电力系统分布式多目标无功优化研究
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摘要
随着我国电力系统“西电东送,南北互供”大联网格局的逐步实现,以及特高压交直流电网和分布式发电技术的发展,电力系统规模不断扩大且日趋复杂,因而电力系统的各类计算正变得越来越繁琐,传统的计算分析方法受到挑战。无功优化作为保障电力系统安全经济运行的重要内容,属于计算复杂度非常高的非线性混合优化问题,其求解难度将因以上原因迅速增大,因而传统的集中式优化计算模式难以有效地满足大规模系统的无功优化需求。考虑到无功功率平衡的局部特性,可以通过电压无功分区方法将整个系统“软分区”成若干较小规模的分区,即将原有计算量较大的问题分解为若干计算量较小、且相互之间耦合度较低的子任务,然后通过相互协调得到整个问题的解决方案。在电力系统改革日益深化、电网结构日趋复杂的大环境下,这种“分而治之”的方法符合电力系统发展的趋势,对大规模电力系统的分析计算具有十分重要的现实意义。
在广泛阅读相关参考文献并分类评述的基础上,本文采用模糊聚类、模糊评价、多代理和智能搜索等理论和技术,紧密结合电力系统工程实际,围绕分布式多目标无功优化进行了系统深入的研究和探索,主要研究内容和创新性成果如下:
提出了一种基于改进模糊C均值聚类的无功电压分区方法。该方法为了计及无功优化时并联电容组/电抗器组的投切、变压器分接头档位的调节等离散控制变量的变化对系统中各节点电气量的影响,采用摄动分析方法逐一计算无功离散及连续控制变量摄动变化对各节点电压的响应。这种计算方法在每次摄动分析时都考虑了各无功控制变量的共同影响,克服了传统灵敏度计算的局限性,符合电压控制的准稳态过程。再依据归一化后的摄动响应值将网络中的各节点映射到无功变量空间,并与改进的节点关联矩阵相结合,得到了节点间的电气距离。所得电气距离既包含了电气信息,也包含了系统网络拓扑信息,可避免产生孤点等不合理的分区结果。然后利用改进模糊C均值聚类算法对系统进行无功电压分区,采用改进α分解算法或依据电网调度分区对系统分区数和聚类中心点进行初始化,为算法提供有效的初始参数,避免了随机初始化可能会陷入局部最优解的问题。聚类过程中,聚类有效性指标被用于评判聚类分区的效果,从而最终确定系统分区数。专家知识也被加入聚类计算,以进一步保证所得分区结果的合理性。通过这种模糊聚类方法对节点进行“软”聚类分区,更能客观地反映事物分类的不确定性,同时在一定程度上增大了求得聚类最优解的概率,可以取得更好的聚类效果。利用该方法对IEEE算例系统及实际电网进行仿真计算,验证了方法的可行性,并通过对结果进行比较,表明了该方法所得分区结果更加合理有效。
通过电力系统无功电压分区,可将大规模电网的无功优化问题分解为若干个小规模分区的优化子问题,降低了无功优化问题的复杂度。在无功电压分区的基础上,提出了一种多代理分布式多目标无功优化方法。考虑到不同拓扑结构的系统在进行无功优化时具有不同的特点,设计了两类代理对分区后不同结构的网络进行无功优化,分别为用于环型网络无功优化的环网代理和用于辐射型网络的辐射网代理。在进行无功优化时,两类代理可选用不同的潮流算法、优化数学模型、优化算法对所负责的分区进行无功优化计算。针对分布式多目标无功优化问题,建立隶属度函数,对各优化目标进行模糊评价,使得不同量纲的目标之间可以相互比较。避免了传统加权求和法中,因目标函数原始值不同而造成的影响。并将多目标问题解的模糊评价值映射成一个多维空间中不同的点,依据各个点与理想点之间欧氏距离的长短来衡量所得解的优劣。然后根据分解协调的思想,分布式无功优化时各代理在交互的信息量较少的情况下,通过Internet对各自边界节点的电气量进行交互,而分区内部数据互相不可观,从而保证了数据的完整性和密封性。整个优化过程中没有计算的简化和等值,也没有海量数据的传输,最终实现整个系统的全局一体化优化,制定出适用于整个电网的全局无功配置决策。另外,在开放式网格服务体系结构的基础上,围绕多代理分布式多目标无功优化方法设计了一种用于电力系统无功优化的网格计算构架,通过封装成网格服务的计算代理对所负责分区进行优化计算,为分布式资源的共享和异构问题提供了解决途径。通过对IEEE算例系统及实际电网进行仿真计算,验证了这种分布式多目标无功优化方法的可行性和有效性。所得优化结果表明,该方法可兼顾多个优化目标,在协调边界节点参数的同时,有效地降低网络损耗、提高节点电压合格率。
电力系统无功优化作为电网安全经济运行的重要内容,所求得的无功资源优化配置方案不仅要满足电网经济运行的要求,而且要满足系统对电压安全性的要求。无功资源配置不当会使得系统存在电压失稳事故隐患,因而有必要从增强系统电压稳定性的角度出发,对电力系统无功优化问题进行研究。为了在无功优化时考虑薄弱功率传输路径的电压稳定性,提出了一种计及电压稳定的多代理分布式无功优化方法。该方法先将局部电压稳定性指标经过模糊评价后作为多代理分布式无功优化问题的子目标进行优化,以提高分区中薄弱节点的稳定裕度。然后利用所得无功优化结果及薄弱节点信息,判别分区的最弱功率传输路径,并计算该路径的电压稳定性指标。将关键发电机无功储备指标的计算扩展为关键功率源点无功储备指标的计算,除了考虑关键发电机,还计及了虚拟功率源点的无功储备对负荷节点的影响。将各区所得电压稳定性指标与关键功率源点的无功储备指标相结合,转化为空间坐标后,利用四区图对系统的电压稳定性进行评估,最终得到所需的无功优化方案。通过对IEEE算例系统的基本运行方式和重负荷运行方式的仿真计算,所得结果表明该方法在对无功资源进行优化配置时,考虑了各分区内薄弱节点及薄弱功率传输路径对系统电压稳定性的影响,所得优化方案能保证系统的电压稳定裕度,可避免由于无功优化策略不当造成的电压失稳事故隐患。
With the expansion of power networks and the development of UHV AC/DC power grid and distributed generation technology, various calculations of power systems are becoming more and more complex. Thus, many traditional calculation methodes need to be improved for the development situation. As an important calculation for the safety and economic operation of power systems, reactive power optimization is a mixed nonlinear optimization