电网检修计划优化编制方法研究及应用
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摘要
电力设备计划检修作为供电企业日常运行的重要工作,是提高设备健康水平、保证电网安全运行和持续可靠供电的一项必要措施。电网检修计划主要依靠人工编制完成,受专业技术能力、工作经验等人为因素影响较大,缺乏对检修经济效益和供电可靠性的考虑。目前关于电力系统检修计划编制的研究主要集中在机组检修计划优化上,对电网检修计划优化的理论研究和实际应用则处于初步阶段。因此,本文在借鉴机组检修计划优化理论研究的基础上,分析和总结了我国电网检修计划编制的一般流程及其特点,引入多目标优化理论求解电网检修计划优化,并对日前检修计划安全校核及检修计划优化编制系统研发进行了深入研究,取得了以下创新性成果：
从电网检修计划优化侧重的不同角度出发,分别提出了电网检修计划的实用化优化方法、多目标优化方法和交互式优化方法,兼顾了电网检修规划过程中的经济性和可靠性指标。其中,多目标检修计划优化方法以检修成本和期望缺供电量最小为目标,建立了电网检修计划多目标优化模型,并提出一种基于小生境的改进多目标粒子群算法对其进行求解。该算法采用小生境共享机制来更新粒子的位置,保持了解的多样性和分布的均匀性；引入混沌变异对部分非支配粒子进行小范围的扰动,提高了算法全局搜索能力,避免陷入局部最优。交互式检修计划优化方法将决策者的偏好引入到检修计划多目标优化模型中,以目标满意度和目标贴近度为基础构造交互式决策模型,将多目标优化模型分解为3个单目标决策模型进行交互求解,通过决策者对各单项目标满意度和目标总体贴近度的不断调整来体现其主观愿望,避免了人为确定目标权重的任意性,便于实际操作应用。
为了使算法更好地应用于电网检修计划优化问题,对模型求解过程中的约束条件处理和最优方案选取进行改进：采用惩罚函数法对不等式约束条件进行处理,让部分目标优良、违反约束的个体参与进化过程,提高算法寻优性能；采用模糊满意度评价对帕雷托最优解集进行最优折衷解选取,辅助决策者根据自身偏好选择最佳检修方案。
针对日前电网检修计划安全校核存在基态潮流精度不高、校核结果偏离实际等缺点,提出一种用于电网检修计划安全校核的基于多数据源的日前预报潮流自动生成方法。从实际电网计划调度运行的实际出发,分析了日前电网运行方式的构成,对调度计划、负荷预测和电网运行数据等多数据进行数据拟合形成日前电网预报潮流模型,采用联合动态潮流算法对有功平衡和无功电压平衡进行自动调整,提高了日前检修计划安全校核基准潮流的准确性和收敛性。
根据电网检修计划编制工作的实际流程,设计了可视化电网检修计划优化编制支持系统。系统的主要功能包括：根据本论文提出的实用化电网检修计划优化模型及其算法,自动生成优化的检修计划方案；根据本文提出的日前预报潮流自动生成方法,实现了基于多数据源的日前电网检修计划安全校核；采用图模一体化技术建立可视化检修计划仿真平台,可在电网接线图上进行检修计划编制和检修方式评估,以图形化的方式显示检修停电范围、检修停电规则知识,为用户提供智能化、可视化的检修计划编制工具。
As an important work in the day-to-day running of the power supply enterprise, planned maintenance of electrical equipment is a necessary measure to improve the health level of equipment, and ensure the safe operation of power grid and a continuous and reliable power supply. Maintenance scheduling of network is mainly completed by manually, and affected by the man-made factors such as professional and technical ability, working experience and so on greatly, and lack of consideration on the economic efficiency and reliability of power supply. At present, the research of power system maintenance scheduling mainly focuses on the unit maintenance scheduling, and the theoretical research and practical application of network maintenance scheduling are at a preliminary stage. Therefore, based on the theoretical study of the unit maintenance scheduling, this paper analysis and summarize the general process and characteristics of the compilation of network maintenance scheduling, and introduce the multi-objective optimization theory to solve network maintenance plan optimization, and study the day-ahead security correction and develop a system which carry out the maintenance scheduling planning optimization and compilation, the innovative achievements are as follow:
From the different point of view which grid maintenance scheduling optimization focus on, this paper proposes practical optimization method, multi-objective optimization method and interactive optimization method for maintenance scheduling, which can coordinate the economic and reliability objectives of maintenance scheduling optimization problem. The multi-objective optimization method of maintenance scheduling took the minimum maintenance cost and expected energy not supplied (EENS) as objective functions, and built a multi-objective optimization model for maintenance scheduling of transmission network and proposed an improved multi-objective particle swarm optimization algorithm based on niche technology for the built model, which used the niche sharing mechanism to update particle's position so as to keep the diversity of solution and the uniformity of distribution, and led in the chaotic mutation to part of non-dominated particles in order to enhance the global searching ability and avoid the local optimum. The interactive optimization method of maintenance scheduling introduced the preference of decision-makers into the multi-objective optimization model, and constructed an interactive decision-making model based on the satisfaction degree of objective and the nearness degree of objective, and decomposed the multi-objective optimization model into three single-objective decision-making models to solve the multi-objective optimization problem.
