Abstract
Over the past few years, electricity demand has been on the rise. This has resulted in renewable energy resources being used rapidly, considering the shortage as well as the environmental impacts of fossil fuel. A renewable energy source that has become increasingly popular is photovoltaic (PV) energy as it is environmentally friendly. Installing PV modules, however, has to ensure harsh environments including temperature, dust, birds drop, hotspot, and storm. Thus, the phenomena of the non-uniform aging of PV modules has become unavoidable, negatively affecting the performance of PV plants, particularly during the middle and latter duration of their service life. The idea here is to decrease the capital of maintenance and operation costs involved in medium- and large-scale PV power plants and improving the power efficiency. Hence, the present paper generated an offline PV module reconfiguration strategy considering the non-uniform aging PV array to ensure that this effect is mitigated and does not need extra sensors. To enhance the economic benefit, the offline reconfiguration takes into account labor cost and electricity price. This paper proposes a gene evolution algorithm (GEA) for determining the highest economic benefit. The proposed algorithm was verified using MATLAB software-based modeling and simulations to investigate fourteen countries to maximize the economic benefit that employed a representative 18-kW and 43-kW output and the power of 10 × 10 PV arrays in connection as a testing benchmark and considered the electricity price and workforce cost. According to the results, enhanced power output can be generated from a non-uniformly aged PV array of any size, and offers the minimum swapping/replacing times to maximize the output power and improve the electric revenue by reducing the maintenance costs.
Highlights
IntroductionIn the last 10 years, the increased greenhouse gas emissions resulting from fossil fuels being excessively used and the requirement of saving these resources has led to the necessity of using renewable energy, solar energy using photovoltaic (PV)
In the last 10 years, the increased greenhouse gas emissions resulting from fossil fuels being excessively used and the requirement of saving these resources has led to the necessity of using renewable energy, solar energy using photovoltaic (PV) plants.PV modules tend to be located in an exacting outdoor environment and are damaged by various factors such as storms, wind, bird droppings, and hail, which leads to the modules becoming non-uniformly aged, adversely impacting their efficiency as well as the array’s overall efficiency [1]
In order to achieve quick calculation with low computing resources, this paper proposed a genetic-algorithm-supported reconfiguration for medium and large PV arrays exhibiting non-uniform aging
Summary
In the last 10 years, the increased greenhouse gas emissions resulting from fossil fuels being excessively used and the requirement of saving these resources has led to the necessity of using renewable energy, solar energy using photovoltaic (PV). Regarding power electronics, implementing high-performance switching devices such as super junction MOSFETs and silicon carbon and innovative converter topologies such as multilevel DC–DC as well as resonant DC–AC converters can enhance the efficiency of energy conversion [14,15]. The present paper proposes a reconfiguration strategy concerning aged PV systems to improve the maximum power generation by rearranging the positions of the PV modules while decreasing labor cost. This proposed reconfiguration strategy is based on the bucket effect concerning the maximum short-circuit current of PV strings and minimizing the swap times, for which it is important to introduce a PV system’s basic structure and working principles. The study of the mismatch due to non-uniform aging is illustrated
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