Optimization of PV/Wind/Battery stand-alone system, using hybrid FPA/SA algorithm and CFD simulation, case study: Tehran

• Published in: Energy conversion and management Vol. 106; pp. 644 - 659
• Main Authors: Tahani, Mojtaba, Babayan, Narek, Pouyaei, Arman
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2015
• Subjects: Algorithms; batteries; Camber; case studies; CFD; Computational fluid dynamics; fluid mechanics; Hybrid algorithm; Hybrid system; Iran; LPSP; Mathematical models; Optimization; Panels; Photovoltaic cells; probability; Solar cells; solar collectors; solar energy; wind power; wind speed; wind turbines; ISW, Iran; Iran, Tehran; Iran; CFD; LPSP; Hybrid algorithm; Optimization; Hybrid system
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2015.10.011

•The utilization of an optimized Hybrid PV/Wind/Battery system has been studied.•The proposed system has been studied for a building in Tehran.•A novel hybrid optimization method, namely FPA/SA has been proposed.•The impact of inclined part of the roof on wind velocity is studied by CFD.•LPSP and Payback time were considered as objective functions in this study. Renewable energy hybrid systems are a promising technology toward sustainable and clean development. Due to stochastic behavior of renewable energy sources, optimization of their convertors has great importance for increasing system’s reliability and efficiency and also in order to decrease the costs. In this research study, it was aimed to study the utilization of an optimized hybrid PV/Wind/Battery system for a three story building, with an inclined surface on the edge of its roof, located in Tehran, capital of Iran. For this purpose, a new evolutionary based optimization technique, namely hybrid FPA/SA algorithm was developed, in order to maximize system’s reliability and minimize system’s costs. The new algorithm combines the approaches which are utilized in Flower Pollination Algorithm (FPA) and Simulated Annealing (SA) algorithm. The developed algorithm was validated using popular benchmark functions. Moreover the influence of PV panels tilt angle (which is equal to the slope of inclined part of the roof) is studied on the wind speed by using computational fluid dynamics (CFD) simulation. The outputs of CFD simulations are utilized as inputs for modeling wind turbine performance. The Loss of Power Supply Probability (LPSP) and Payback time are considered as objective functions, and PV panel tilt angle, number of PV panels and number of batteries are selected as decision variables. The results showed that if the tilt angle for PV panels is set equal to 30° and the number of PV panels is selected equal to 11 the fastest payback time which is 12years and two months and maximum cumulative savings with LPSP equal to 3.28% will occur.