基于改进遗传算法的园区综合能源系统规划研究

Research on multi-objective optimal allocation of park integrated energy system based on improved genetic algorithm

中文关键词: 改进遗传算法  综合能源系统  能源规划  多目标优化

英文关键词: improved genetic algorithm  integrated energy system  energy planning  multi-objective optimization

中文摘要:

      通过能源综合化建设来实现终端能源的高效化，成为当前支撑碳中和碳达峰的重要途径之一。针对园区能源系统能效提升、规划配置等问题，提出了园区综合能源系统经济-能效多目标优化规划模型。分析园区综合能源系统的基本结构，以年总成本、综合能效为优化目标，并考虑能源规划投资和能源运行安全的各类约束，建立了园区综合能源系统多目标优化规划模型；然后，基于NSGA-II算法和融合模拟退火算法的特点，融合模拟退火算法的搜索机制改进NSGA-II的求解性能；最后，以我国某园区为例验证模型和算法的有效性。

英文摘要:

      The comprehensive construction of energy to realize the high efficiency of terminal energy has become one of the important ways to support carbon neutralization and carbon peak. Aiming at the problems of energy efficiency improvement,planning and allocation of energy system in the park,a multi-objective optimal allocation model of economy and energy efficiency of comprehensive energy system in the park is put forward. By analyzing the basic structure of the park’s comprehensive energy system,taking the total annual cost and comprehensive energy efficiency as the optimization objectives,and considering various constraints of energy planning investment and energy operation safety,a multi-objective optimal allocation model of comprehensive energy system in the park is established. Then,based on the characteristics of NSGA-II algorithm and fusion simulated annealing algorithm,the search mechanism of fusion simulated annealing algorithm improves the solution performance of NSGA-II. Finally,a park in China is taken as an example to verify the effectiveness of the model and algorithm.