Sizing and implementing off-grid stand-alone photovoltaic/battery systems based on multi-objective optimization and techno-economic (MADE) analysis. (15th September 2020)

• Record Type: Journal Article
• Authors: Ridha, Hussein Mohammed; Gomes, Chandima; Hazim, Hashim; Ahmadipour, Masoud
• Is Part Of: Energy. Volume 207(2020)
• Publication Date: 2020-09-15
• Subjects: Off-grid SAPV system -- Multi-objective optimization -- Differential evolution -- Storage battery -- LLP -- LCC; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118163
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Sun energy is widely utilized to power stand-alone photovoltaic systems (SAPV). However, the lack of long term hourly meteorological data and inaccurate methods result in obstacles in designing the SAPV system. Therefore, an optimal sizing methodology is necessary to guarantee satisfactory performance. In this study, a new mutation adaptive differential evolution (MADE) based on a multi-objective optimization algorithm is presented to optimize the configuration of the off-grid SAPV system. Three conflict objectives are normalized, weighted, and then aggregated by mono-objective function to optimally size the off-grid stand-alone PV system. The performance of the proposed SAPV system is analyzed based on three types of batteries which are lead-acid, AGM, and lithium-ion. The results show that the optimal configuration based on lead-acid has less fitness function ( f ), life cycle cost (LCC), levelized cost of energy (LCE), with a high level of loss of load probability (LLP), and their values are 0.0268, 54, 896 USD, 1.58USD, and 0.19%, respectively. Moreover, the optimal numbers of the PV modules (in series and parallel) and lead-acid battery are 9, 28, and 42, respectively. Therefore, the SAPV system based on lead-acid battery can be very suitable for real-world applications. Highlights: MADE method is presented for optimally size of the SAPV system. An efficient mutation vector with using 2-Opt approach is proposed. Dynamically adapting F and C R are proposed to boost the convergence rate. MOO design of SAPV system through reliability and cost assessments. The SAPV system's performance is analyzed based on three types of batteries.