Multi-objective optimal sizing of grid connected photovoltaic batteryless system minimizing the total life cycle cost and the grid energy. (April 2020)

• Record Type: Journal Article
• Authors: Ndwali, Kasereka; Njiri, Jackson G.; Wanjiru, Evan M.
• Is Part Of: Renewable energy. Volume 148(2020)
• Page Start: 1256
• Page End: 1265
• Publication Date: 2020-04
• Subjects: Islanding mode -- Levelized cost of energy -- Loss of power supply probability -- Mixed integer linear programming -- Stand-alone; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2019.10.065
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: The increasing demand of electricity has led to drastic use of renewable energy resources because of the scarcity and environmental effects of fossil fuel. Photovoltaic energy is one of renewable energy sources that emerges exponentially due to its environmentally friendly, operating and maintenance free, among other benefits. However, the main drawback of photovoltaic energy is its unreliability due to unpredictable nature of solar. Thus, this paper tackles a novel optimization technique based on multi-objective sizing of grid connected photovoltaic without energy storage systems. The objective aims at minimizing the total life cycle cost (TLCC) and energy purchased from utility grid while maximizing the reliability. In this study, the microgrid system reliability is expressed by the loss of power supply probability (LPSP). Mixed integer linear programming has been used to determine the decision variables which are the optimal number of photovoltaic panels and the hourly powers from utility grid. A case study has been done based on daily power demand of Engineering workshops at Jomo Kenyatta University of Agriculture and Technology (JKUAT). From the results obtained, the optimal number is 354 photovoltaic arrays, 0.6022 kWh is purchased from the grid from 7:00 h to 18:00 h, and the total life cycle cost of the project is found to be 191630$. The daily potential energy saving is up to 64.16%. Highlights: Mixed integer linear programming is used to determine the decision variables. The optimal number of photovoltaic panels is 354. The total life cycle cost is 191630 $ and daytime grid energy is 0.622 kWh. The daily potential energy saving is up to 64.16%.