In order to solve the difficulties of dispatching the regional integrated energy system (RIES) under the operating conditions of multi-energy complementary mechanisms, as well as to achieve the purpose of economic operation and low carbon operation of the system, an optimal dispatching model of RIES, including demand response (DR) and an improved carbon trading mechanism (ICTM), is proposed. Firstly, a demand response model is established, the cooling, thermal, electricity, and gas load models under demand response are built, and then an improved customer satisfaction model is proposed based on the four demand response load models. In addition, since EV trips fit a normal distribution, the charging load of EVs is predicted using a Monte Carlo method and incorporated into RIES as a demand-side load; moreover, for EVs, an improved genetic algorithm is used to optimize EV charging, aiming to reduce the peak-to-valley difference; secondly, carbon emission quotas are provided for systems and EVs based on the baseline method and gratuitous allocation, and a carbon trading model is constructed based on carbon quotas and actual A carbon trading model for the system and EV is constructed based on the carbon allowances and actual carbon emissions; finally, four operation scenarios are set up in this paper, and the unit output scheme is developed with the objective of achieving the lowest total system operation cost and lowest carbon emissions. The four typical scenarios are solved using the MATLAB/CPLEX solver and compared for analysis. The simulation results show that an improved genetic algorithm for optimizing the ordered charging method of electric vehicle charging reduces the peak valley difference by 23.06%, and the total operation cost and carbon transaction cost are reduced by 16.13% and 83.10%, respectively, which can provide a reference for the environmental protection and economic dispatch of RIES.

To solve the problems of large fluctuation of photovoltaic output power affecting the safe operation of the power grid, a hybrid energy storage capacity configuration strategy based on the improved Harris hawks optimization algorithm optimizing variational mode decomposition (IHHO-VMD) is proposed. In this strategy, the improved Harris hawk optimization algorithm is used to adaptively select k and α in VMD parameters and decompose the photovoltaic output power and distinguish between correlated and uncorrelated modes. Similarly, the moving average method (MA) is used to extract the continuous component signal in the uncorrelated mode, and it is reconstructed with the related mode as the grid-connected power that meets the national standard. The hybrid energy storage system (HESS) is used to stabilize the fluctuation component signal. The minimum annual configuration cost of the energy storage system is established as the objective function. The simulation results show that the improved algorithm reduces the cost of the hybrid energy storage system by 6.15% compared with the original algorithm, suppresses the power fluctuation, and improves the economy and stability of the system.