problem with a large number of variables and constrains. Because of the above results, it is becoming more and more difficult to get a satisfying global solution for a large-scale power system using centralized optimization approaches. Considering reactive power needs to be compensated locally, a large-scale power system can be divided into several small-scale subsystems in network partition. Therefore the whole optimization problem is decomposed into several low-dimension and low-coupling subproblems for corresponding subsystems. Then the optimization problem is solved coordinatively in distributed computing. It is of great significance that the computing mode conforms to the development of power systems.
Introducing the theory and methods of fuzzy clustering, fuzzy evaluation, multi-agent system and intelligent optimization, distributed multi-objective reacitive power optimization is researched systematically in the dissertation. The main contributions of the dissertation are shown as follows.
A new network partition approach based on the improved fuzzy C means clustering algorithm is presented herein. In order to take into account the perturbation impact of discrete variables on nodes' parameters, such as transformer tap-changers and capacitor banks, a perturbation approach is adopted to get the voltage response of nodes to the perturbation of various discrete and continuous variables. The approach takes into account the combined effect of reactive power variables in perturbation analysis, which overcomes disadvantages of traditional sensitivity approaches. The nodes in power networks are mapped to the space of var variables according to the normalized perturbation values, and a new electrical distance is worked out associated with an improved incidence matrix. Therefore the electrical distance combines network topology information with the voltage response of nodes, which can avoid the unreasonable partition results. And then an improved fuzzy C means clustering algorithm is used for network partition, in which the clustering parameters are initialized according to a improved a decomposition algorithm or dispatching areas. The effective initial parameters can avoid trapping into local optimal solution of clustering problems. In the clustering process, a clustering validity index is defined to evaluate the clustering results and confirm the final result of network partition. And expert knowledge is also introduced into the clustering algorithm for the reasonableness of partition results. The fuzzy clustering algorithm is a "flexible" method for nerwork partition, which can reflect more objectively the uncertainty of the classification and increase the probability of getting the global optimal solution of network partition. The simulations verify that the reasonable and effective results can be obtained using the proposed partition method.
