Locating Distributed Generations (DGs) Using the Combined Genetic and Optimal Power Flow (GA-OPF) Algorithm with Decreasing Operating Costs and Increasing Network Reliability

Today, most of the electricity needed by countries is generated by using fossil fuels. Due to the fact that fossil fuels are non-renewable and have harmful environmental effects, the use of renewable energy sources is inevitable. In many studies, the random behavior of load and renewable energies, which leads to a disproportion in demand and consumption, is not considered. This article presents a model for simultaneously determining the location and capacity of programmable and renewable DGs, electric energy storage units, and a strategy for operating the set. The objectives of the problem include reducing the costs of construction and operation to provide reliable and quality electricity to the customers. Other goals include improving reliability and voltage profile, reducing losses, reducing the cost of purchasing electrical energy from the upstream network, and reducing the production of environmental pollutants. Various constraints including load distribution equations, capacity constraints of lines and substations, and constraints related to distributed generation units and storage generators are considered. Furthermore, the combined algorithm of genetics and optimal power flow (GA-OPF) has been used for optimization. To more accurately calculate the operating costs and also to locate and determine the optimal utilization strategy of DG resources, it is necessary to consider the load changes at different hours of the day and on different days of the year. The efficiency of the presented model is evaluated and analyzed for different scenarios using the combined genetic algorithm and GA-OPF optimal power flow for optimization. Simulation results indicate that by simultaneously using controllable and renewable DG units and electrical energy storage, as well as determining the optimal strategy of using the proposed set, it is feasible to plan the development of the distribution system by the lowest possible cost to respond to the growth of the load with the proper quality and the desired reliability.