Research On Unit Commitment Model And Method By Mixed Integer Programming

In recent years,with the rapid development of China’s economy,environmental problems such as resource shortages and air pollution are becoming more and more serious.Under this background,improving energy utilization rate is one of the main measures to reduce energy consumption and alleviate environmental pollution.Therefore,it is of great theoretical and practical significance for optimizing the scheduling plan of generating units,improving the utilization rate of resources,and reducing the emission of greenhouse gases such as carbon dioxide.This paper proposed a tight three-period high-dimensional projected unit commitment model for the traditional unit commitment problem.Firstly,the power output of units was projected into the interval [0,1] by using projection technology,and new state variables are introduced to express all operation states of a single unit in three time periods.Then,based on the actual operation requirement of the unit,the ideal expression forms of output upper bound constraints and ramping constraints of unit in three time periods are systematically derived by new state variables.According to the relationship between the new state variables and other state variables,the new state variables are eliminated in order to improve the compactness of the model.Finally,a tight three-period highdimensional projected unit commitment model was obtained.In order to verify the compactness and effectiveness of the proposed model,51 randomly generated realistic instances with units running from 10 to 1080 for a time span of 24 hours were used in our experiments.A deterministic global optimization algorithm,named center-point algorithm,is proposed to solve the unit commitment problem with carbon emission trading constraints in this paper.At first,a compact and tight approximate polyhedron of the nonlinear carbon emission trading constraint can be quickly constructed by using cutting-plane method and perspective-cuts technology.Then,a high-quality feasible solution can be obtained by finding the integer ellipsoid center of the approximate polyhedron.The integer ellipsoid center is an important research achievement in this paper,which is an extension of the Chebyshev center theory.To assess the performance of the proposed algorithm,we compared the algorithm with the state-of-the-art solver CPLEX.Twenty-two test instances with 28 to 1080 units running for a time span of 24 h were used in our experiments.The simulation results show that the proposed algorithm can find high-quality solutions faster than CPLEX,and it is suitable to solve large-scale unit commitment problem with carbon emission trading constraints.