求解暂态稳定约束最优潮流的混合算法  被引量:5

Hybrid Algorithm for Solution of Transient Stability Constrained Optimal Power Flow

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作  者:黄玉龙[1] 刘明波[1] 

机构地区:[1]华南理工大学电力学院广东省绿色能源技术重点实验室,广州510640

出  处:《电工技术学报》2012年第5期229-237,共9页Transactions of China Electrotechnical Society

基  金:国家自然科学基金资助项目(50777021)

摘  要:借助单机无穷大母线等值建立严格稳定判据,将轨迹灵敏度和微分进化技术结合起来求解暂态稳定约束最优潮流问题。以临界稳定功角作为暂态稳定约束功角阈值,并用预测失稳时刻修正功角阈值,提高了功角阈值的准确性和优化精度。按照单机无穷大母线等值,将故障分为稳定故障、极度稳定故障、一般不稳定故障和极度不稳定故障,将极度稳定故障从暂态稳定约束中剔除,省略相应灵敏度计算。为充分发挥改进轨迹灵敏度法的快速收敛特性和微分进化算法较强的全局搜索能力,提出将两者适当结合构造求解多故障暂态稳定约束最优潮流问题的混合算法。所提微分进化种群规模和计算量大大减小;含不稳定故障规格化稳定度的评价函数值更能综合反映种子的安全经济指标。在3机和10机试验系统上验证了所提算法的高效性和实用性。The strict stability criterion was established through one-machine infinite bus (OMIB) equivalence, and trajectory sensitivity and differential evolution (DE) techniques were applied to solving transient stability constrained optimal power flow (TSCOPF) problem, in which critical stable rotor angle was used as rotor angle threshold in transient stability constraint and the predicted unstable time was introduced to modify this rotor angle threshold, highly improving the threshold correctness and optimization accuracy. According to OMIB equivalence, faults were classified into stable, extreme stable, generally unstable, and very unstable faults. And extreme stable faults were deleted in transient stability constraints, saving trajectory sensitivity computing accordingly. Furthermore, in order to pursuing fast convergence features of the improved trajectory sensitivity method and global search ability of the DE method, a hybrid algorithm for TSCOPF under multi-contingency condition was formed by the combination of these two methods. Population size and computation burden are greatly decreased in the proposed DE method. The DE fitness value considering normalized stable margin for unstable faults better evaluates the individual's stability and economic index. Efficiency and practicality of the proposed method are validated on a 3-machine system and a 10-machine test system.

关 键 词:最优潮流 暂态稳定 单机无穷大母线等值 预测.校正 轨迹灵敏度 微分进化 

分 类 号:TM744[电气工程—电力系统及自动化]

 

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