In order to make the algorithm apply to maintenance scheduling optimization problem better, the model constraints handling and optimal solution selected were improved. This paper processed the constraints by using a penalty function, and selected the best compromise solution from the Pareto optimal solution set according to fuzzy membership degree, and provided the scientific decision basis for maintenance plan makers.
The traditional method of security correction of power grid dispatching planning exists some problems such as rough calculations, larger error of the results and so on. Using day-head forecast power flow for security correction in power grid dispatching planning can solve these problems. This paper presents an auto-generated method of day-ahead forecast power flow based on multiple sources, which can generate the day-head forecast power flow automatically and improve the precision and accuracy of security correction work in power grid dispatching planning. Firstly, this method analysis the parameters constitute of normal operation mode of day-head power grid from the view of day-ahead forecast power flow calculation model. Secondly, it generate the parameters which used for day-head forecast power flow calculation automatically by getting data from multiple data sources and fitting these data, and set up the model of day-ahead forecast power flow calculation. Finally, it adjust the model of power flow according to the combined dynamic power flow algorithm, and generate the day-head forecast power flow which is converged automatically. The results of the security correction system in some an area power grid dispatching planning using this method verify its convergence and effectiveness.
According to the actual planning process of maintenance scheduling of Power network, this paper designs a visualization supporting system for power network maintenance scheduling optimization. The main function of the system include: firstly, generates an optimized maintenance scheme automatically according to the practical maintenance scheduling optimization algorithm presented in the paper; secondly, achieves the day-ahead security check of maintenance scheduling based on multiple data sources by the automatic generation method of forecast power flow presented in this paper; thirdly, builds the visual simulation platform of maintenance scheduling by the figure module integration technology, which can display the outage range and the rules knowledge of equipment maintenance, and provides the intelligent and visualization maintenance planning tools for the users.
从电网检修计划优化侧重的不同角度出发,分别提出了电网检修计划的实用化优化方法、多目标优化方法和交互式优化方法,兼顾了电网检修规划过程中的经济性和可靠性指标。其中,多目标检修计划优化方法以检修成本和期望缺供电量最小为目标,建立了电网检修计划多目标优化模型,并提出一种基于小生境的改进多目标粒子群算法对其进行求解。该算法采用小生境共享机制来更新粒子的位置,保持了解的多样性和分布的均匀性；引入混沌变异对部分非支配粒子进行小范围的扰动,提高了算法全局搜索能力,避免陷入局部最优。交互式检修计划优化方法将决策者的偏好引入到检修计划多目标优化模型中,以目标满意度和目标贴近度为基础构造交互式决策模型,将多目标优化模型分解为3个单目标决策模型进行交互求解,通过决策者对各单项目标满意度和目标总体贴近度的不断调整来体现其主观愿望,避免了人为确定目标权重的任意性,便于实际操作应用。
为了使算法更好地应用于电网检修计划优化问题,对模型求解过程中的约束条件处理和最优方案选取进行改进：采用惩罚函数法对不等式约束条件进行处理,让部分目标优良、违反约束的个体参与进化过程,提高算法寻优性能；采用模糊满意度评价对帕雷托最优解集进行最优折衷解选取,辅助决策者根据自身偏好选择最佳检修方案。
针对日前电网检修计划安全校核存在基态潮流精度不高、校核结果偏离实际等缺点,提出一种用于电网检修计划安全校核的基于多数据源的日前预报潮流自动生成方法。从实际电网计划调度运行的实际出发,分析了日前电网运行方式的构成,对调度计划、负荷预测和电网运行数据等多数据进行数据拟合形成日前电网预报潮流模型,采用联合动态潮流算法对有功平衡和无功电压平衡进行自动调整,提高了日前检修计划安全校核基准潮流的准确性和收敛性。
根据电网检修计划编制工作的实际流程,设计了可视化电网检修计划优化编制支持系统。系统的主要功能包括：根据本论文提出的实用化电网检修计划优化模型及其算法,自动生成优化的检修计划方案；根据本文提出的日前预报潮流自动生成方法,实现了基于多数据源的日前电网检修计划安全校核；采用图模一体化技术建立可视化检修计划仿真平台,可在电网接线图上进行检修计划编制和检修方式评估,以图形化的方式显示检修停电范围、检修停电规则知识,为用户提供智能化、可视化的检修计划编制工具。
As an important work in the day-to-day running of the power supply enterprise, planned maintenance of electrical equipment is a necessary measure to improve the health level of equipment, and ensure the safe operation of power grid and a continuous and reliable power supply. Maintenance scheduling of network is mainly completed by manually, and affected by the man-made factors such as professional and technical ability, working experience and so on greatly, and lack of consideration on the economic efficiency and reliability of power supply. At present, the research of power system maintenance scheduling mainly focuses on the unit maintenance scheduling, and the theoretical research and practical application of network maintenance scheduling are at a preliminary stage. Therefore, based on the theoretical study of the unit maintenance scheduling, this paper analysis and summarize the general process and characteristics of the compilation of network maintenance scheduling, and introduce the multi-objective optimization theory to solve network maintenance plan optimization, and study the day-ahead security correction and develop a system which carry out the maintenance scheduling planning optimization and compilation, the innovative achievements are as follow:
