M Yazdanpanah Jahromi - Master of Science, University of Sistan and Baluchestan
S Farahat - Associate Professor, University of Sistan and Baluchestan
S. M Barakati - Assistant Professor, University of Sistan and Baluchestan;

The coordinating between generation periods of renewable resources and consumption periods is very complicated issue in stand-alone hybrid power systems. The optimal sizing method which can maximize the electricity match rate between demand and supplies is an important task. Most literatures sized hybrid renewable systems based on reliability and cost. They ignored the electricity match rate. In this paper, a triple multi-objective design of stand-alone hybrid power systems has been done by considering all match criteria. These criteria are Inequality Coefficient (IC), total cost throughout the useful life of the installation and Correlation Coefficient (CC). The optimization procedure minimizes IC and cost, and also maximizes CC, simultaneously. Six types of wind turbine (WT) and also six types of PV modules, with different output powers and costs are considered for this optimization procedure. For this task, the multi-bjective particle swarm optimization algorithm (MOPSO) which is one of the multi-objective evolutionary algorithm (MOEA), have been used in order to find the best combination of components of hybrid power systems. As an example of application, a hybrid power system has been assumed. A set of possible solutions (Pareto set) for each configuration is obtained. The designers can select the best configuration among the Pareto set which fits their desire. The results achieved for this proposed method, demonstrate the practical utility of this procedure.

modeling of hybrid systems, multi-objective optimization, sizing method, electricity match rate