Power System Self-Organized Criticality Analysis Based On Improved Blackout Model

With the scale of interconnected power grid growing, ensure the operational reliability of large-scale interconnected power grid becomes the highest goal that must be achieved. In recent years, there have been several large scale blackouts caused by cascading failure have serious influence, and fully exposed the vulnerability and complexity of the large-scale interconnected power grid. In this view, applying complexity theory and methods to explore the structural features and internal mechanism of interconnected power grid blackouts has great practical significance.To research and analysis the self-organizing critical features of power system blackouts, there ware several power system blackouts models had been proposed to simulate the evolution mechanism of power system and blackouts caused by cascading failure, and had made many valuable achievements; however, because of the simplification of different degrees, there are some differences between those models and the actual power system engineering, further research is needed.To overcome the shortcoming in the existing power grid self-organized criticality simulation models, the main researches of this paper are as follows:① An improved OPA model based on DC power flow is proposed, which analyze the power system blackouts self-organized criticality. In the slow dynamic process of the improved model considers the action of the transmission network expansion planning. The transmission network expansion planning model, which’s objective function is minimum comprehensive cost, considers that the transmission lines are updated by adding new lines or changing lines, when changing lines, we took the conductor type applied in engineering as a basis for selecting lines and considered the line load rate constraints, which made the development of power system more close to engineering practice. Because transmission network expansion planning is a nonlinear mixed integer program problem, bi-level programming model is introduced and hybrid algorithm combing Particle Swarm Optimization algorithm and conventional optimize algorithms is adopted to solve this problem. Operation status of power system which is retrieved by Monte-Carlo sampling method is used to simulate blackouts caused by cascading failure in fast dynamic systems. Power system self-organized criticality is analyzed by simulation of the IEEE-30 system, and the effectiveness and practicality of the proposed improved OPA model is validated and illustrated.② An improved blackout model based on AC power flow is proposed to analyze the self-organized critical of power system. In the slow dynamic process of the improved model, the load forecasting, new expansion or capacity increase of power plants and transformer substations are simulated, and grid expansion plan model based on ac power flow considering the transmission wire type is used to realize the new reformation of power grid; In the fast dynamic process, the actions of scheduling measures and protective relaying are considered, and an AC power flow model considering the PV-PQ type conversion is used to simulate the voltage adjustment and control function of reactive power in power system. The simulation results show that the proposed improved blackout model can well simulate the evolution process in a long time scale as well as the propagation process of cascading failure in a short period of time in power system. Self-organized critical of power system blackouts is also effectively analyzed by this model.