Energy Storage Optimization Planning for Renewable Energy Enrichment Areas Considering Conditional Value-at-risk
Under the background of double carbon goal construction of the new power system,the disequilibrium of the spatial and temporal distribution of the renewable energy enrichment area and the load center aggravates the demand for energy storage configuration on the grid side.Aiming at the energy storage optimization configuration in large-scale re-newable energy transmission areas,considering the insufficient utilization of renewable energy transmission channels and the risk of energy storage investment caused by the uncertainty of renewable energy output and load,an optimal planning model for energy storage location and capacity was established.Considering the influence of grid constraints on local consumption and transmission of renewable energy,the model used CVaR based on K-MILP scenario clustering to measure the risk cost caused by these uncertainties and characterized the tail risk that the net investment cost exceeds a certain confidence level.Finally,the model was transformed into mixed integer linear programming model.The results show that considering the reasonable measurement of energy storage investment risk in energy storage planning is condu-cive to reducing the tail risk of energy storage investment caused by extreme scenarios of renewable energy output,and improving the local and outbound consumption capacity of renewable energy economically.
energy storage planningrenewable energyuncertaintyK-MILP scenario clusteringrisk measurementMILP
万方数据
维普
