A Novel Optimization Approach for the"Power Source-Network-Load-Storage Integration Project"Based on a Multi-Time-Scale Energy Balance Algorithm
Against the backdrop of global consensus on promoting a low-carbon economy,the integration of power source,network,load,and storage is of great significance in helping to achieve carbon peak and carbon neutrality goals,and promoting the green and low-carbon transformation of the power system.However,the construction of demonstration projects has many difficulties and pain points in the planning,implementation and operation stages.In view of its importance,this study took the balance of system power at multiple time scales as the starting point to provide a new framework to discuss the scientific optimization configuration of various elements of source,grid,load and storage:taking the maximum substitution of green electricity as the goal,taking the safe use of electricity and the green electricity absorption of the field stations as the constraint,adopting the multi-time scale energy balance algorithm.While achieving smooth and safe operation of the project,it also takes into account economic efficiency and grid friendliness;in the part of demonstration,the efficiency of this method was verified by the example of the power source-network-load-storage demonstration project in Daqing OilField.The framework provides a novel approach for the planning and allocation of integrated source-network-load-storage projects,the exploration of new modes of new energy development and construction,and the scientific and technological innovation of large-scale energy storage.It has constructive significance for ensuring the safe and stable operation of the power system,exploring new models for the development and construction of new energy,and carrying out large-scale energy storage technological innovation.
integration of power source-network-load-storagea green-oriented transition of energya multi-time-scale energy balance algorithm,nonlinear programmingKarush-Kuhn-Tucker conditionsDaqing OilField