Multiobjective Optimization of a Residential Grid-Tied Solar System

Warren S. Vaz
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Warren S. Vaz: Department of Engineering Technology, University of Wisconsin-Oshkosh, Fox Cities Campus, Menasha, WI 54952, USA

Sustainability, 2020, vol. 12, issue 20, 1-15

Abstract: Residential customers are increasingly turning to solar energy as they are becoming more climate-conscious and solar energy is becoming more cost-effective. However, customers are often faced with myriad choices from retailers. The current retail landscape features several solar panel sizes, battery storage sizes, and technologies, and all of them come in a range of prices. The present study aims to present a strategy to optimize the choice for the customer taking two conflicting objectives into account: minimizing the cost and minimizing the carbon footprint. By presenting multiple nondominated (optimal) solutions based on the individual’s unique parameters, customers can make the optimal choice. Two disparate locations are examined: New York City, NY, USA and Phoenix, AZ, USA. Several variations are examined, including no battery storage, battery storage, and charging of an electric vehicle. The strategy was found to suitably highlight a variety of options that gave the best tradeoff between carbon emissions and cost. Metrics to compare nondominated fronts showed that a variable season charging time for the electric vehicle produced fronts that dominated a fixed season strategy by 6%. This strategy can be easily implemented by customers to avoid choosing improperly sized and priced residential solar systems.

Keywords: solar photovoltaic; battery storage; residential electrical load; genetic algorithm; multiobjective optimization; solar generation data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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