Optimization of micro-grid system using MOPSO

• Published in: Renewable energy Vol. 71; pp. 295 - 306
• Main Authors: Borhanazad, Hanieh, Mekhilef, Saad, Gounder Ganapathy, Velappa, Modiri-Delshad, Mostafa, Mirtaheri, Ali
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2014; Elsevier
• Subjects: algorithms; Applied sciences; batteries; climatic factors; cost effectiveness; developing countries; education; electricity; Energy; Equipments, installations and applications; Exact sciences and technology; generators (equipment); health services; Hybrid system; Iran; Multiobjective; Natural energy; Particle swarm optimization; Photovoltaic conversion; Renewable energy; renewable energy sources; solar collectors; Solar energy; Wind; wind speed; Iran; Multiobjective; Wind; Renewable energy; Particle swarm optimization; PV; Hybrid system; Electric energy transportation; Photovoltaic system; Optimization; Photovoltaic cell
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2014.05.006

Access to a reliable source of electricity is a basic need for any community as it can improve the living standards characterized via the improvement of healthcare, education, and the local economy at large. There are two key factors to consider when assessing the appropriateness of a micro-grid system, the cost-effectiveness of the system and the quality of service. The tradeoff between cost and reliability of the system is a major compromise in designing hybrid systems. In this way, optimization of a Hybrid Micro-Grid System (HMGS) is investigated. A hybrid wind/PV system with battery storage and diesel generator is used for this purpose. The power management algorithm is applied to the load, and the Multi-Objective Particle Swarm Optimization (MOPSO) method is used to find the best configuration of the system and for sizing the components. A set of recent hourly wind speed data from three meteorological stations in Iran, namely: Nahavand, Rafsanjan, and Khash, are selected and tested for the optimization of HMGS. Despite design complexity of the aforementioned systems, the results show that the MOPSO optimization model produces appropriate sizing of the components for each location. It is also suggested that the use of HMGS can be considered as a good alternative to promote electrification projects and enhance energy access within remote Iranian areas or other developing countries enjoying the same or similar climatic conditions. •Optimization of a hybrid wind/PV/battery/diesel micro-grid system is investigated.•Power management algorithm and particle swarm optimization method are applied.•Three stations in Iran are selected and tested.•The method can find the least-cost, most reliable configuration in HMGS.•It can be also used as a starting point for management of electrification projects.