考虑多重不确定性的概率暂态稳定约束最优潮流

Probabilistic transient stability constrained optimal power flow considering multiple uncertainties

摘要

【目的】针对高比例可再生能源电力系统并网的多种不确定性，为维持系统运行稳定性和经济性，提出了一种考虑多重不确定性的概率暂态稳定约束最优潮流(Probabilistic Transient Stability Constrained Optimal Power Flow, PTSCOPF)方法。【方法】首先，在综合考虑多重不确定性的影响下，建立了风电出力、负荷、故障类型、故障位置及故障清除时间不确定性变量的概率模型；其次，基于机会约束优化理论构建了电力系统PTSCOPF模型；之后，结合基于Gauss-Hermite积分的多点估计法和Gram-Charlier级数对随机变量进行确定性处理，再联合粒子群优化(Particle Swarm Optimization, PSO)算法和蚁群优化(Ant Colony Optimization, ACO)算法以实现PTSCOPF模型的有效求解；最后，在改进后的IEEE 39节点算例系统上进行了仿真。【结果】采用基于Gauss-Hermite积分的多点估计法计算得到的输出随机变量标准差的相对误差和均值均小于2.0%,该方法以27.9 s的计算时间和62 610·h^-1的期望成本实现了对系统运行方式的优化，优化后系统暂态稳定系数值为62.4。【结论】结果表明：在故障发生后，该方法在综合考虑多重不确定性因素的情况下，可以在较好地兼顾系统经济性的同时，以较低计算时间成本实现系统暂态稳定性的可靠提升，使系统过渡到暂态稳定状态，保障了电力系统的安全稳定运行。

Abstract

[Objective] In view of the various uncertainties of grid-connected power systems with a high proportion of renewable energy, in order to maintain the stability and economy of the system, a probabilistic transient stability constrained optimal power flow(PTSCOPF) method considering multiple uncertainties is proposed. [Methods] Firstly, taking into account the uncertain factors, probabilistic models of uncertainty variables of wind power output, load, fault type, fault location and fault clearance time are established. Secondly, the PTSCOPF model based on chance constraint optimization theory is constructed. Then, combined with the multipoint estimation method based on Gauss-Hermite integral and the Gram-Charlier series, the random variables are treated deterministically. Then particle swarm optimization(PSO) algorithm and ant colony optimization(ACO) algorithm are combined to realize the effective solution of PTSCOPF model. Finally, simulations are conducted on the modified IEEE 39-bus test system. [Results] The relative error and mean of the standard deviation of the output random variables computed using the multi-point estimation method based on Gauss-Hermite integration are less than 2.0%, and the method in this paper achieves the optimization of the way the system operates with a computation time of 27.9 s and an expected cost of 62 610 $·h^-1, and the value of the transient stability index of the system is 62.4 after the optimization. [Conclusion] The results show that after the occurrence of the fault, under the condition of considering multiple uncertain factors, the proposed method in this paper can realize the reliable improvement of the transient stability of the system with low computational time cost while taking into account the economy of the system, so that the system can transition to the transient stable state, which guarantees the safe and stable operation of the power system.

关键词

暂态稳定约束最优潮流 / Gauss-Hermite积分 / 多点估计 / 粒子群算法 / 蚁群算法 / 影响因素 / 可再生能源 / 电力系统

Key words

transient stability constrained optimal power flow / Gauss-Hermite integral / multipoint estimation / particle swarm optimization / ant colony algorithm / influencing factors / renewable energy / power system

基金资助

国家自然科学基金项目(52307109)

湖北省自然科学基金项目(2022CFB825)