基于粒子群-内点混合优化算法的区域综合能源系统可靠性评估

Reliability Evaluation of Integrated Community Energy System Based on Particle-Swarm-Interior-Point Hybrid Optimization Algorithm

区域综合能源系统(integrated community energy system,ICES)的发展将电、气、热等能源联系得更加紧密。文章在能源集线器模型基础上,结合蒙特卡洛系统状态抽样方法,提出了一种基于粒子群-内点混合优化算法的区域综合能源系统可靠性评估算法。该算法通过结合粒子群算法和内点法的优劣势互补,可较准确计算目标区域综合能源系统可靠性量化指标。之后详细分析了可再生能源渗透率对区域综合能源系统可靠性的影响。

With the development of integrated community energy system（ ICES）,the relationship among electrical,gas and thermal systems is becoming tighter and tighter. Based on the energy hub model and sampling technique on system status using Monte Carlo simulation,this paper proposes the particle sw arm optimization（ PSO）-inner point algorithm to assess ICES＇s reliability. By applying the advantages of PSO and inner-point method,the proposed algorithm assesses ICES ＇s reliability with better accuracy. Moreover,this paper analyzes the impact of renew able energy penetration level on ICES ＇s reliability in detail.