The integration of large-scale renewable energy significantly increases the computation time of reliability assessment and tracing. To solve this problem, the traditional methods cluster the scenarios directly based on renewable energy data. However, it could lead to errors in reliability assessment due to scenarios with similar risks. In this paper, a multi-scenario risk-oriented clustering algorithm considering renewable energy is proposed. The enumeration method is used to calculate the risk for different scenarios. According to the risk of each scenario, the Fuzzy C-means clustering method is adopted to cluster the scenarios, which maximizes the similarity of scenarios in the same cluster. The high-risk scenarios that contribute more to the reliability index are retained. The system reliability assessment and tracing are conducted based on the clustered scenarios. Case studies on the IEEE RBTS-6 and RTS-79 systems verify the accuracy and efficiency of the proposed method.
Abstract. PV and energy storage integrated grid-connected converter (GCC) is used popularly in distribution generation (DG) system. As there is a significant increase in the size and capacity of grid-connected power plants, the stability and reliability of the grid become more important. Different from the traditional synchronous generator, the fault characteristics of GCC are affected by its control strategy, thus this paper researches the fault characteristics of GCC under different control strategies. Firstly, active and reactive power decoupling control strategy and fault characteristics of GCC under PQ control are analyzed. The fault current characteristics of GCC under low voltage ride through (LVRT) control are studied as well. And equivalent current source model of the GCC under PQ and LVRT control during grid fault period are derived. Finally, the working principle and fault characteristics of GCC under droop control are studied. The influence that the voltage sag level at point of common coupling (PCC) has on the fault characteristics of GCC is researched, and equivalent model of GCC with droop control is obtained. The simulation results verify the correctness of the theoretical analysis.
In order to solve the problem of power supply frequency instability after large-scale grid connection of new energy, a multi-objective programming optimization algorithm for large-scale grid connection of new energy considering frequency stability is proposed. Before planning, the limit evaluation method for grid connection of new energy considering the frequency stability of the power system is used to judge the frequency change limit of the power system to be connected to the grid. Through the real-time measurement method of power system frequency under the large-scale grid connection of new energy, the real-time change value of power system frequency under the large-scale grid connection of new energy is calculated. Combined with the mastered frequency change limit and realtime frequency change value of power system, an optimization decision-making model for multi-objective planning of large-scale grid connection of new energy is constructed, and the improved genetic algorithm is used to solve the grid connection strategy that the frequency control quantity does not exceed the limit and the auxiliary cost of multi-objective planning for grid connection is the minimum. It is verified that the frequency of IEEE-30 standard node system is stable and within the limit after the algorithm is used, and the auxiliary cost of multi-objective planning for grid connection is significantly reduced.
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