Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

Eduardo Quiles, Carlos Roldán-Blay, Guillermo Escrivá-Escrivá and Carlos Roldán-Porta
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Eduardo Quiles: Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain
Carlos Roldán-Blay: Institute for Energy Engineering, Universitat Politècnica de València, 46022 Valencia, Spain
Guillermo Escrivá-Escrivá: Institute for Energy Engineering, Universitat Politècnica de València, 46022 Valencia, Spain
Carlos Roldán-Porta: Institute for Energy Engineering, Universitat Politècnica de València, 46022 Valencia, Spain

Sustainability, 2020, vol. 12, issue 3, 1-18

Abstract: In rural areas or in isolated communities in developing countries it is increasingly common to install micro-renewable sources, such as photovoltaic (PV) systems, by residential consumers without access to the utility distribution network. The reliability of the supply provided by these stand-alone generators is a key issue when designing the PV system. The proper system sizing for a minimum level of reliability avoids unacceptable continuity of supply (undersized system) and unnecessary costs (oversized system). This paper presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level. The proposed method is based on the application of a sequential random Monte Carlo simulation to the system model. Uncertainties of solar radiation, energy demand, and component failures are simultaneously considered. The results of the case study facilitate the sizing of the main energy elements (solar panels and battery) depending on the required level of reliability, taking into account the uncertainties that affect this type of facility. The analysis carried out demonstrates that deterministic designs of SAPV systems based on average demand and radiation values or the average number of consecutive cloudy days can lead to inadequate levels of continuity of supply.

Keywords: renewable energy; photovoltaic generation; battery storage; reliability evaluation; Monte Carlo Simulation (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 (2)

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