• Energy Research

As the most important part of the power system load, the dynamic characteristics of motors are very important for power system simulation. The calculation is very large if all motors are modeled respectively. In order to reduce the amount of calculations, a dynamic equivalent modeling method of motors based on the improved hierarchical clustering algorithm is proposed in this paper. The two state parameters, the load rate and the product of inertia time constant and rotor resistance, are taken as clustering indexes. The improved hierarchical clustering algorithm is used to cluster dynamically the motors. And with the pseudo t2 statistics, it can obtain the best clustering results. Then it establishes the dynamic multi-machine equivalent model after each motor group equivalent. With the example system, the simulation results show that the proposed dynamic equivalent method can keep the dynamic characteristics of models and improve the equivalent accuracy.

Abstract In this study, a two-layer model is established for evaluating the adaptability and regulating the active power to improve the economy and stability of a distribution network. A flexible interconnection device (FID) is used to provide flexible, fast, and accurate power conversion control in the active distribution network. It solves the power reverse problem due to photovoltaics (PV). The adaptability model is established in the planning layer to evaluate the revenue of the distribution network after access to FIDs in different numbers and positions with respect to the economy. The adaptive step-size search algorithm and FID active power transfer interval (which can be advantageous to the distribution network) are considered as the operation regions. Subsequently, the operation regions are transferred to the active power regulation model in the optimization layer via the sequential scan method to adjust the PV permeability and load ratio of the distribution network for stability. The elitist non-dominated sorting genetic algorithm is used to select the optimal position, number, and active power transfer values of the FID corresponding to the optimal PV permeability and load rate in the operation regions. Finally, the results of a realistic case study are provided and indicate that the proposed approach improves the economy and stability of the distribution network. The simulation results verify the effectiveness and feasibility of the proposed method.

The zonal market (ZM) adopted in Europe, in contrast to the nodal market (NM), reconciles the inconsistency between physical networks and administrative management. However, the growing integration of renewable energy sources (RESs) has introduced zonal supply-demand imbalances that exacerbate congestion and the need to re-dispatch. Furthermore, different clearing mechanisms between the day-ahead and real-time markets provide further opportunities for collusive bidding, decreasing total social welfare (TSW). Thus, this paper is the first to propose a long-term congestion management (CM) framework through a market zone (MZ) configuration approach with CM assessment considering collusive bidding in the joint spot markets. More specifically, a topology-based location division (TLD) method is proposed to partition optimal MZs, ensuring the minimum number of MZs based on critical branches. Then, a bi-level evolutionary model is developed to analyze the collusive bidding of producers in the day-ahead and ancillary service markets. Finally, the established framework is applied to a 20-bus test and simplified European systems. Our simulation on the 20-bus system shows that compared with the initial ZM and NM, the congestion cost of the optimized ZM decreased by 90% and 33%, respectively, while the TSW increased by around 13% and 1%, respectively.