PRODUCTION AND MAINTENANCE OPTIMIZATION OF SOLAR ENERGY USING MACHINE LEARNING TECHNIQUES

Abstract

In this paper, an optimal integrated production - maintenance strategy for a solar power plant, is presented. An optimal maintenance cost model applied to solar power plant with the aim of simultaneously maximizing a plant reliability and minimizing a maintenance cost was developed. The maintenance strategy is a combined priority imperfect/selective maintenance strategy, which selects the priority components for maintenance in order to reduce maintenance downtime. The goal of the paper is to simultaneously determine the optimal energy production and maintenance plan, characterized by the quantity of energy stored and the losses incurred when the energy demand is unmet. The strategy is to minimize the expected total cost of energy production (generation, storage, and shortage) as well as maintenance over a limited time horizon. Thus, determining the energy production economic plan, and the optimal number of maintenances to be performed that yields maximum reliability associated with the cost. A numerical example was presented to validate the developed model using Sokoto solar power plant in Nigeria as the case study.

Keywords

• optimization
• support vector regression;
• artificial neural network
• maintenance;
• reliability