Power system's efficient operations and management heavily rely on dynamic economic dispatch (DED), which, due to its integration with spatial and temporal factors, poses a elaborate and intricate challenge in optimizing decision-making processes. The introduction of vehicle-to-grid (V2G) technology, which allows for the integration of plug-in electric vehicles (PEVs) to connect to the grid, serves as a viable solution to mitigate grid fluctuations and capitalize on the advantages of load leveling during peak times and utilizing off-peak electricity consumption. The paper introduces a model that incorporates current date, hourly dispatch of power systems as well as the influence exerted by Plug-in Electric Vehicles (PEVs). To resolve the model, an Osprey optimization algorithm (OOA) is introduced.

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Multi-objective Dynamic Economic Dispatch

  • Wenqiang Yang,
  • Xinxin Zhu

摘要

Power system's efficient operations and management heavily rely on dynamic economic dispatch (DED), which, due to its integration with spatial and temporal factors, poses a elaborate and intricate challenge in optimizing decision-making processes. The introduction of vehicle-to-grid (V2G) technology, which allows for the integration of plug-in electric vehicles (PEVs) to connect to the grid, serves as a viable solution to mitigate grid fluctuations and capitalize on the advantages of load leveling during peak times and utilizing off-peak electricity consumption. The paper introduces a model that incorporates current date, hourly dispatch of power systems as well as the influence exerted by Plug-in Electric Vehicles (PEVs). To resolve the model, an Osprey optimization algorithm (OOA) is introduced.