Research On Optimal Dispatch Of Microgrid Considering Comprehensive Demand Response

In the context of increasing energy demand and environmental pressure,with the rapid development of technologies such as cogeneration of heat and power and Power to Gas(P2G),improving the utilization rate of energy and enhancing the coupling ability of different energy sources have become a research hotspot.Microgrid is a coupled system that contains multiple types of energy in production,transmission and consumption.Microgrid has the advantages of fast and timely demand-side response and can meet various demands of load,and improve the comprehensive utilization rate of energy by means of multi-energy complementary operation.After summarizing the research status of optimal scheduling and demand response of microgrids,this paper studies the comprehensive demand response of electric and thermal multi-loads in view of the fact that the current research rarely involves the schedulability of multiple types of loads on the demand side.The specific research work is as follows:Firstly,the architecture of the microgrid including wind turbine,cogeneration unit,P2 G equipment,gas-fired boiler,electric boiler,storage battery,electrical load and thermal load is established.Then,the mathematical model of the each equipment is established and their operation characteristics are analyzed in detail.Taking economic cost and environmental protection cost as objective functions and considering various constraints,the optimal scheduling model of microgrid was established.Taking the minimum fluctuation of electric heating load as the objective function,the response model of users to TOU electricity price is established by using the elastic matrix of electricity price and the constraint of user satisfaction.For the thermal demand response,the thermal inertia of the thermal load is described by the autoregressive moving average model considering the perceptual fuzziness of the thermal load.The result of comprehensive demand response realizes the effect of peak clipping and valley filling and gentle load fluctuation.Aiming at the problems of the standard NSGA-Ⅱ algorithm,such as limited search range and slow convergence speed,a new NSGA-Ⅱ algorithm with improved crossover operator and improved adaptive mutation operator was adopted,and the superiority of the improved algorithm was verified by standard test function and performance evaluation index.Based on the uncertainty of load and wind power output,the fuzzy chance constraint programming was introduced to establish the fuzzy chance constraint conditions,which were clarified by the clear equivalence class.The improved NSGAⅡ algorithm was used to solve the scheduling model,and the optimal compromise solution was obtained by screening the Pareto optimal solution set.The effects of different confidence levels on cost are studied.Select the optimal confidence level,compare the results in four scenarios with or without considering the demand response or adding P2 G equipment,and study the influence of P2 G equipment capacity change on the results.Finally,the three algorithms were used to solve the scheduling model and the corresponding Pareto optimal front edge was obtained.The results proved that the improved NSGA-Ⅱ algorithm was more efficient and economical than the other two algorithms.An example is given to verify the validity of the proposed model.