Search Results (3)

To solve the voltage stability problem of electric vehicles connected to the distribution network in the limit state, a reactive power compensation strategy based on the holomorphic embedding method and electrical distance is proposed. Firstly, the load model of the electric vehicle charging station is constructed, and the limit of the charging power of the electric vehicle connected to a certain bus is obtained. Then, the power flow embedding equation of the power system is constructed by the holomorphic embedding method, and the analytical expression of the voltage rational function is introduced based on the Padé approximation algorithm. The voltage collapse point is solved by the distribution of zeros and poles of the rational function. Then, a method of reactive power and voltage control partition based on electrical distance is proposed. According to the principle of weak regional coupling and strong interval coupling, the power system is divided into several regions by spectral clustering and a k-means clustering algorithm. The order of the voltage stability margin value s is obtained by connecting the limit charging power to each bus of the power system. In this paper, the reactive power compensation strategy proposes to add reactive power compensation devices to the buses with the weakest voltage stability margin in different zones. Finally, compared with other reactive power compensation strategies 1 and 2, the reactive power compensation strategy provided in this paper is increased by 1.626121813 and 1.160494345 times, respectively. The superiority of this method is verified by simulation. Full article

This paper presents control relationships between the low voltage distribution grid and flexibilities in a peer-to-peer local energy community using a stratified control strategy. With the increase in a diverse set of distributed energy resources and the next generation of loads such as electric storage, vehicles and heat pumps, it is paramount to maintain them optimally to guarantee grid security and supply continuity. Local energy communities are being introduced and gaining traction in recent years to drive the local production, distribution, consumption and trading of energy. The control scheme presented in this paper involves a stratified controller with grid and flexibility layers. The grid controller consists of a three-phase unbalanced optimal power flow using the holomorphic embedding load flow method wrapped around a genetic algorithm and various flexibility controllers, using three-phase unbalanced model predictive control. The control scheme generates active and reactive power set-points at points of common couplings where flexibilities are connected. The grid controller’s optimal power flow can introduce additional grid support functionalities to further increase grid stability. Flexibility controllers are recommended to actively track the obtained set-points from the grid controller, to ensure system-level optimization. Blockchain enables this control scheme by providing appropriate data exchange between the layers. This scheme is applied to a real low voltage rural grid in Austria, and the result analysis is presented. Full article

Distribution networks are typically unbalanced due to loads being unevenly distributed over the three phases and untransposed lines. Additionally, unbalance is further increased with high penetration of single-phased distributed generators. Load and optimal power flows, when applied to distribution networks, use models developed for transmission grids with limited modification. The performance of optimal power flow depends on external factors such as ambient temperature and irradiation, since they have strong influence on loads and distributed energy resources such as photo voltaic systems. To help mitigate the issues mentioned above, the authors present a novel class of optimal power flow algorithm which is applied to low-voltage distribution networks. It involves the use of a novel three-phase unbalanced holomorphic embedding load flow method in conjunction with a non-convex optimization method to obtain the optimal set-points based on a suitable objective function. This novel three-phase load flow method is benchmarked against the well-known power factory Newton-Raphson algorithm for various test networks. Mann-Whitney U test is performed for the voltage magnitude data generated by both methods and null hypothesis is accepted. A use case involving a real network in Austria and a method to generate optimal schedules for various controllable buses is provided. Full article