A heuristic-based approach for optimizing a small independent solar and wind hybrid power scheme incorporating load forecasting

摘要

Small independent hybrid power schemes (IHPSs) are promising alternatives for load supply for remote areas. In IHPS optimization, load data are generally the main input. In this paper, forecasting strategies are proposed for load related parameters and tested on real data. Also, an efficient method based on the heuristic procedure (tabu search) is presented for optimization of an IHPS based on solar and wind energy along with a battery. The effect of using forecast load information instead of past information on the IHPS performance is investigated. In the optimization, there are three main decision variables: number of batteries, surface area of the PV system, and wind turbine swept area. The optimization is done to satisfy continually the load demand and to minimize the IHPS life cycle cost while respecting relevant limitations. To ensure the scheme's reliability, the probability of loss of power supply is determined. The performance of the proposed algorithm-based load forecasting approach is compared with the harmony search algorithm-based load forecasting and simulated annealing algorithm-based load forecasting. The simulation results clearly demonstrate the advantages of utilizing load forecasting in an IHPS optimization problem, and confirm that the tabu search method earnings more promising results than the harmony search and simulated annealing methods. (C) 2019 Elsevier Ltd. All rights reserved.