Abstract

The existing literature on integrated energy station-grid planning studies focuses on configuration planning. Therefore, a multi-objective hybrid particle swarm algorithm is used in this paper to solve a multi-objective optimisation model and combines a multi-indicator evaluation method based on evidence-based reasoning to select the solution with the highest evaluation value from multiple candidates (Pareto solution set) as the optimal solution. The optimal planning solution is selected from multiple candidates (Pareto solution set) by a multi-indicator evaluation method based on evidence-based reasoning, and the effectiveness of the proposed model is verified utilizing an example. The customer participation demand response optimises the demand curve by adjusting the flexible load, reduces the system operation cost and investment construction cost, and maximises the economic, environmental and reliability benefits of the integrated regional energy station grid.

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