A Solution Method For Many-objective Security Constrained Unit Commitment Of Power System Considering Flexibility

With the development of wind power generation technology,the energy crisis has been alleviated,but the random fluctuation of its output will affect the stable operation of power grid,so the system should have enough flexibility to adjust resources to balance its random fluctuation.At the same time,under the influence of other factors such as environmental pollution and electric power system reform,the formulation of unit generation plan should consider multiple objectives besides operation cost.Therefore,it is necessary to establish a many-objective security constrained unit commitment(SCUC)model of power system with wind power and propose an effective algorithm to solve the model.Firstly,a four objective SCUC model of power system with wind power is established to minimize system operation cost,network loss,power purchase cost and pollutant emission.The convex relaxation method is used to transform the model into a mixed integer convex programming model to reduce the computational complexity.Then a method for solving Pareto frontier of the four objective optimization problem is proposed.Firstly,the four objective optimization problem is transformed into a series of three objective optimization problems based on the Spearman correlation coefficient and ε-constraint method.Secondly,according to normalized normal constraint(NNC)method and a mathematical optimization solver GUROBI,the Pareto frontier surface of each three objective optimization problem is solved,and the fourth objective value is represented by the color column.Therefore,the Pareto frontier surface clusters of the four objective optimization problem in three dimensional space are obtained.Finally,the compromise optimal solution of the four objective optimization problem is obtained by entropy weight method.The results on the modified IEEE-9 bus system and an actual power grid demonstrate that the proposed model and algorithm can quickly and effectively obtain the evenly distributed Pareto frontier surface of the four objective optimization problem.Then,based on the limit scenario of uncertain fluctuation of wind farm output,a system flexibility risk index is proposed to evaluate the flexibility of each period,and considering the constraints of flexibility supply and demand,a five objective SCUC model is established to minimize the system flexibility risk,network loss,operation cost,power purchase cost and pollution emission.In order to solve the Pareto optimal solution set of the model,it is necessary to reduce the dimension of the objective first.According to objective selection algorithm and ε-constraint method,two dimensionality reduction methods of five objective optimization model based on two objective grid values and two objective Pareto frontier curve values are proposed respectively and the five objective optimization problem is transformed into a series of three objective optimization problems.Then the NNC method is used to solve the reduced three objective optimization model,and the color column is used to represent the upper two objective set to obtain the Pareto frontier surface clusters of the five objective optimization problem in three dimensional space.The modified IEEE-9 bus system is solved by using the grid based and curve based ε-constraint methods respectively,and the results are compared with those of elitist non dominated sorting genetic algorithm(NSGA-II).The results demonstrate that the curve based ε-constraint method is faster,and its Pareto frontier and compromise optimal solution are better.Finally,the test results on an actual power grid demonstrate that the curve based ε-constraint method can solve the five objective SCUC model of large-scale power grid more effectively.