Multi-target particle swarm optimization-based wind-solar-diesel storage system optimization scheduling method and device, and storage medium

• Main Authors: PAN XIAOJUN, ZHU WANLU, HAN SHUWEI, YANG CHENGQIAO
• Format: Patent
• Language: Chinese; English
• Published: 27.10.2023
• Subjects: CALCULATING; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRICITY; GENERATION; PHYSICS; SYSTEMS FOR STORING ELECTRIC ENERGY; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a multi-target particle swarm optimization-based wind-light-diesel-storage system optimization scheduling method, equipment and a medium, belongs to the field of energy storage, and solves the problem that the benefit of wind-light-diesel-storage system optimization scheduling and the stability of a power system are reduced due to the fact that power load prediction and wind-light power generation power prediction are not fully considered in the prior art. The method comprises the following steps: establishing a prediction model; obtaining prediction parameters according to the prediction model; establishing a multi-objective particle swarm optimization-based optimal scheduling model of the wind-light-diesel-storage system, and determining an objective function and constraint conditions during energy storage optimal scheduling of the wind-light-diesel-storage system; and carrying out optimization solution on the target function by adopting a multi-target particle swarm algorithm to obt