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The Source-Load-storage Coordination and Optimal Dispatch from the High Proportion of Distributed Photovoltaic Connected to Power Grids

Maolin Li,Youwen Tian, Haonan Zhang,Nannan Zhang

Journal of Engineering Research(2023)

Shenyang Agr Univ

Cited 0|Views12
Abstract
With the rapid development of distributed PV, many distributed PV devices are connected to the power grid, which is essential to optimize the scheduling in the power grid containing a high proportion of distributed PV. In this paper, a new day-ahead optimal dispatching model of a power system combined with the high proportion of photovoltaic is established. The impact of time-of-use tariffs on customers and the regulation of electricity by energy storage plants are considered in the model. The main contribution of this paper is that providing a better solution for grids with a high proportion of distributed photovoltaic, reducing carbon emissions and improving photovoltaic consumption. A solution approach i.e., Wild horse optimizer (WHO) is employed to optimal dispatch. The results show that compared with the Particle swarm algorithm, using the Wild horse optimizer has saved 16% costs, reduced 28% in thermal power carbon emissions, and increased 24% in distributed PV utilization rates. Wild horse optimizer is a better optimal approach which can reduce distributed PV abandonment rates and decrease costs when applied to the optimal scheduling in the grid with high percentage of distributed photovoltaic.
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Key words
High percentage of distributed PV,Wild horse optimizer,Low-carbon,Optimal dispatch,Distributed PV utilization rates
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要点】:本文建立了一种新的结合高比例分布式光伏的电力系统日优化调度模型,考虑了分时电价对客户的影响以及储能电站的电力调节,为高比例分布式光伏电网提供了更优解决方案,降低了碳排放和提高了光伏消耗。

方法】:采用了一种名为野马优化器(WHO)的解决方案来进行优化调度。

实验】:实验结果表明,与粒子群算法相比,使用野马优化器可以节省16%的成本,减少28%的热力发电碳排放,并增加24%的分布式光伏利用率。当应用于高比例分布式光伏电网的优化调度时,野马优化器是一种更好的优化方法,可以降低分布式光伏弃光率并减少成本。