Based on the general methods in power flow calculation of power system and on conceptions and classifications of parallel algorithm, a new approach named Dynamic Asynchronous Parallel Algorithm that applies to the onl...Based on the general methods in power flow calculation of power system and on conceptions and classifications of parallel algorithm, a new approach named Dynamic Asynchronous Parallel Algorithm that applies to the online analysis and real-time dispatching and controlling of large-scale power network was put forward in this paper. Its performances of high speed and dynamic following have been verified on IEEE-14 bus system.展开更多
The result of OPF whose task is to compute the voltage and angle of each node in power system is the basic of stability calculation and failure analysis in power system. For this goal, the idea of simulated annealing ...The result of OPF whose task is to compute the voltage and angle of each node in power system is the basic of stability calculation and failure analysis in power system. For this goal, the idea of simulated annealing method is introduced, mixed with the greedy randomized algorithm (GRASP), and then the hybrid SA algorithm is obtained. The algorithm is applied to the multi-objective optimal power flow calculation of power system, and the effectiveness of the algorithm given in this paper is verified by analysis of examples.展开更多
With the integration of distributed generation and the construction of cross-regional long-distance power grids, power systems become larger and more complex.They require faster computing speed and better scalability ...With the integration of distributed generation and the construction of cross-regional long-distance power grids, power systems become larger and more complex.They require faster computing speed and better scalability for power flow calculations to support unit dispatch.Based on the analysis of a variety of parallelization methods, this paper deploys the large-scale power flow calculation task on a cloud computing platform using resilient distributed datasets(RDDs).It optimizes a directed acyclic graph that is stored in the RDDs to solve the low performance problem of the MapReduce model.This paper constructs and simulates a power flow calculation on a large-scale power system based on standard IEEE test data.Experiments are conducted on Spark cluster which is deployed as a cloud computing platform.They show that the advantages of this method are not obvious at small scale, but the performance is superior to the stand-alone model and the MapReduce model for large-scale calculations.In addition, running time will be reduced when adding cluster nodes.Although not tested under practical conditions, this paper provides a new way of thinking about parallel power flow calculations in large-scale power systems.展开更多
The new reality of smart distribution systems with use of generation sources of small and medium sizes brings new challenges for the operation of these systems. The complexity and the large number of nodes requires us...The new reality of smart distribution systems with use of generation sources of small and medium sizes brings new challenges for the operation of these systems. The complexity and the large number of nodes requires use of methods which can reduce the processing time of algorithms such as power flow, allowing its use in real time. This paper presents a known methodology for calculating the power flow in three phases using backward/forward sweep method, and also considering other network elements such as voltage regulators, shunt capacitors and sources of dispersed generation of types PV （active power and voltage） and PQ （active and reactive power）. After that, new elements are introduced that allow the parallelization of this algorithm and an adequate distribution of work between the available processors. The algorithm was implemented using a multi-tiered architecture; the processing times were measured in many network configurations and compared with the same algorithm in the serial version.展开更多
随着电力系统的快速发展和复杂性日益增加,最优潮流(Optimal Power Flow,OPF)计算作为电力系统分析的关键环节,对于提高电网的运行效率和可靠性具有重要意义。文章提出了一种基于自适应人工蛙跳觅食算法的最优潮流计算方法,旨在解决传...随着电力系统的快速发展和复杂性日益增加,最优潮流(Optimal Power Flow,OPF)计算作为电力系统分析的关键环节,对于提高电网的运行效率和可靠性具有重要意义。文章提出了一种基于自适应人工蛙跳觅食算法的最优潮流计算方法,旨在解决传统最优潮流计算方法在处理大规模非线性问题时的不足。为了解决算法在处理复杂电力系统问题时存在收敛速度慢和易陷入局部最优的问题,文章引入自适应策略,通过动态调整算法参数,提高算法的全局搜索能力和收敛速度。仿真实验结果表明,所提出的方法在解的质量、收敛速度和算法稳定性方面均表现出显著的优势。展开更多
文摘Based on the general methods in power flow calculation of power system and on conceptions and classifications of parallel algorithm, a new approach named Dynamic Asynchronous Parallel Algorithm that applies to the online analysis and real-time dispatching and controlling of large-scale power network was put forward in this paper. Its performances of high speed and dynamic following have been verified on IEEE-14 bus system.
文摘The result of OPF whose task is to compute the voltage and angle of each node in power system is the basic of stability calculation and failure analysis in power system. For this goal, the idea of simulated annealing method is introduced, mixed with the greedy randomized algorithm (GRASP), and then the hybrid SA algorithm is obtained. The algorithm is applied to the multi-objective optimal power flow calculation of power system, and the effectiveness of the algorithm given in this paper is verified by analysis of examples.
基金supported by National Natural Science Foundation of China (No.51677072)
文摘With the integration of distributed generation and the construction of cross-regional long-distance power grids, power systems become larger and more complex.They require faster computing speed and better scalability for power flow calculations to support unit dispatch.Based on the analysis of a variety of parallelization methods, this paper deploys the large-scale power flow calculation task on a cloud computing platform using resilient distributed datasets(RDDs).It optimizes a directed acyclic graph that is stored in the RDDs to solve the low performance problem of the MapReduce model.This paper constructs and simulates a power flow calculation on a large-scale power system based on standard IEEE test data.Experiments are conducted on Spark cluster which is deployed as a cloud computing platform.They show that the advantages of this method are not obvious at small scale, but the performance is superior to the stand-alone model and the MapReduce model for large-scale calculations.In addition, running time will be reduced when adding cluster nodes.Although not tested under practical conditions, this paper provides a new way of thinking about parallel power flow calculations in large-scale power systems.
文摘The new reality of smart distribution systems with use of generation sources of small and medium sizes brings new challenges for the operation of these systems. The complexity and the large number of nodes requires use of methods which can reduce the processing time of algorithms such as power flow, allowing its use in real time. This paper presents a known methodology for calculating the power flow in three phases using backward/forward sweep method, and also considering other network elements such as voltage regulators, shunt capacitors and sources of dispersed generation of types PV （active power and voltage） and PQ （active and reactive power）. After that, new elements are introduced that allow the parallelization of this algorithm and an adequate distribution of work between the available processors. The algorithm was implemented using a multi-tiered architecture; the processing times were measured in many network configurations and compared with the same algorithm in the serial version.
文摘随着电力系统的快速发展和复杂性日益增加,最优潮流(Optimal Power Flow,OPF)计算作为电力系统分析的关键环节,对于提高电网的运行效率和可靠性具有重要意义。文章提出了一种基于自适应人工蛙跳觅食算法的最优潮流计算方法,旨在解决传统最优潮流计算方法在处理大规模非线性问题时的不足。为了解决算法在处理复杂电力系统问题时存在收敛速度慢和易陷入局部最优的问题,文章引入自适应策略,通过动态调整算法参数,提高算法的全局搜索能力和收敛速度。仿真实验结果表明,所提出的方法在解的质量、收敛速度和算法稳定性方面均表现出显著的优势。
