A fully distributed microgrid system model is presented in this paper. In the user side, two types of load and plug-in electric vehicles are considered to schedule energy for more benefits. The charging and discharging states of the electric vehicles are represented by the zero-one variables with more flexibility. To solve the nonconvex optimization problem of the users, a novel neurodynamic algorithm which combines the neural network algorithm with the differential evolution algorithm is designed and its convergence speed is faster. A distributed algorithm with a new approach to deal with the inequality constraints is used to solve the convex optimization problem of the generators which can protect their privacy. Simulation results and comparative experiments show that the model and algorithms are effective.

中文翻译：

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考虑智能电网中新型组合神经动力学算法的用户和发电机优化能源调度的完全分布式方法

本文提出了一个完全分布式的微电网系统模型。在用户端，考虑负载和插电两种电动汽车，调度能源以获得更多收益。电动汽车的充放电状态用零一变量表示，更具灵活性。针对用户的非凸优化问题，设计了一种神经网络算法与差分进化算法相结合的新型神经动力学算法，其收敛速度更快。使用一种新的处理不等式约束的分布式算法来解决生成器的凸优化问题，可以保护他们的隐私。仿真结果和对比实验表明该模型和算法是有效的。