The invention discloses an energy
internet network topology optimization method and
system based on a multi-objective
evolutionary algorithm, and belongs to the technical field of energy internet, and the method comprises the steps of geometrically driving evolutionary operation, preferentially connecting adjacent nodes, strengthening a triangular structure, and optimizing a link
layout in combination with an energy transmission efficiency weight. An NSGA-III
algorithm is improved, a
cosine similarity punishment mechanism and a dynamic weight strategy are introduced, and algebraic
connectivity and an R index are balanced; a dynamic repair mechanism quickly complements isolated sub-graphs through local evolution and depth-first search, and the
response time is shortened; a learning prediction topology adjustment strategy is reinforced, and a sliding window
multiplexing historical solution is combined, so that the convergence speed under wind and light fluctuation is improved. According to the method, the problems of target singleness, uneven
Pareto solution set distribution and dynamic response
lag in the prior art can be solved, algebraic
connectivity and node balance are improved, and the method can be widely applied to
dynamic energy internet optimization scenes containing wind and
light energy.