Research On Robust Optimal Dispatching Of Integrated Energy System Based On Confidence Gap Decision

With the rapid development of industrial productivity and economy,traditional energy systems have problems such as low energy utilization efficiency,difficulty in absorbing renewable energy,and difficulty in meeting the diversified load demand,which largely limits the reliability and flexibility of the energy system.In this case,integrated energy system,as a sustainable energy system,has the advantages of multi-energy complementation,strong renewable energy absorption capacity,and reasonable energy distribution,which has attracted people’s attention.However,the optimal dispatching of integrated energy system still needs to face many problems,such as the uncertainty modeling analysis of wind power,photovoltaic and other renewable energy output and load demand,the coupling relationship and transformation relationship between multiple energy sources,and the efficient use of energy,etc.The above problem has become the key in the study of optimal dispatching of integrated energy system.Firstly,this research introduces the basic concept and framework structure of the integrated energy system.On this basis,it further analyzes the operating principles and mathematical models of the energy conversion equipment and energy storage equipment in the system.Thus,it lays the theoretical foundation for the subsequent chapters to study the optimal dispatch model of the integrated energy system.Secondly,in order to improve the consumption level of renewable energy,fully consider the coupling between multiple energy sources and ensure the efficient use of energy.Aiming at the uncertainty of renewable energy output,this research uses Gaussian mixture model to fit the probability distribution of wind power and photovoltaic output forecast errors.On this basis,the influence of the uncertainty of the load forecast error is considered.In view of the current uncertainty processing methods mainly include stochastic programming method and robust optimization method.Among them,the stochastic programming method has the disadvantages of large calculation amount and weak robustness,while the robust optimization method is often too conservative or subjective,so this research adopts Information Gap Decision Theory(IGDT)which has higher computational efficiency to deal with the uncertainty problems in the integrated energy system.First of all,combining the probabilistic confidence interval with the robust idea of IGDT,a new confidence gap decision theory(CGDT)is proposed,and from the perspective of improving the energy efficiency quality and economic benefits of the system,the goal is to maximize the exergy efficiency and minimize the operating cost.Function to construct a multi-objective robust optimal scheduling model for the integrated energy system based on the CGDT.After that,according to the uncertainty theory,the opportunity constraints in the model are transformed into equivalent certainty constraints in order to solve the model simply.The CGDT model proposed in this research can not only reduce the conservativeness of conventional robust decision,but also overcome the roughness of the uncertainty set and the subjectivity of the target deviation factor in the traditional IGDT model.Thirdly,in order to achieve an efficient solution to the robust optimal dispatching model of integrated energy system with multi-objective coupling,high-dimensional nonlinearity and multi-constraint,this study proposes a new type of adaptive harmonic aliasing mechanism multi-objective compound differential evolution algorithm,which effectively taking into account the optimization speed and the optimization depth in the later stage of algorithm evolution.Moreover,the fuzzy set theory is used to obtain the optimal compromise solution for decision makers to choose the dispatching plan.Finally,an integrated energy system is used as an example to perform simulation calculations.The analysis of the simulation result shows that the proposed CGDT has better robustness,economy and energy efficiency,and has better adaptability in dealing with uncertainty problems.The new adaptive harmonic aliasing mechanism multi-objective compound differential evolution algorithm is obviously superior to other algorithms in the optimization performance,which verifies its effectiveness and superiority.The research results can be further expanded and applied to other fields such as integrated energy system planning and coordinated operation of multi-region integrated energy systems.