DISTRIBUTED FRAMEWORK FOR SOLVING AND BENCHMARKING SECURITY CONSTRAINED UNIT COMMITMENT WITH WARM START DRIVEN BY DATA ANALYTICS

摘要

A method may improve commercial optimization solver performance on day ahead security constrained unit commitment through warm start and lazy constraint settings. Data analytics is performed to greatly improve the quality of the initial commitment solution and lazy constraint setting. A distributed optimization framework is provided to take advantage of the diversity from prevalent solvers (GUROBI and CPLEX) under different warm start settings. A systematic distribution profile based benchmarking method is also provided.