Taking into account the energy cost, pollution emission, wind power consumption, and other dispatching objectives in the regionally integrated energy system (RIES), the RIES multi-objective optimization model considering the integrated demand response is established. Firstly, the RIES modeling of equipment including electricity-to-gas, energy storage systems, cogeneration units, etc., and the introduction of a comprehensive demand response that specifically considers load reduction, load transfer, and load replacement in the region, aimed at reducing system load peaks and valleys difference. Then, the objective function to minimize the system energy cost, the abandoned wind power, and the pollutant treatment cost was established respectively, and the multi-objective optimization method was adopted—the Pareto front was solved by fuzzy weighted programming traversal weights, and then the decision was made based on evidence Method to find the optimal scheduling strategy. Finally, based on a typical case study, the results show that the proposed multi-objective optimization algorithm can effectively make trade-offs among multiple scheduling objectives, and RIES considering comprehensive demand response has advantages in terms of total energy consumption, environmental friendliness, and wind power consumption.
Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting
