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For the first time, the SCE-UA (shuffling complex evolution-University of Arizona) method is used to solve the management model for deep groundwater resources of the Yangtze Delta, which is a multi-aquifer system with large area and complicated geology conditions. A series of environmental geology problem, such as decreasing of groundwater resources, the land interstice and the land subsidence, emerged...
The need to optimize the operation of PV systems is justified by the fact that PV systems are expensive to build, fuel- free source, and it is therefore natural that user of such systems would want them to perform at their most optimal point. Under the faulted condition, the power curve has a multi-peak nature; conventional optimization technique can easily fall down in local optimal and initial point...
This paper presents an investigation of possible hybrid genetic algorithm/particle swarm optimization approaches to evaluate the flow of electric power in power transmission network. The possible schemes are presented and their performances are illustrated by applying them to the power flow problem of the Klos Kerner 11-busbar system.
This paper proposes optimal task decomposition agents (OTDAS) of the multiagent power plant control system. The goal, decision-making and operation of the OTDAS are introduced. The OTDAS optimally decompose the task of power plant control system through an optimization agent and a decomposition agent. The optimization agent makes decision using Genetic Algorithm (GA). The results of the OTDAS show...
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