Regional planning of solar photovoltaic technology based on LCA and multi-objective optimization

Abstract

Solar power is a crucial force in renewable energy. The production of solar photovoltaic (PV) has nonnegligible effects on the environment, and the economic properties of various PV technologies range. Life Cycle Assessment (LCA) and Multi-objective Optimization (MOO) methodologies were utilized in this research to establish an optimization model of PV technology regional planning that took into account combined environmental impacts and Electricity Supply Cost (ESC). Through NSGA-II genetic algorithm, the Pareto optimal solution with the minimum environmental pollution and the lowest economic cost in the whole life cycle of solar PV technology is obtained. The results demonstrated that toxic environmental impacts are the primary categories of crystalline silicon PV panels' potential environmental impacts, and monocrystalline silicon PV technology is the more advantageous choice when considering environmental impact and ESC. Results of sensitivity analysis indicated that uncertain factors would affect the scheme selection. This research offers a planning methodology for regional sustainable development of solar PV technology considering both environmental and economic objectives.