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Optimal Allocation of Renewable Energy Resources Considering Uncertainty in Load Demand and Generation

机译:考虑负荷需求和发电的不确定性,最佳分配可再生能源资源

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The uncertainty problems emerged due to the stochastic variations in power systems including the uncertainties of load and the output powers of renewable energy resources (wind and solar PV units). Thus, considering the uncertainties in power system planning is a challenge issue to diminish the risk of assigning the optimal siting and sizing of renewable energy resources (RER). This paper determines the optimal allocation of RER in the radial distribution network (RDN) considering the uncertainties of system. The optimal ratings and locations of the PV units and the wind-based DG are determined in 118-bus system for power loss minimization using new optimization technique called the lightning attachment procedure optimization (LAPO). Several scenarios are created using Monte-Carlo simulation to consider the uncertainties in the power system. The simulation results reveal that the optimal allocation of wind-based DG and PV units minimizes the power loss considerably. Moreover, the results verify the effectiveness of the proposed algorithm to solve the optimal allocation of wind and solar in terms of the objective function with considering the uncertainties.
机译:由于电力系统随机变化而出现的不确定性问题,包括负载不确定性和可再生能源资源(风和太阳能光伏单位)的输出功率。因此,考虑到电力系统规划的不确定性是一个挑战问题,以减少分配可再生能源资源(RER)的最佳选址和尺寸的风险。本文确定了考虑到系统不确定性的径向分布网络(RDN)中RER的最佳分配。光伏单元的最佳额定值和位置和基于风力的DG在118总线系统中确定了使用称为雷电连接过程优化(LAPO)的新优化技术的功率损耗最小化。使用Monte-Carlo仿真创建了几种情况,以考虑电力系统的不确定性。仿真结果表明,基于风力的DG和PV单元的最佳分配最大限度地减少了功率损耗。此外,结果验证了所提出的算法的有效性,以考虑不确定性,在客观函数方面解决风和太阳能的最佳分配。

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