By the above method of network partition, a reactive power optimization problem can be decomposed into several subproblems of small-scale systems, which can reduce the complexity of var optimization problem significantly. A distributed multi-objective reactive power optimization method based on the multi-agent technology is presented in the dissertation. Considering the characteristics of reactive power optimization in different network structures, two kinds of agents are developed according to network structures: loop agent for loop network and radial agent for radial network. The characteristics of two kinds of agents for reactive power optimization are presented respectively in power flow algorithm, objective function and optimization algorithm. Membership functions for the distributed multi-objective optimization problem are constructed to evaluate objectives, so that the objectives with different units can be compared. Evaluation values of multi-objective optimization problem are regarded as coordinate values of points in a multidimensional space, and the Euclidean distances between the points and the ideal point are used to evaluate optimization solutions. According to the decomposition and coordination theory, agents transmit the parameters of boundary nodes each other via Internet in the process of distributed var optimization. Due to the unobservability of internal data among subsystems, the integrity and sealing of data is ensured. In addition, a grid-computing architecture for distributed multi-objective reactive power optimization is designed based on open grid service architecture. Grid computing technology can solve the data-sharing problem of distributed resources and integrate the heterogeneous computational resources. The optimization subproblems for corresponding subsystems can be worked out autonomously by agents, which are wrapped into grid services. The simulation results, greatly reduced power losses and improved voltage profiles as well as coordinated the parameters of boundary nodes, show that the method is feasible and effective.
The solutions of reactive power optimization not only meet the requirement of power system economic operation, but also meet the requirement of voltage security. The improper allocation of reactive power resources will have hidden dangers of voltage instability accidents in power systems, thus it is necessary to research the reactive power optimization considering voltage stability. For considering voltage stability of power transmission paths in power systems, a new distributed reactive power optimization considering voltage stability method is introduced in the dissertation. The local voltage stability index as the optimization objective is used to improve the stability margin of weak nodes after fuzzy evaluation. Then according to optimization results and weak nodes, the voltage stability indeces of weak paths are computed and the weakest power transmission path is searched. The reactive power reserve index of key power sources is developed from the key generators reactive power reserve index, including virtual power sources as well as key generators. The two kinds of indeces are incorporated as coordinate values in a four-zone diagram, which is used to evaluate the solutions of reactive power optimization. Weak nodes and weak paths of voltage stability in subsystems are considered in the proposed method of reactive power optimization. The results of IEEE 30-bus system in the base and heavy load conditions show that the method can ensure the voltage stability margin of power systems and avoid accidents of voltage instability due to the improper allocation of reactive power resoures.
