The Experts below are selected from a list of 51741 Experts worldwide ranked by ideXlab platform
Jiaxin Ning - One of the best experts on this subject based on the ideXlab platform.
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Optimal Allocation of Dynamic Var Sources Using the Voronoi Diagram Method Integrating Linear Programing
IEEE Transactions on Power Systems, 2017Co-Authors: Weihong Huang, Kai Sun, Jiaxin NingAbstract:Dynamic reactive power (var) sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues. This paper optimizes the sizes of dynamic var sources at given locations against FIDVR issues under severe contingencies. First, the geometric characteristics about the non-convex solution Space of this problem are studied. Accordingly, a Voronoi diagram approach integrating linear programming (LP) is proposed, which disperses a number of sample points of potential solutions in the Searching Space to construct a Voronoi diagram blending the local cost functions over the entire Space by Barycentric interpolation in Voronoi regions. New sample points are then recursively added, including the tentative optimal point using LP, the most depopulated area point ensuring global fidelity, and the connecting point, until the stopping criterion is met. The new approach is demonstrated in detail on the WSCC 9-bus system. A case study on the NPCC 140-bus system also validates that the proposed approach can effectively estimate the boundary and the geometry of the feasible solution region in the Searching Space and find the optimal solution.
Li Xiang-fei - One of the best experts on this subject based on the ideXlab platform.
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Improving Mutative Scale Chaos Optimization Algorithm and Simulation Study
Computer Simulation, 2006Co-Authors: Li Xiang-feiAbstract:In order to avoid blind and repeated Searching of chaos optimization in Searching Space and improve Searching efficiency, an improving mutative scale chaos optimization algorithm was proposed. A couple of cycles are set, chaos search in the inner cycle and the range is reduced in the outer cycle. The algorithm counts better value for every Searching and sets a sign A in the chaos Searching, when the numbers of better value searched is equal to A, the Searching Space is dynamic reduced according scale, and the above course is repeated in the lesser scale till global optimal value is found. The simulation results show that algorithm is simple and local Searching ability is better, the efficiency is higher than that of mutative scale chaos optimization.
Weihong Huang - One of the best experts on this subject based on the ideXlab platform.
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Optimal Allocation of Dynamic Var Sources Using the Voronoi Diagram Method Integrating Linear Programing
IEEE Transactions on Power Systems, 2017Co-Authors: Weihong Huang, Kai Sun, Jiaxin NingAbstract:Dynamic reactive power (var) sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues. This paper optimizes the sizes of dynamic var sources at given locations against FIDVR issues under severe contingencies. First, the geometric characteristics about the non-convex solution Space of this problem are studied. Accordingly, a Voronoi diagram approach integrating linear programming (LP) is proposed, which disperses a number of sample points of potential solutions in the Searching Space to construct a Voronoi diagram blending the local cost functions over the entire Space by Barycentric interpolation in Voronoi regions. New sample points are then recursively added, including the tentative optimal point using LP, the most depopulated area point ensuring global fidelity, and the connecting point, until the stopping criterion is met. The new approach is demonstrated in detail on the WSCC 9-bus system. A case study on the NPCC 140-bus system also validates that the proposed approach can effectively estimate the boundary and the geometry of the feasible solution region in the Searching Space and find the optimal solution.
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Voronoi diagram based optimization of dynamic reactive power sources
2015 IEEE Power & Energy Society General Meeting, 2015Co-Authors: Weihong Huang, Kai SunAbstract:Dynamic var sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues or even voltage collapse. This paper proposes a new approach to optimization of the sizes of dynamic var sources at candidate locations by a Voronoi diagram based algorithm. It first disperses sample points of potential solutions in a Searching Space, evaluates a cost function at each point by barycentric interpolation for the subSpaces around the point, and then constructs a Voronoi diagram about cost function values over the entire Space. Accordingly, the final optimal solution can be obtained. Case studies on the WSCC 9-bus system and NPCC 140-bus system have validated that the new approach can quickly identify the boundary of feasible solutions in Searching Space and converge to the global optimal solution.
