【作者】 田建伟；

【导师】 胡兆光； 吴俊勇；

【作者基本信息】 北京交通大学 ， 电气工程， 2012， 博士

【摘要】 摘要：近年来,为了应对资源和环境对电力系统发展提出的严峻挑战,电网智能化成为全球电网发展的必然趋势。随着能源结构的优化调整和清洁能源如风能、太阳能的快速发展、用户与电网之间的互动交互、新型市场参与方的出现,电力市场运营更加复杂,给输电网规划提出了新的要求,输电网规划面临更大的复杂性和不确定性。我国能源资源与需求逆向分布,需要依托智能电网技术进行大范围的资源优化配置,因此合理的智能输电网规划成为迫切需要研究的重大课题。面对新形势、新问题,本文从理论研究和工程应用出发,研究了综合的智能方法体系智能工程理论。从宏观政策、电网-用户互操作性、输电网扩展规划等不确定性方面探讨适用于智能输电网规划不确定性问题建模的方法学,主要研究工作如下：理论研究方面针对智能电网机制下输电网规划所面临的模糊随机、随机模糊等双重不确定性问题,对智能工程理论框架和方法体系进行发展和扩充。通过定义智能工程机会路径、交叉子空间、αβ-机会解等,扩充了智能工程优化理论并定义了协调优化算子、协同进化算子、目标冲突协调算子等,证明了相关定理,为应用智能工程理论进行智能输电网规划不确定性问题建模奠定了理论基础。智能电网建设是一项复杂巨系统工程,涉及国家政策、电力系统运行、不确定发电、不确定用电、实时电价等复杂性、不确定性问题。我国计划在2020年基本建成坚强智能电网,电网的资源配置能力、安全水平、运行效率以及电网与电厂、用户的互动水平显著提高。理论应用层面从协调智能电网各参与方利益入手,对智能输电网规划不确定性问题建模方法进行研究,抽取复杂的智能输电网规划不确定性问题如宏观政策模拟子问题、电网-用户互操作模拟子问题、电厂-电网-用户三方输电网协调规划子问题等三个子问题进行研究。针对三个子问题,本文应用智能工程理论分别对其进行理论研究与建模应用。运用智能工程混合模型、交互式协调机制对不确定性子问题进行建模,并在IEEE-39新英格兰节点测试系统和IEEE-30节点测试系统上模拟仿真,验证了智能工程方法学及智能工程混合协调模型解决不确定性问题的有效性。更多还原

【Abstract】 ABSTRACT:In order to deal with the formidable challenges that resource and environment impact on power system’s development, Smart Grid has become an inevitable trend on grid development around the world. With the optimization and revision in energy resource structure, rapid development of clean energies such as wind power and solar power, two-way communication between consumer and grid, emergence of new market participators, the electricity market operation becomes more and more complex, and it also raises new requirements to transmission planning, thus transmission planning is confronted with greater complexities and uncertainties.Energy resource is reversely distributed with energy demand in China, so smart grid technologies are indispensable for optimal resource allocation on wide area level, and reasonable smart transmission planning turns into an urgent and key task for research. Facing new situations and new issues, starting from theoretical research and engineering application, intensive researches on integrative intelligent methodology Intelligent Engineering (IE) are presented in this study. Applicable uncertainty problem’s modeling in smart transmission planning methodology is explored from some uncertain perspectives, which consist of macroeconomic policy simulation, grid-consumer interoperability, transmission expansion planning, and so on. The main works are shown as follows:On theoretical research level, in view of dual uncertainties such as fuzzy random, random fuzzy emerge under smart grid mechanism, the theoretical framework and methodology of IE are pushed forward and expanded. IE chance path, sub-overlap space, αβ-chance solution are defined, IE optimization theory is expanded and coordinated optimization operator, co-evolution operator and objective-conflict coordination operator are created, and related theorems are proved. All above mentioned lay a solid foundation for uncertainty problems’modeling in smart transmission planning.Smart Grid’s development is a complex giant system engineering, which involves complex and uncertain issues such as national policy, power system operation, uncertain generation, uncertain consumption, real time price, and so on. Strong&Smart Grid plan would be basically completed by2020in China, and by then resource allocation capacities, grid security and operation efficiency, interaction among generation, grid and consumer would be significantly enhanced. On theoretical application level, the methodology system of uncertainty problems of smart transmission planning is explored. The complicated uncertainty problems of smart transmission planning problem are divided into three And-subproblems i.e. macro policy simulation subproblem, grid-consumer interoperability simulation subproblem and generation-grid-consumer coordination planning subproblem for study.For the three And-subproblems, IE is partially employed for theoretical research and modeling practice in this study. IE hybrid model and interactive coordination are implemented to make uncertainty subproblem modeling, and simulations on IEEE-39bus test system and IEEE-30bus test system demonstrate the validity of IE methodology and coordinated IE hybrid model on solving uncertain problem.更多还原