Application of best first search algorithm to demand control

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.