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Application of best first search algorithm to demand control

机译:最佳优先搜索算法在需求控制中的应用

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In the recent past, Zambia has faced a critical power deficit due to low water levels in the Kariba Dam, which is a main source of electricity. This problem has negatively affected the economy. One way to mitigate this problem is by diversifying to renewable solar energy. Though the government is making efforts to diversify, the current photovoltaic (PV) systems are not efficient in managing the energy produced. In this paper we propose a system that applies the Best First Search algorithm to demand control in PV systems. The proposed system is capable of finding the best combination of household appliances that optimizes user priorities and limits the power consumed from the grid. This goal is achieved by using heuristic search techniques that are used in Artificial Intelligence. The Best First Search algorithm with appropriate heuristic function is employed to determine the best combination of these household appliances. The application of the algorithm limits the demand below the generation capacity of the PV system and also limit grid dependence by consumers.
机译:在最近的过去,由于作为主要电力来源的卡里巴大坝水位低,赞比亚面临着严重的电力短缺。这个问题对经济产生了负面影响。缓解此问题的一种方法是通过多样化利用可再生太阳能。尽管政府正在努力实现多样化,但当前的光伏(PV)系统在管理产生的能源方面效率不高。在本文中,我们提出了一种将最佳优先搜索算法应用于光伏系统需求控制的系统。所提出的系统能够找到家用电器的最佳组合,从而优化用户优先级并限制电网的功耗。该目标是通过使用人工智能中使用的启发式搜索技术来实现的。采用具有适当启发式功能的Best First Search算法来确定这些家用电器的最佳组合。该算法的应用将需求限制在光伏系统的发电量以下,并且还限制了消费者对电网的依赖性。

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