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A cluster-autonomous partitioning algorithm in electrical power grid using Monte Carlo simulation
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作者 chengchao lu Zhongjie Wang 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2018年第1期1-16,共16页
Power grid partitioning decomposes a large power grid into several clusters.Most of the existing partitioning methods suffer from a limitation that the buses within a cluster are severely topologically disconnected af... Power grid partitioning decomposes a large power grid into several clusters.Most of the existing partitioning methods suffer from a limitation that the buses within a cluster are severely topologically disconnected after partitioning in some cases.As a result,a cluster will inevitably be assigned to two or more power grid corporations.This assignment obstructs inner-cluster monitoring and control applications of the transmission system.To overcome the limitation,this paper proposes a multi-index power grid partitioning approach using Monte Carlo simulation guaranteeing cluster connectivity to ensure the cluster autonomy.A line-based binary coding technique is developed to ensure the cluster connectivity.Three partitioning indices are considered:the coherency,the cluster connectivity,and the number of clusters.Finally,the proposed partitioning method is applied to IEEE 9-bus system,IEEE 39-bus system and IEEE 145-bus system and compared with Fuzzy C-medoid(FCMdd)algorithm. 展开更多
关键词 AUTONOMY COHERENCY CONNECTIVITY dynamic data power grid partitioning Monte Carlo
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Pseudo-derivative evolutionary algorithm and convergence analysis
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作者 Yang Yu Zhongjie Wang +1 位作者 Huaglory Tianfield chengchao lu 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2018年第5期92-107,共16页
In this paper,a novel evolutionary algorithm(EA),called pseudo-derivative EA(called PDEA),is proposed.The basic idea of PDEA is to use pseudo-derivative,which is obtained based on the information produced during the e... In this paper,a novel evolutionary algorithm(EA),called pseudo-derivative EA(called PDEA),is proposed.The basic idea of PDEA is to use pseudo-derivative,which is obtained based on the information produced during the evolution,and to help search the solution of optimization problem.The pseudo-derivative drives the search process in a more informed direction.That makes PDEA different from the random optimization methods.The convergence of PDEA is first analyzed based on systems theory.The convergence condition of PDEA is then derived though this condition is too strong to be satisfied.Next,this condition is relaxed based on the entropy theory.Finally,performances of PDEA are evaluated on the benchmark functions and an adaptive liquid level control system of a surge tank.The numeric simulation results show that PDEA is capable of finding the solutions to the optimization problems with good accuracy,reliability,and speed. 展开更多
关键词 Evolutionary algorithm convergence analysis entropy theory pseudoderivative.
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