A Case Study of Grid-Connected Solar Farm Control Using Artificial Intelligence Genetic Algorithm to Accommodate Peak Demand

Abstract

The continuous rise in peak electricity demands is now considered to be one of the most prominent power generation problems. The need to increase generation capacity caused by peak demand growth is a critical economic issue due to the financial burdens associated with increasing capacity. Jordan is a good example of the problems caused by growing peak demand. As a small, aid-dependent country already suffering from financial and environmental issues, the number of Syrians seeking refuge in Jordan has created a strain on the country’s energy resources. This study examines the effect of installing a Photovoltaic (PV) solar farm at the Amman East Power Plant in order to offer a solution to the continuous growth in peak demand. As part of the research reported here, three mathematical representative models have been created and tested using real solar radiation, energy generation, and peak demand data. These results then were used to build a model based on an artificial intelligence Genetic Algorithm (GA) that could be used in predicting, analysing and calculating the best solar farm size in order to keep the generation curve as flat as possible with the least cost. Subsequently, an iterative simulation of the processes has been done to test the model different chromosomes: the optimum configuration of the model ensures that the annualized cost of the system (ACS) is minimized, while the peak demand is lessened as much as possible.