基于多能互动的主动配电网多时空尺度能量优化调度研究

As the advanced stage of Smart Grid in power distribution, active distribution network technology will be an important way to solve the large scale application problems of distributed energy resources represented by electric vehicles in the future, but it also brings huge challenge to the energy optimal dispatch of current distribution network with unidirectional, passive, static and centralized characteristics. This project starts from the load characteristics and interaction mechanism of different energy forms in the time-space domain, presents a new bidirectional power modeling approach of electric vehicles based on Markov probability methods and Non-cooperative game theory, and constructs the quantitative index system of low-carbon, economy and security objectives. Then, based on the hierarchical modeling methods such as fuzzy chance constrained programming, model rolling prediction and intelligent feeder control, the novel multiple temporal and spatial scales coordinated energy dispatching model for active distribution network is proposed ultimately with the abilities of overall global optimization, regional short-term autonomy and local real-time response. While, on the basis of spatial mapping relationship between objective and decision variables of evolutionary algorithms based decomposition, this project also proposes the dynamic weight vector adjustment strategy, resource allocation method with variable neighborhood size and dynamic processing mechanism of strongly coupled uncertain constraints to solve the uniform distribution problem of Pareto optimal solutions for complex dispatching models. The research results are expected to offer technical support for the development of active distribution network, and also provide the decision-making basis and quantitative analysis tool for power dispatch department.

作为智能电网在配电领域发展高级阶段的主动配电网技术，将是未来解决以电动汽车为代表的分布式能源规模化接入问题的重要手段，但这也给现有单向、被动、静态、集中的配电网能量优化调度带来了巨大挑战。本项目拟从时空范畴内不同能源形式的负荷特性及互动机制出发，提出基于马尔可夫概率模型和非合作博弈理论的电动汽车双向功率建模方法，进而构建多目标低碳、经济、安全等量化指标体系，并基于模糊机会约束规划、模型滚动预测、智能馈线控制等层次化建模方法，提出新型的整体全局优化、区域短时自治、局部实时响应的主动配电网多时空尺度协同能量调度模型；然后利用分解进化算法目标变量和决策变量的空间映射关系，提出有效的动态权重调整策略、变邻域限制的资源分配策略及强耦合不确定约束的动态处理机制，以解决复杂调度模型Pareto最优解集的均匀分布问题。项目成果有望为主动配电网的发展提供技术支撑，也能为调度部门提供决策依据和定量分析工具。

积极探索新形势下清洁、高效、安全的新型调度模式及调度方法，深刻揭示“源-网-荷”多能互动的内在联系和协同机理，是未来主动配电网等系统作为智能电网区域能量中心实践与应用的重要步骤和关键问题。本项目对含多种能源形式的主动配电网系统多时空尺度能量调度问题展开研究，项目执行顺利，完成了既定内容，主要包括：1）在电动汽车等多能负荷特性建模及互动机制方面，针对风、光、车等不确定性资源的功率特性，提出了风电的机会约束规划随机描述方法、光伏的神经网络预测方法，以及电动汽车的V2G充放电模型、资源互动模型、随机概率出行模型、博弈配置策略等；2）在“源-网-荷”多时空尺度协同调度方面，建立了“环境-经济-安全”调度评价指标体系、“区域自治-实时响应”多级调度机制、整体-局部层次化调度框架、充电站博弈规划策略、鲁棒协同规划方法、多重电网博弈模型等；3）在新型智能算法优化调度方法方面，提出了复杂调度模型的分解-进化调度求解算法及约束处理机制、改进的非支配排序差分进化算法、自组织物种形成粒子群算法、转移密度估计策略强度帕累托进化算法，以及考虑供需互动因素的MOEA/D资源调整策略等；4）研发了区域电网能量管理系统，形成了新一代柔性新能源系统理论分析与实践应用规划体系，突破了时空协同柔性资源调度关键技术难点，实现了多元利益主体复杂互动行为的协同增效以及柔性新能源系统的动态最优化运行。围绕以上研究成果，共发表学术论文23篇，其中SCI检索9篇，EI检索期刊论文5篇，EI检索会议2篇；授权国家发明专利7项，获批软件著作权9项；项目负责人主持获河南省科学技术进步二等奖1项、三等奖1项，中国商业联合会科技进步一等奖1项，河南省高校科技成果一等奖2项，出版学术著作1部；获校优秀硕士论文1篇，联合培养博士1名，硕士13名，超额完成了预期目标。