Design of a solar concentrator system for a green community—A dual-objective stochastic optimization model

Abstract

The solar concentrator consisting of prisms is a promising solution for clean energy collection. Concentrator design and allocation play a key role for efficient solar energy collection. This study investigates a green community with many houses. A solar concentrator is installed on the roof of each house to receive sunlight. Several types of solar concentrators are delivered by a manufacturer who fabricates the solar concentrators to maximize its own profit while maintaining a level of collected energy that is acceptable to the community. A novel dual-objective model is proposed. Given uncertain energy demand, a trade-off between maximizing the manufacturer's profit and the community's energy collected is achieved when designing and allocating such a solar concentrator system. A revised genetic algorithm with chance constrained technique is proposed to seek the best resource portfolio and allocation plan for the solar concentrator system and the corresponding optimal layouts for individual solar concentrators. Pareto frontier analysis for the dual objectives is further given to highlight the proposed compromised solution. Experiments indicate that the proposed method significantly improves both energy collection efficiency and profits earned. The compromised solution is mutually accepted by the two parties. The impact of the variation of demand to profit is examined so that demand information can be quantified. This study contributes simultaneously to resolving the optimal resource portfolio and allocation of solar concentrators at a system level and to optimizing solar concentrator layout at the individual concentrator level.