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Optimal power flow with renewable energy resources including storage

机译:具有可再生能源资源的最佳功率流,包括存储

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The incorporation of renewable energy resources (RERs) into electrical grid is very challenging problem due to their intermittent nature. This paper solves an optimal power flow (OPF) considering wind-solar-storage hybrid generation system. The primary components of the hybrid power system include conventional thermal generators, wind farms and solar photovoltaic modules with batteries. The main critical problem in operating the wind farm or solar PV plant is that these RERs cannot be scheduled in the same manner as conventional generators, because they involve climate factors such as wind velocity and solar irradiation. This paper proposes a new strategy for the optimal power flow problem taking into account the impact of uncertainties in wind, solar PV and load forecasts. The simulation results for IEEE 30 bus system with genetic algorithm (GA) and two-point estimate method have been obtained to test the effectiveness of the proposed optimal power flow strategy. Results for a sample system with GA and two-point estimate OPF, and GA and Monte Carlo simulation have been obtained to ascertain effectiveness of the proposed method.
机译:由于他们间歇性的性质,将可再生能源资源(RERS)纳入电网是非常具有挑战性的问题。本文解决了考虑风 - 太阳能储存混合生成系统的最佳电流(OPF)。混合动力系统的主要组件包括具有电池的传统热发电机,风电场和太阳能光伏模块。操作风电场或太阳能光伏电厂的主要关键问题是,这些RER不能以与传统发电机相同的方式调度,因为它们涉及气候因素,如风速和太阳照射。本文提出了一种新的策略,以考虑到风,太阳能光伏和负荷预测的不确定性的影响。已经获得了具有遗传算法(GA)和两点估计方法的IEEE 30总线系统的仿真结果,以测试所提出的最佳功率流策略的有效性。已经获得了具有GA和两点估计OPF的样本系统的结果,并且已经获得了GA和Monte Carlo模拟以确定所提出的方法的有效性。

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