This invention discloses a method for energy
community electricity-carbon differential matching based on an improved
slime mold algorithm, belonging to the field of smart grids. First, considering the
coupling characteristics of energy hubs at the distribution
network level, a data-driven method is used to quantitatively analyze the peak-valley
coupling potential between different types of energy hubs. Initial differential matching is then performed on energy hubs with different external characteristics. Combining the load characteristics and carbon quota balance of energy hubs, a comprehensive
index system that considers both regional structural and functional needs is constructed. Finally, aiming for optimal overall energy
community characteristics, a matching strategy based on an improved
slime mold optimization
algorithm is proposed, introducing an adaptive search mechanism and
information sharing strategy to optimize the structure and boundaries of the energy
community. This invention simulates the dynamic matching process of energy communities, achieving differential matching that considers both
electricity and carbon quotas, efficiently and accurately determining the boundaries and
optimal matching schemes of energy communities, providing a new approach to improving the comprehensive benefits of
electricity and carbon emission management.