Institute of Energy Economics and Environment, North China Electric Power University, Beijing 102206, China
  • Received:2016-02-04 Online:2016-05-16 Published:2016-05-16
  • Supported by:
    This work is supported by National Natural Science Foundation of China (No.71273090, No.71573084).

摘要: 为解决风电随机性对电力系统稳定运行的影响,引入梯级水电机组为风电机组提供调峰备用,构建了考虑风险约束的风电和水电联合日前调度优化模型。首先,分别构建了梯级水电机组输出功率模型、风电机组输出功率模型,以系统调度净收益期望值最大化作为目标函数,综合考虑风水电协调约束、系统功率平衡约束,构建了风水电联合调度模型。进一步,为了考虑风电不确定性给系统带来的风险因素,建立了计及风险约束的风水电联合随机优化调度模型,并采用启发式算法对模型进行线性化处理。最后,选择3个风力发电场和2个流域的7个水力发电厂组成仿真系统,对风水电联合调度优化进行算例仿真模拟。结果表明:所提出的水风电联合运行策略可以用来促进风力发电,最大化系统运营期望收益的同时最小化系统运营风险,因此,在进行风电和水电联合调度时应综合考虑内部和外部不确定性因素,以获得能够兼顾运营收益和风险的最优解。

关键词: 风电, 水电, 日前调度, 风险, 优化模型

Abstract: In order to overcome the influence of wind power on power system operation, peak shaving is introduced. The wind power output and cascaded hydroelectric unit model are modeled at first. Based on hydro-wind coordination constraints, a day-ahead scheduling optimization model is built with consideration of risk constraint. A heuristic algorithm is applied to linearize proposed model. At last, a simulation system is built with three wind farms and seven hydroelectric power stations in two basins. The simulation results show that proposed hydro-wind coordination strategy can be used to increase wind power generation and reduce operation risks. Both internal and external uncertain factors need to be integrated into the joint scheduling optimization of hydro-wind power generation, which is essential for obtaining optimization solution considering both system operation benefits and risks.

Key words: wind power, hydropower, day-ahead scheduling, risk, optimization model

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