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Modeling and Optimization of Multitype Power Sources Stochastic Unit Commitment Using Interval Number Programming

机译：区间数规划的多类型电源随机装置组合建模与优化

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摘要

The increasing penetration of renewable energy (RE) brings nonnegligible uncertainties to a power system, which should be carefully considered in the day-ahead scheduling for better RE utilization and higher power supply reliability. However, stochastic unit commitment of multitype power is a challenging problem considering the uncertainties of RE and the complicated characteristics of different power. This paper specifically focuses on the modeling and optimization approach for multitype power sources stochastic unit commitment (MPSSUC) with high penetration of RE and multiple uncertainties using interval number programming (INP). The MPSSUC model is established considering the elaborate characteristics of thermal power, hydropower, wind power and pumped storage power. The uncertainties of wind energy, natural water inflow, and power load are depicted by interval numbers. A novel particle swarm optimization-based bilevel solving approach is proposed for MPSSUC optimization, which preserves the interval properties of INP for better accommodation of uncertainties. Case studies on the IEEE 118-bus system and a realistic power system show that this study can effectively improve the RE accommodation while maintaining operation benefit. Analyses on the uncertainty level influence, trade-off between cost and robustness, and the operation characteristics by water regimens are also presented. (c) 2017 American Society of Civil Engineers.
机译：可再生能源（RE）的普及率不断提高，给电力系统带来了不可忽略的不确定性，在日程安排中应仔细考虑这些不确定性，以提高RE的利用率和供电可靠性。然而，考虑到RE的不确定性和不同电源的复杂特性，多类型电源的随机单位承诺是一个具有挑战性的问题。本文特别着重于使用区间数编程（INP）对具有高RE渗透性和多种不确定性的多类型电源随机单位承诺（MPSSUC）进行建模和优化的方法。建立MPSSUC模型时要考虑火电，水电，风电和抽水蓄能的精细特性。风能，自然水流入和电力负荷的不确定性用区间数表示。提出了一种新颖的基于粒子群优化的双级求解方法进行MPSSUC优化，该方法保留了INP的区间属性，以更好地适应不确定性。对IEEE 118总线系统和实际电源系统的案例研究表明，该研究可以有效地改善可再生能源的适应性，同时保持运营效益。还提出了不确定性水平的影响，成本与鲁棒性之间的折衷以及水方案的运行特性分析。 （c）2017年美国土木工程师学会。

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  • 来源
    《Journal of Energy Engineering》 |2017年第5期|04017036.1-04017036.17|共17页
  • 作者

    Zhou Yifan; Hu Wei; Min Yong; Xu Xialing; Li Yong;

  • 作者单位

    Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;

    Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;

    Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;

    Cent Branch State Grid Corp China, Dispatch & Commun Ctr, 47 Xudong St, Wuhan 430077, Hubei, Peoples R China;

    Cent Branch State Grid Corp China, Dispatch & Commun Ctr, 47 Xudong St, Wuhan 430077, Hubei, Peoples R China;

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