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Load Leveling Potential Evaluation of Virtual Power Plant Based on Genetic Algorithm Optimization

  • Yafei Wang,
  • You Li,
  • Weijun Gao

摘要

The widespread adoption of renewable energy represents a crucial measure for addressing the global challenge of carbon emissions reduction. Despite the substantial energy-saving potential of renewable sources, their proliferation has been hindered by the intermittency of power generation. This paper proposes a Virtual Power Plant (VPP) model that incorporates the integration of updated high efficiency equipment, photovoltaic system, and energy storage system. The results demonstrate that VPPs deliver a significant load leveling potential, effectively enhancing the region’s energy self-sufficiency rate.