园区综合能源系统多时间尺度优化  

Multi-timescales optimization of park-level integrated energy system

作　　者：林锦弘 奚圣羽 李梦诗[1] 吴青华[1] LIN Jinhong;XI Shengyu;LI Mengshi;WU Qinghua(School of Electric Power Engineering,South China University of Technology,Guangzhou 510641,China)

机构地区：[1]华南理工大学电力学院,广东广州510641

出　　处：《现代电子技术》2023年第22期137-143,共7页Modern Electronics Technique

基　　金：广州市科技项目(202201010752);广东省重点领域研发项目计划(2022A1515011608)。

摘　　要：园区综合能源系统(PIES)是生产、传输、储存和消耗过程中耦合多种能源的一体化能源系统,能够提高一次能源利用率,具有节能、环保、高能效的显著优势,是早日实现“碳达峰、碳中和”目标的重要途径。基于此,文中建立一种基于需求侧响应的园区综合能源系统的多时间尺度分层优化模型,考虑负荷与可再生能源的不确定性,采用蒙特卡洛方法处理不确定性优化问题。通过引入自适应参数设置和改进群体搜索算法(GSO)的领头者搜索策略,提高GSO算法的性能,使其能适用于PIES的大规模非凸的非线性优化问题。算例结果表明:改进的GSO算法能够提高搜索效率并有效避免陷入局部最优解,具有良好的全局求解性能;在不确定性情况下,采用蒙特卡洛方法,基于综合能源需求侧响应技术的多时间尺度优化可以有效降低PIES成本,降低系统能源损耗,且所提优化策略具有一定的随机性抵抗能力。The park integrated energy system(PIES)is an integrated energy system that couples multiple energy sources during the production,transmission,storage,and consumption processes.It can improve the utilization rate of primary energy and has significant advantages in energy conservation,environmental protection,and high energy efficiency.It is an important way to achieve the goal of"carbon peaking and carbon neutrality"as soon as possible.On this basis,a PIES multi-timescales and hierarchical optimization model based on demand side response technology is proposed considering load and renewable energy uncertainties,and the Monte Carlo method is used to deal with the uncertainty optimization problem.By introducing adaptive parameter settings and improving the producers search strategy of the group search optimizer(GSO)algorithm,the performance of the GSO is improved to reslove the large-scale non-convex nonlinear optimization problems of PIES.The example results show that the improved GSO algorithm can improve the search efficiency,can effectively avoid falling into the local optimal solution,and has good global solution performance.In the case of uncertainty,by means of the Monte Carlo method,multi-time scale optimization based on integrated energy demand side response technology can effectively reduce the cost of PIES and reduce system energy loss,and the proposed optimization strategy has a certain uncertainty resistance ability.

关 键 词：园区综合能源系统 多时间尺度 运行优化 改进群体搜索算法 需求侧响应 蒙特卡洛方法 不确定性优化 

分 类 号：TN919-34[电子电信—通信与信息系统] TM73[电子电信—信息与通信工程]