在广泛阅读相关参考文献并分类评述的基础上,本文采用模糊聚类、模糊评价、多代理和智能搜索等理论和技术,紧密结合电力系统工程实际,围绕分布式多目标无功优化进行了系统深入的研究和探索,主要研究内容和创新性成果如下:
提出了一种基于改进模糊C均值聚类的无功电压分区方法。该方法为了计及无功优化时并联电容组/电抗器组的投切、变压器分接头档位的调节等离散控制变量的变化对系统中各节点电气量的影响,采用摄动分析方法逐一计算无功离散及连续控制变量摄动变化对各节点电压的响应。这种计算方法在每次摄动分析时都考虑了各无功控制变量的共同影响,克服了传统灵敏度计算的局限性,符合电压控制的准稳态过程。再依据归一化后的摄动响应值将网络中的各节点映射到无功变量空间,并与改进的节点关联矩阵相结合,得到了节点间的电气距离。所得电气距离既包含了电气信息,也包含了系统网络拓扑信息,可避免产生孤点等不合理的分区结果。然后利用改进模糊C均值聚类算法对系统进行无功电压分区,采用改进α分解算法或依据电网调度分区对系统分区数和聚类中心点进行初始化,为算法提供有效的初始参数,避免了随机初始化可能会陷入局部最优解的问题。聚类过程中,聚类有效性指标被用于评判聚类分区的效果,从而最终确定系统分区数。专家知识也被加入聚类计算,以进一步保证所得分区结果的合理性。通过这种模糊聚类方法对节点进行“软”聚类分区,更能客观地反映事物分类的不确定性,同时在一定程度上增大了求得聚类最优解的概率,可以取得更好的聚类效果。利用该方法对IEEE算例系统及实际电网进行仿真计算,验证了方法的可行性,并通过对结果进行比较,表明了该方法所得分区结果更加合理有效。
通过电力系统无功电压分区,可将大规模电网的无功优化问题分解为若干个小规模分区的优化子问题,降低了无功优化问题的复杂度。在无功电压分区的基础上,提出了一种多代理分布式多目标无功优化方法。考虑到不同拓扑结构的系统在进行无功优化时具有不同的特点,设计了两类代理对分区后不同结构的网络进行无功优化,分别为用于环型网络无功优化的环网代理和用于辐射型网络的辐射网代理。在进行无功优化时,两类代理可选用不同的潮流算法、优化数学模型、优化算法对所负责的分区进行无功优化计算。针对分布式多目标无功优化问题,建立隶属度函数,对各优化目标进行模糊评价,使得不同量纲的目标之间可以相互比较。避免了传统加权求和法中,因目标函数原始值不同而造成的影响。并将多目标问题解的模糊评价值映射成一个多维空间中不同的点,依据各个点与理想点之间欧氏距离的长短来衡量所得解的优劣。然后根据分解协调的思想,分布式无功优化时各代理在交互的信息量较少的情况下,通过Internet对各自边界节点的电气量进行交互,而分区内部数据互相不可观,从而保证了数据的完整性和密封性。整个优化过程中没有计算的简化和等值,也没有海量数据的传输,最终实现整个系统的全局一体化优化,制定出适用于整个电网的全局无功配置决策。另外,在开放式网格服务体系结构的基础上,围绕多代理分布式多目标无功优化方法设计了一种用于电力系统无功优化的网格计算构架,通过封装成网格服务的计算代理对所负责分区进行优化计算,为分布式资源的共享和异构问题提供了解决途径。通过对IEEE算例系统及实际电网进行仿真计算,验证了这种分布式多目标无功优化方法的可行性和有效性。所得优化结果表明,该方法可兼顾多个优化目标,在协调边界节点参数的同时,有效地降低网络损耗、提高节点电压合格率。
电力系统无功优化作为电网安全经济运行的重要内容,所求得的无功资源优化配置方案不仅要满足电网经济运行的要求,而且要满足系统对电压安全性的要求。无功资源配置不当会使得系统存在电压失稳事故隐患,因而有必要从增强系统电压稳定性的角度出发,对电力系统无功优化问题进行研究。为了在无功优化时考虑薄弱功率传输路径的电压稳定性,提出了一种计及电压稳定的多代理分布式无功优化方法。该方法先将局部电压稳定性指标经过模糊评价后作为多代理分布式无功优化问题的子目标进行优化,以提高分区中薄弱节点的稳定裕度。然后利用所得无功优化结果及薄弱节点信息,判别分区的最弱功率传输路径,并计算该路径的电压稳定性指标。将关键发电机无功储备指标的计算扩展为关键功率源点无功储备指标的计算,除了考虑关键发电机,还计及了虚拟功率源点的无功储备对负荷节点的影响。将各区所得电压稳定性指标与关键功率源点的无功储备指标相结合,转化为空间坐标后,利用四区图对系统的电压稳定性进行评估,最终得到所需的无功优化方案。通过对IEEE算例系统的基本运行方式和重负荷运行方式的仿真计算,所得结果表明该方法在对无功资源进行优化配置时,考虑了各分区内薄弱节点及薄弱功率传输路径对系统电压稳定性的影响,所得优化方案能保证系统的电压稳定裕度,可避免由于无功优化策略不当造成的电压失稳事故隐患。
With the expansion of power networks and the development of UHV AC/DC power grid and distributed generation technology, various calculations of power systems are becoming more and more complex. Thus, many traditional calculation methodes need to be improved for the development situation. As an important calculation for the safety and economic operation of power systems, reactive power optimization is a mixed nonlinear optimization problem with a large number of variables and constrains. Because of the above results, it is becoming more and more difficult to get a satisfying global solution for a large-scale power system using centralized optimization approaches. Considering reactive power needs to be compensated locally, a large-scale power system can be divided into several small-scale subsystems in network partition. Therefore the whole optimization problem is decomposed into several low-dimension and low-coupling subproblems for corresponding subsystems. Then the optimization problem is solved coordinatively in distributed computing. It is of great significance that the computing mode conforms to the development of power systems.
