Research On Dispatch Of IES-CCHP And Parameter Coupling Particle Swarm Optimization Algorithm

Dominated by a variety of new green energy,Energy Internet will be developed into a energy network which takes electric energy as the main carrier.To insure the diversified energy complementation horizontally and collaboration development vertically among source,network,load and storage,as well as to enhance the comprehensive utilization level of diversified energy have become the main direction of Integrated Energy System(IES).In the research of Integrated Energy System,the coupling of electricity,gas and heat is described quantitatively based on the energy hub model and the coupled matrix of multi-input and multi-output of energy.Three normal distributions are used to characterize the randomness of electric,gas and thermal output.Then a comprehensive income model of Integrated Energy System-Combined Cold Heat and Power(IES-CCHP)is established,considering the coupling and randomness of electricity,gas and heat.In order to overcome the defects of traditional particle swarm algorithm,such as easily falling into local extreme value,low efficiency and high randomness,another enhanced particle swarm optimization(PSO)coupling all parameters(PC-PSO)is also put forward.By strengthen the correlation between different parameters of different particles,this algorithm uses the coupling and coordination strategy to make each particle effectively connected with each dimension parameter and integrates the real-time information of each particle to launch the next optimization scheme.When connected to power grid,CCHP can not only buy electricity from the system,but also sell electricity to the system.As the promotion of peak-valley price can inject more vitality into demand side,the cost of electricity sales is introduced to improve the economical efficiency.Then an IES-CCHP regional joint environmental economic dispatch model is established,In the model,the coupling of electricity,gas and heat of IES is taken as constraints,and the cost of purchasing and selling electricity,the cost of the fuel and the environmental cost of the effluent pollutants is taken as objective function.In order to solve this problem in a targeted way,an improved parametric coupled particle swarm algorithm based on Nataf transform is presented.The correlation random variable is transformed into a spatial sample matrix closer to the original variable by Nataf transform,then the actual characteristics of each particle are combined to optimize.The algorithm have stronger search ability in both vertical and horizontal dimension,thus solving the problem of easily precocious puberty.In order to analyze the performance of the improved particle swarm optimization that include parameter coupled particle swarm optimization and the parameter coupled particle swarm optimization based on the Nataf transform and the standard particle swarm optimization algorithm adequately,several single objective and multi-objective test functions are taken to verify the results.The results show that all the improved algorithms proposed by this paper are superior to the traditional PSO,,which obviously reduces the error and randomness,has strong global search ability and more reliable optimization results.The proposed joint dispatch model is more effective for energy efficient utilization,power economic dispatch,energy saving and emission reduction.