Parameter and Siting Optimization of Concentrated Solar Power - Parabolic Trough Distributed Generation Using Elitist Non-dominated Sorting Genetic Algorithm

As a unique approach to distributed generation (DG), concentrated solar power-parabolic trough (CSP-PT) technology utilizes solar energy to convert it into thermal energy, where the excess can be stored using thermal energy storage (TES) and dispatched during low insolation periods. However, the intricacy of selecting the appropriate values for the design parameters and location presents a challenge when integrating CSP-PT DG. Further, insufficient efforts were made in CSP DGs that consider both financial aspects and system improvements. Thus, this study utilized Non-dominated Sorting Genetic Algorithm (NSGA-II), a multi-objective evolutionary approach, in identifying optimal parameters and integration site for CSP-PT DG with and without TES in the IEEE 37-bus system, minimizing the levelized cost of energy (LCOE) and system losses. Precisely matching plant parameters and the location of the DG improves system performance and determines economic viability. Lower LCOE and fewer system losses are achieved in the system with TES at the expense of higher installed costs.