Introducing the theory and methods of fuzzy clustering, fuzzy evaluation, multi-agent system and intelligent optimization, distributed multi-objective reacitive power optimization is researched systematically in the dissertation. The main contributions of the dissertation are shown as follows.
A new network partition approach based on the improved fuzzy C means clustering algorithm is presented herein. In order to take into account the perturbation impact of discrete variables on nodes' parameters, such as transformer tap-changers and capacitor banks, a perturbation approach is adopted to get the voltage response of nodes to the perturbation of various discrete and continuous variables. The approach takes into account the combined effect of reactive power variables in perturbation analysis, which overcomes disadvantages of traditional sensitivity approaches. The nodes in power networks are mapped to the space of var variables according to the normalized perturbation values, and a new electrical distance is worked out associated with an improved incidence matrix. Therefore the electrical distance combines network topology information with the voltage response of nodes, which can avoid the unreasonable partition results. And then an improved fuzzy C means clustering algorithm is used for network partition, in which the clustering parameters are initialized according to a improved a decomposition algorithm or dispatching areas. The effective initial parameters can avoid trapping into local optimal solution of clustering problems. In the clustering process, a clustering validity index is defined to evaluate the clustering results and confirm the final result of network partition. And expert knowledge is also introduced into the clustering algorithm for the reasonableness of partition results. The fuzzy clustering algorithm is a "flexible" method for nerwork partition, which can reflect more objectively the uncertainty of the classification and increase the probability of getting the global optimal solution of network partition. The simulations verify that the reasonable and effective results can be obtained using the proposed partition method.
By the above method of network partition, a reactive power optimization problem can be decomposed into several subproblems of small-scale systems, which can reduce the complexity of var optimization problem significantly. A distributed multi-objective reactive power optimization method based on the multi-agent technology is presented in the dissertation. Considering the characteristics of reactive power optimization in different network structures, two kinds of agents are developed according to network structures: loop agent for loop network and radial agent for radial network. The characteristics of two kinds of agents for reactive power optimization are presented respectively in power flow algorithm, objective function and optimization algorithm. Membership functions for the distributed multi-objective optimization problem are constructed to evaluate objectives, so that the objectives with different units can be compared. Evaluation values of multi-objective optimization problem are regarded as coordinate values of points in a multidimensional space, and the Euclidean distances between the points and the ideal point are used to evaluate optimization solutions. According to the decomposition and coordination theory, agents transmit the parameters of boundary nodes each other via Internet in the process of distributed var optimization. Due to the unobservability of internal data among subsystems, the integrity and sealing of data is ensured. In addition, a grid-computing architecture for distributed multi-objective reactive power optimization is designed based on open grid service architecture. Grid computing technology can solve the data-sharing problem of distributed resources and integrate the heterogeneous computational resources. The optimization subproblems for corresponding subsystems can be worked out autonomously by agents, which are wrapped into grid services. The simulation results, greatly reduced power losses and improved voltage profiles as well as coordinated the parameters of boundary nodes, show that the method is feasible and effective.
The solutions of reactive power optimization not only meet the requirement of power system economic operation, but also meet the requirement of voltage security. The improper allocation of reactive power resources will have hidden dangers of voltage instability accidents in power systems, thus it is necessary to research the reactive power optimization considering voltage stability. For considering voltage stability of power transmission paths in power systems, a new distributed reactive power optimization considering voltage stability method is introduced in the dissertation. The local voltage stability index as the optimization objective is used to improve the stability margin of weak nodes after fuzzy evaluation. Then according to optimization results and weak nodes, the voltage stability indeces of weak paths are computed and the weakest power transmission path is searched. The reactive power reserve index of key power sources is developed from the key generators reactive power reserve index, including virtual power sources as well as key generators. The two kinds of indeces are incorporated as coordinate values in a four-zone diagram, which is used to evaluate the solutions of reactive power optimization. Weak nodes and weak paths of voltage stability in subsystems are considered in the proposed method of reactive power optimization. The results of IEEE 30-bus system in the base and heavy load conditions show that the method can ensure the voltage stability margin of power systems and avoid accidents of voltage instability due to the improper allocation of reactive power resoures.
引文
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