• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2016, Vol. 37 ›› Issue (6): 31-37.doi: 10.3969/j.issn.1000-7229.2016.06.005

• 新能源大规模集中并网规划 ·栏目主持 康重庆教授· • 上一篇    下一篇

风火联合系统不同备用模式的风险调度策略研究

嵇灵1,解玉磊2,黄鲁成1,牛东晓3   

  1. 1.北京工业大学经济与管理学院,北京市 100124;2.北京科技大学能源与环境工程学院,北京市 100083;3.华北电力大学经济与管理学院,北京市 100126
  • 出版日期:2016-06-01
  • 作者简介:嵇灵(1987),女,通信作者,博士,讲师,主要从事能量优化管理以及能源系统分析方面的研究工作; 解玉磊(1985),男,博士,讲师,主要研究方向为能源系统优化与能源环境; 黄鲁成(1956),男,博士,教授,主要研究方向为技术创新与技术管理; 牛东晓(1962),男,博士,教授,主要研究方向为电力负荷预测以及智能电网优化管理。
  • 基金资助:

    国家自然科学基金项目(71471059);中国博士后科学基金项目(2015M580034)

Risk Dispatch Strategy Study for Wind-Thermal Power System under Different Reserve Modes

JI Ling1, XIE Yulei2, HUANG Lucheng1, NIU Dongxiao3   

  1. 1.School of Economics and Management, Beijing University of Technology, Beijing 100124, China;
    2.School of Energy and Environment Engineering, University of Science and Technology Beijing, Beijing 100083, China;3.School of Economics and Management, North China Electric Power University, Beijing 100126, China
  • Online:2016-06-01
  • Supported by:

    Project supported by National Natural Science Foundation of China(71471059 ), and China Postdoctoral Science Foundation (2015M580034)

摘要:

电侧的需求响应以及蓄电设备运行灵活,可以作为虚拟备用资源,保障含风电等间歇性新能源发电的电力系统安全。为衡量虚拟备用资源给系统经济性和环保性的影响,分别建立传统火电备用和虚拟快速备用这2种含风电并网的电力调度模型。并考虑新能源输出功率、电力市场、机组参数等不确定因素给系统优化带来的风险,将区间两阶段随机优化模型与CVaR风险规避相结合,利用区间数、概率数对系统供给侧和需求侧的不确定因素与优化函数有效结合,同时体现决策者风险偏好。算例分析表明,此混合优化算法能够对含风电并网的电力系统不同旋转备用模式进行优化,权衡系统成本与系统风险。算例结果表明充分利用蓄电池、需求响应作为虚拟备用资源能有效降低系统成本和CO2排放。

关键词: 风电并网, 需求响应, 旋转备用, 区间规划, CVaR

Abstract:

Due to its feasibility, demand side response and storage device can be used as virtual reserve resources to guarantee the security of power system with intermittent wind power penetration. In order to evaluate the impact of virtual reserve resource on the economy and environmental protection of the system, this paper establishes two different kinds of electricity dispatching models with wind power penetration for traditional thermal reserve and virtual fast reserve respectively. With the consideration of system risk brought by renewable energy generation, electricity market and unit parameters, we combine the interval two-stage stochastic optimization model with CVaR risk theory. The uncertainties of supply side and demand side are integrated with optimization function though interval value and probability, which can reflect the risk preferences of decision makers. The example analysis shows that the proposed hybrid optimization algorithm can effectively optimize the different spinning reserve modes of power system with wind power penetration, and make better trade-off between system cost and risk. The results show that making full use of storage battery and demand response as virtual reserve resources can efficiently reduce the system cost and CO2 emission.

Key words:  wind power penetration, demand response, spinning reserve, internal programming, CVaR

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