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Optimal Dispatch of Electric Vehicles and Wind Power Using Enhanced Particle Swarm Optimization

机译：基于增强粒子群算法的电动汽车和风能优化调度

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In this paper, an economic dispatch model, which can take into account the uncertainties of plug-in electric vehicles (PEVs) and wind generators, is developed. A simulation based approach is first employed to study the probability distributions of the charge/discharge behaviors of PEVs. The probability distribution of wind power is also derived based on the assumption that the wind speed follows the Rayleigh distribution. The mathematical expectations of the generation costs of wind power and V2G (vehicle to grid) power are then derived analytically. An optimization algorithm is developed based on the well-established particle swarm optimization (PSO) and interior point method to solve the economic dispatch model. The proposed approach is demonstrated by the IEEE 118-bus test system.
机译：本文开发了一种经济调度模型，该模型可以考虑插电式电动汽车（PEV）和风力发电机的不确定性。首先采用基于仿真的方法来研究PEV充电/放电行为的概率分布。风能的概率分布还基于风速遵循瑞利分布的假设得出。然后，通过分析得出对风力发电和V2G（车辆到电网）发电成本的数学期望。基于完善的粒子群算法（PSO）和内点法，开发了一种优化算法来求解经济调度模型。 IEEE 118总线测试系统演示了该方法。

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