Multi-objective optimization of hybrid PTC+PV system using genetic algorithm

Renewable energy, especially PV systems, has experienced a significant growth in its rate of deployment as an alternative for conventional power sources. However, a larger penetration of PV systems is restricted to the availability of technological options for storage. The integration of thermal energy storage to CSP systems is straightforward, through technologies already available in the market. Hence, the hybridization of CSP and PV systems has the potential for reducing operational and installation costs, as well as significantly increase the capacity factor. The present study describes a methodology for design and sizing of such hybrid plants, by implementing a transient simulation model, coupled to an evolutionary optimization algorithm, allowing to address the tradeoff between costs and capacity factor.