Voltage Stability Constrained Reactive Power Optimization Based on Improved Particle Swarm Optimization
Hu Yaoxing1, Liu Lihua2, Ma Mingyang3
1. School of Inter-culture Studies,Jiangxi Normal University,Nanchang 330022; 2. National Electric Power Dispatching and Control Center,Beijing 100031; 3. Tianjin Electric Power Maintenance Company,Tianjin 300143
Abstract：Voltage stability constrained reactive power optimization model is formulated. In this model, minimizing the active power loss and enhancing voltage stability are considered as objective functions. In order to avoid the premature phenomenon and local convergence of conventional particle swarm optimization (PSO) algorithm, a improve PSO for reactive power optimization is proposed. A fitness sharing mechanism is applied to adjust particles’ fitness so as to enhance the global searching ability. Time variant acceleration coefficients strategy is introduced in order to balance the global exploration and the local exploitation ability of the population in search space. The proposed approach is carried out on the IEEE 30-bus test system, its feasibility and effectiveness are demonstrated.
胡瑶星,刘力华,马明阳. 基于改进粒子群算法的电压稳定约束无功优化分析[J]. 电气技术, 2015, 16(02): 40-44.
Hu Yaoxing, Liu Lihua, Ma Mingyang. Voltage Stability Constrained Reactive Power Optimization Based on Improved Particle Swarm Optimization. Electrical Engineering, 2015, 16(02): 40-44.
[1] 张斌, 刘幸. 基于量子粒子群算法的电力系统无功优化[J]. 电气技术, 2012(2): 15-19. [2] 胡彩娥, 杨仁刚. 考虑电压稳定的电力系统无功优化规划[J]. 继电器, 2005, 33(4): 22-25, 30. [3] 邱威, 张建华, 刘念. 电压稳定约束下最优潮流的多目标优化与决策[J]. 电力自动化设备, 2011, 31(5): 34-38. [4] Alsac O, Bright J, Prais M, et al. Further developments in LP-based optimal power flow[J]. Power Systems, IEEE Transactions on, 1990, 5(3): 697-711. [5] Momoh JA. El-Hawary M E,adapa R.A review of selected optimal power flow literature to 1993. I. nonlinear and quadratic programming approaches[J]. IEEE Transactions on Power Systems, 1999, 14(1): 96-104. [6] Sun Di, Ashley B, Brewar B, et al. Optimal power flow by Newton approach[J]. IEEE Transactions on Apparatus and Systems, 1984, 103(10): 2864-2880. [7] 周晓娟, 蒋炜华, 马丽丽. 基于改进遗传算法的电力系统无功优化[J]. 电力系统保护与控制, 2010, 38(7): 37-41. [8] 李秀卿, 孙守鑫, 张超, 等. 基于改进细菌群体趋药性算法的无功优化[J]. 电力系统保护与控制, 2011, 39(8): 56-59. [9] 张炳才, 秦四娟, 乔世军, 等. 基于改进微分进化算法的电力系统无功优化[J]. 电力系统保护与控制, 2010, 38(15): 91-94, 122. [10] 王韶, 张煜成, 周鑫, 等. 基于一种改进蚁群算法的动态无功优化[J]. 电力系统保护与控制, 2012, 40(17): 100-104. [11] 刘苏云, 丁晓群. 利用混沌鱼群算法的配网无功优化[J]. 电力系统及其自动化学报, 2014, 28(1): 44-48. [12] Kennedy J, Eberhart RC. Particle swarm optimization[C]. Proceedings of IEEE International Conference on Neural Networks, 1995: 1942-1948. [13] Kessel P, Glavitsch H. Estimating the voltage stability of a power system[J]. Power Delivery, IEEE Transactions on, 1986, 1(3): 346-354. [14] Della Cioppa A, De Stefano C, Marcelli A. On the role of population size and niche radius in fitness sharing[J]. IEEE Transactions on Evolutionary Computation, 2004, 8(6): 580-592.
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