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Optimal schedule of dispatchable DG in electrical distribution systems with extended dynamic programming

机译:具有扩展动态规划的配电系统中可调度DG的最佳计划

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In this paper, the optimal schedule of dispatchable distributed generation (DG) units connected to radial electrical distribution systems (EDS) is solved using an extended dynamic programming approach. The objective of the optimal DG scheduling problem is to determine the hour-by-hour active generation output of each dispatchable DG unit, in order to minimize the total active power losses of the EDS and the generation costs. The proposed extended dynamic programming (EDP) is an advantageous approach because convexity is not required to obtain a global optimal solution, and the “curse of dimensionality” is not a concern since the computational complexity of the algorithm grows linearly with the size of the network. Besides, the state variables have only two dimensions, one to represent the active power flows and the other to represent the nodal voltages. A 56-nodes MV distribution system with two dispatchable DG units is used to evaluate the performance of the proposed EDP approach, considering a deterministic and a stochastic case. A set of Monte Carlo simulations is used to analyze the influence of uncertainties. Results confirm that the proposed methodology is a suitable approach to unveil the best operation schedule for dispatchable DG units.
机译:在本文中,使用扩展的动态规划方法求解了连接到径向配电系统(EDS)的可调度分布式发电(DG)单元的最佳调度。最佳DG调度问题的目的是确定每个可调度DG单元的每小时有功发电输出,以使EDS的总有功功率损耗和发电成本最小化。提议的扩展动态规划(EDP)是一种有利的方法,因为不需要凸度即可获得全局最优解,并且“维数诅咒”也无需关注,因为算法的计算复杂度随网络的大小线性增长。此外,状态变量只有两个维度,一个代表有功潮流,另一个代表节点电压。考虑到确定性和随机情况,使用具有两个可调度DG单元的56节点MV分发系统来评估所提出的EDP方法的性能。一组蒙特卡洛模拟用于分析不确定性的影响。结果证实,所提出的方法是揭示可调度DG机组最佳运行时间表的合适方法。

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