Optimizing regional energy systems with concentrated solar power for enhanced efficiency, sustainability, and cost-effective energy management

The current study optimizes a regional integrated energy system that combines concentrated solar power, wind turbines, energy storage, and thermal components to enhance energy efficiency, reduce costs, and minimize environmental impact. The primary objectives were to reduce operational expenses, address environmental concerns, and ensure a reliable electricity supply through integrated load response mechanisms. Fuzzy probability-constrained programming was used to model the uncertainty of renewable energy output, and a modified gravitational search algorithm (MGSA) was employed for optimization. Two different approaches to energy demand response were studied: one using electric boilers with a fixed thermoelectric power ratio, and another employing a flexible system for cooling, heating, and power that could adjust as needed. The implementation of the load response program resulted in a 0.75 % increase in the electrical peak-valley difference and a 0.51 % increase in the thermal peak-valley difference, indicating slight shifts in demand distribution. Additionally, valley values decreased by 0.37 % for electrical loads and by 2.71 % for thermal loads, suggesting modest improvements in off-peak load utilization. These changes demonstrate the program's potential to reshape load profiles; however, significant peak reduction will require further enhancement.