基于粒子群优化算法的电网GIC-Q多目标优化策略

地磁感应电流(GIC)流经变压器绕组会产生直流偏磁现象,造成变压器无功损耗增加,破坏电网无功平衡,影响电网安全稳定运行。为了有效地抑制GIC对电网的不良影响,以无功补偿设备成本和电压偏移量最小为目标,提出一种基于粒子群优化算法的多目标无功优化策略,保证地磁场扰动下电网无功平衡。所提策略利用小生境共享机制不断更新粒子位置,并依据拥挤距离排序对Pareto最优解进行存档,保持解的多样性和均匀性;引入混沌变异避免陷入局部最优解,同时提高全局搜索能力。GIC标准算例的仿真结果验证了所提策略的准确性和有效性。

Multi-objective optimization strategy based on PSO algorithm for GIC-Q of power grid

GIC(Geomagnetically Induced Current) may cause the DC magnetic bias when it flows through the transformer windings, resulting in the increase of transformer reactive-power loss, the imbalance of grid reactive-power and the impact on safe and stable grid operation. A multi-objective reactive-power optimization strategy based on the particle swarm optimization algorithm is proposed to restrain the influence of GIC and ensure the reactive-power balance of power grid under geomagnetic disturbance, which takes the minimum cost of reactive-power compensation equipments and the minimum voltage deviation as its objectives. The proposed strategy applies the niche sharing mechanism to update the particle locations and archives the Pareto optimal solution set according to the crowding distance for the diversity and uniformity of solutions. Chaotic mutation is introduced to avoid the locally optimal solutions and to improve the global searching ability. Simulative results of GIC-benchmark verify the accuracy and effectiveness of the proposed strategy.