Research On Multi-objective Coordinative Optimization Of Network Reconfiguration For Power System Restoration

As modern society is increasingly dependent on the power supply,the economic losses and social effects caused by blackouts are becoming more and more serious.Therefore,it is of great significance to study how to realize fast and safe restoration of power system after a major blackout.Network reconfiguration is the most important phase in the whole restoration process,when the backbone network is constructed by restoring vital plants,substations and transmission lines in the system,and the strength of the restored network is improved through the restoration and adjustment of the transmission network.As a consequence,the coordination mechanism of different restoration subjects,restoration strategies and optimization methods of network reconfiguration are important research issues,which also play an important role in speeding up the restoration process and reducing the power loss.Around the kernel tasks of network reconfiguration,several issues are studied deeply and systematically in this thesis,including energizing path optimization,coordinated restoration of generators and vital loads,looped network restoration,and load restoration optimization.Corresponding optimization models are established for different problems,and multi-objective optimization technologies and mathematical programming methods are introduced to solve the proposed models.Main contributions of this thesis are described as following:1.A general method for searching and evaluating the energizing paths of power system restoration is proposed.Power system restoration after a major blackout is a complex progress in which fault possibility of transmission lines is much higher than in the normal condition.The energizing path optimization based on the minimum cost flow model is studied,then an iterative searching method for alternative path schemes based on mixed integer programming is proposed.In order to make a comprehensive evaluation of the alternative schemes,an evaluation index set is established.The multiple attribute decision-making method based on similarity to ideal grey relational projection is introduced to achieve the final evaluation and ranking.The proposed energizing path optimization method could provide more comprehensive decision support for the dispatchers.2.A global optimization approach based on multi-time-stage coordination for network reconfiguration is proposed.Firstly,the vital load is introduced as one of the restoration objectives of network reconfiguration.Secondly,considering several constraints,a novel global optimization model for coordinative restoration of the units,vital loads and transmission network is established.By analyzing the intrinsic logicality of restoration action sequences,a two-step solving strategy for the global optimization model is proposed,in which the number of the restoration stages is first estimated and the objective functions are then optimized globally.The non-dominated neighbor immune algorithm and the variation coefficient method are employed to solve the proposed models.The proposed optimization strategy and method provide a new idea for the global optimization of multitime-stage network reconfiguration.3.An optimization decision-making method for looped network restoration to eliminate transmission line overload is proposed.During the network reconfiguration process,transmission line overloads may possibly occur with gradual pickup of loads due to the weak structure of the restored network.In view of this problem,a looped network restoration strategy is proposed to eliminate the line overloads by restoring some unenergized transmission lines.A mixed-integer nonlinear programming(MINLP)model considering AC power flow constraints is established firstly.In order to improve the computational efficiency,a fast hierarchical optimization method is established,in which the original problem is decomposed into a master problem and two sub-problems solved iteratively.The proposed looped network restoration strategy could eliminate the overload of transmission lines and enhance the strength of the restored network at the same time.The proposed hierarchical optimization algorithm with high computational efficiency is of great reference value for online decision making of power system restoration.4.A multi-objective optimization for load restoration during the last stage of network reconfiguration is proposed.The continuous process of load restoration is divided into a sequence of closely related time stages.The proposed model focuses on maximizing weighted restorable loads and minimizing square sum of all buses' voltage deviations of each load restoration time stage.Considering the frequency modulation process and system operation requirements,a novel constraint set is established.The normalized normal constraint method(NNC)is introduced to solve the bi-objective optimization model.By using NNC,the multi-objective MINLP problem is converted to a series of MINLP problems with single objective and additional linear constraints.An efficient commercial optimization software,GAMS(The General Algebraic Modeling System),is applied to solve the single-objective MINLP problems.The proposed load restoration method shows good performance in solution stability and engineering application.