The networked operation of multiple energy sources is gradually becoming the direction of future powersystem development. The optimal scheduling of the multi-energy network system is an important means to cope with t...
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When regional power grid is asynchronized by high voltage direct current (HVDC) systems, the division of frequency regulation resources and reserve capacity weakens the system's ability to resist load fluctuation ...
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Building a renewable powersystem with renewable energy as the main part can give full play to the regulatory capacity of sources, network, loads, storage and other types of controllable resources. It is the key to pr...
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In the practical application of electromagnetic transient real-time simulation computing platform, due to the large amount of calculation and long calculation time of electromagnetic transient simulation calculation, ...
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The DC/DC converter in the DC microgrid is the core device that supports the efficient grid connection of power electronic drive devices such as new energy generation units and energy storage devices. In view of this,...
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The testing of HVDC new control function and training of HVDC operation personnel require the integration of powersystemsimulation and dispatching automation. This paper presents and builds AC&DC powersystem si...
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With the increasing scale and complexity of powersystem, the current scheduling strategy methods often have the problems of limited adaptability and unsatisfactory results. Therefore, a powersystem scheduling method...
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To address the issue of insufficient accuracy in wind power output forecasting, this paper proposes a Support Vector Machine (VSM) model based on similar day matching and kernel entropy component analysis for wind pow...
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powersystemsimulation involves simulating the operating states and dynamic processes of powersystems using mathematical models and computer technology to analyze and predict system behavior. Traditional simulation ...
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This study explores the optimization of Distributed Generation systems (DGS) within a Multi-Agent Deep Reinforcement Learning (MADRL) framework. The focus is on transforming the overall optimization goal of the system...
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