计及源荷随机性的交直流配电网电压多目标优化改进粒子群算法

Improved Particle Swarm Optimization Algorithm for Multi-objective Voltage Optimization of AC/DC Distribution Network Considering the Randomness of Source and Loads

含高比例波动性新能源和多类型随机性负荷的交直流配电网,受源荷不确定性的影响,其运行状态呈现较强的复杂性和多样性。为保证电网的安全稳定运行,本文以交直流配电网为对象,研究考虑源荷随机性的电压优化问题。首先,计及分布式电源和负荷的不确定性建立源荷概率分布模型,并基于拉丁超立方抽样和交替迭代法对交直流配电网进行随机潮流计算。然后,将混沌理论、人工免疫理论融合到杂交粒子群优化算法中,提出了一种免疫混沌杂交粒子群优化算法用于求解以节点电压偏差平均值的期望、电压损耗平均值的期望及网损的期望最小为目标的交直流配电网电压优化模型。最后,算例验证了所提方法能有效改善交直流配电网的电压水平和提高其应对源荷不确定性的能力。

The AC/DC distribution network with a high proportion of fluctuating new energy and multiple types of random loads is affected by the uncertainties in source and loads,and its operating state presents a strong complexity and diversity.To ensure the safe and stable operation of power grid,the AC/DC distribution network is taken as the object in this paper to study the voltage optimization problem considering the randomness of source and loads.First,considering the uncertainties in distributed generations and loads,a probability distribution model of source and loads is established,and the stochastic power flow calculations for the AC/DC distribution network are performed based on Latin hypercube sampling(LHS)and the alternate iteration method.Then,the chaos theory and artificial immune theory are merged into the hybrid particle swarm optimization(HPSO)algorithm,and an immune chaos hybrid particle swarm optimization(ICHPSO)algorithm is proposed to solve the voltage optimization model of AC/DC distribution network,which takes the minimal expected values of the average value of node voltage deviation,average voltage loss,and network loss as its objective.Finally,the results of an example verify that the proposed method can effectively improve the voltage level of the AC/DC distribution network and enhance its capability to cope with the uncertainties in source and loads.