From the different point of view which grid maintenance scheduling optimization focus on, this paper proposes practical optimization method, multi-objective optimization method and interactive optimization method for maintenance scheduling, which can coordinate the economic and reliability objectives of maintenance scheduling optimization problem. The multi-objective optimization method of maintenance scheduling took the minimum maintenance cost and expected energy not supplied (EENS) as objective functions, and built a multi-objective optimization model for maintenance scheduling of transmission network and proposed an improved multi-objective particle swarm optimization algorithm based on niche technology for the built model, which used the niche sharing mechanism to update particle's position so as to keep the diversity of solution and the uniformity of distribution, and led in the chaotic mutation to part of non-dominated particles in order to enhance the global searching ability and avoid the local optimum. The interactive optimization method of maintenance scheduling introduced the preference of decision-makers into the multi-objective optimization model, and constructed an interactive decision-making model based on the satisfaction degree of objective and the nearness degree of objective, and decomposed the multi-objective optimization model into three single-objective decision-making models to solve the multi-objective optimization problem.
In order to make the algorithm apply to maintenance scheduling optimization problem better, the model constraints handling and optimal solution selected were improved. This paper processed the constraints by using a penalty function, and selected the best compromise solution from the Pareto optimal solution set according to fuzzy membership degree, and provided the scientific decision basis for maintenance plan makers.
The traditional method of security correction of power grid dispatching planning exists some problems such as rough calculations, larger error of the results and so on. Using day-head forecast power flow for security correction in power grid dispatching planning can solve these problems. This paper presents an auto-generated method of day-ahead forecast power flow based on multiple sources, which can generate the day-head forecast power flow automatically and improve the precision and accuracy of security correction work in power grid dispatching planning. Firstly, this method analysis the parameters constitute of normal operation mode of day-head power grid from the view of day-ahead forecast power flow calculation model. Secondly, it generate the parameters which used for day-head forecast power flow calculation automatically by getting data from multiple data sources and fitting these data, and set up the model of day-ahead forecast power flow calculation. Finally, it adjust the model of power flow according to the combined dynamic power flow algorithm, and generate the day-head forecast power flow which is converged automatically. The results of the security correction system in some an area power grid dispatching planning using this method verify its convergence and effectiveness.
According to the actual planning process of maintenance scheduling of Power network, this paper designs a visualization supporting system for power network maintenance scheduling optimization. The main function of the system include: firstly, generates an optimized maintenance scheme automatically according to the practical maintenance scheduling optimization algorithm presented in the paper; secondly, achieves the day-ahead security check of maintenance scheduling based on multiple data sources by the automatic generation method of forecast power flow presented in this paper; thirdly, builds the visual simulation platform of maintenance scheduling by the figure module integration technology, which can display the outage range and the rules knowledge of equipment maintenance, and provides the intelligent and visualization maintenance planning tools for the users.
引文
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