Hideyuki Takagi - One of the best experts on this subject based on the ideXlab platform.
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Acceleration of EC convergence with landscape visualization and human intervention
Applied Soft Computing, 2002Co-Authors: Norimasa Hayashida, Hideyuki TakagiAbstract:Abstract We propose Visualized EC/IEC as an evolutionary computation (EC) and interactive EC (IEC) with visualizing individuals in a multi-dimensional Searching Space in a 2-D Space. This visualization helps us envision the landscape of an n -D Searching Space, so that it is easier for us to join an EC search by indicating the possible global optimum estimated in the 2-D mapped Space. We first compare four mapping methods from the points of view of computational time, convergence speed, and visual easiness to grasp whole EC landscape with five benchmark functions and 28 subjects. Then, we choose self-organizing maps for the projection of individuals onto a 2-D Space and experimentally evaluate the effect of visualization using a benchmark function. The experimental result shows that the convergence speed of GA with human search on the Visualized Space is at least five times faster than a conventional GA.
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visualized iec interactive evolutionary computation with multidimensional data visualization
International Conference on Industrial Electronics Control and Instrumentation, 2000Co-Authors: Norimasa Hayashida, Hideyuki TakagiAbstract:We propose Visualized IEC as an interactive evolutionary computation (IEC) with visualizing individuals in a multidimensional Searching Space in a 2D Space. This visualization helps us envision the landscape of an n-D Searching Space; so that it is easier for us to join an EC search, by indicating the possible global optimum estimated in the 2D mapped Space. We experimentally evaluate the effect of visualization using a benchmark function. We use self-organizing maps for this projection of individuals onto a 2D Space. The experimental result shows that the convergence speed of the GA with human search on the visualized Space is at least five times faster than a conventional GA.
Ngochoa Nguyen - One of the best experts on this subject based on the ideXlab platform.
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optimizing the shortest path query on large scale dynamic directed graph
International Conference on Big Data, 2016Co-Authors: D U Phuonghanh, Haidang Pham, Ngochoa NguyenAbstract:This paper presents our approach in order to optimize the shortest path query on a large-scale directed, dynamic graph such as a social network. For this kind of graph, edges can be dynamically added or removed while a user asks to determine the shortest path between two vertices. To solve this problem, we propose a strategic solution based on (i) an appropriate data structure, (ii) the optimized update actions (insertions and deletions) and (iii) by improving the performance of query processing by both reducing the Searching Space and computing in multithreaded parallel. Thus, graph is globally organized by the adjacent lists in order to improve the cache hit ratio and the update action performance. The reduction of Searching Space is based on the way of calculating the potential enqueued vertices. Cilkplus is chosen to parallelize the consecutive queries. Our strategy was validated by the datasets from SigMod Contest 2016 and SNAP DataSet Collection with the good experimental results.
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BDCAT - Optimizing the shortest path query on large-scale dynamic directed graph
Proceedings of the 3rd IEEE ACM International Conference on Big Data Computing Applications and Technologies, 2016Co-Authors: Haidang Pham, Ngochoa NguyenAbstract:This paper presents our approach in order to optimize the shortest path query on a large-scale directed, dynamic graph such as a social network. For this kind of graph, edges can be dynamically added or removed while a user asks to determine the shortest path between two vertices. To solve this problem, we propose a strategic solution based on (i) an appropriate data structure, (ii) the optimized update actions (insertions and deletions) and (iii) by improving the performance of query processing by both reducing the Searching Space and computing in multithreaded parallel. Thus, graph is globally organized by the adjacent lists in order to improve the cache hit ratio and the update action performance. The reduction of Searching Space is based on the way of calculating the potential enqueued vertices. Cilkplus is chosen to parallelize the consecutive queries. Our strategy was validated by the datasets from SigMod Contest 2016 and SNAP DataSet Collection with the good experimental results.
