Self-operation and low-carbon scheduling optimization of solar thermal power plants with thermal storage systems

Abstract

Photo thermal power generation, as a renewable energy technology, has broad development prospects. However, the operation and scheduling of photo thermal power plants rarely consider their internal structure and energy flow characteristics. Therefore, this study explains the structure of a solar thermal power plant with a thermal storage system and analyzes its main energy flow modes to establish a self-operation and low-carbon scheduling optimization model for the solar thermal power plant. The simulation results of the example showed that for the self-operating model oriented towards power generation planning and peak valley electricity prices, the existence of a thermal storage system could improve the power generation capacity and revenue of the photovoltaic power plant. For example, when the capacity of the thermal storage system was greater than 6 h, the penalty for insufficient power generation in the simulation result was 0 $, and the maximum increase in revenue reached 84.9% as the capacity of the thermal storage system increased. In addition, when the capacity of the thermal storage system increased from 0 to 8 h, the comprehensive operating cost decreased from 1635.2 k $ to 1224.6 k $, and the carbon emissions decreased from 26.4 × 103 ton to 22.1 × 103 ton. Compared with the existing literature, this study provides a more comprehensive and systematic solution through detailed energy flow analysis and optimization model. The research has practical and far-reaching significance for promoting the development of clean energy technology, improving the sustainable utilization of renewable energy, and optimizing the overall performance of the energy system.