A high proportion of renewable energy affects the power quality of distribution networks, and surplus energy will be sold to the upstream grid at a low price. In this paper, considering peer-to-peer energy transactions, the energy router-based multiple distribution networks are analyzed to solve the above problems and realize collaborative consumption of renewable energy. Presently, the investing cost of an energy router is high, and research on the economic operation of energy routers in distribution networks is little. Therefore, this paper establishes a planning model for energy routers considering peer-to-peer energy transactions among distribution networks, and explores the benefits of peer-to-peer energy transactions through energy router based multiple distribution networks. A structure of an energy router suitable for peer-to-peer energy transactions is selected, and a power flow calculation model based on a multi-layer structure is established. The energy router’s scheduling model is established, and unique functions of the energy router and revenue of each distribution network are considered. A power flow calculation model based on peer-to-peer interconnection of multiple distribution networks through energy routers is also established. Finally, simulation results verify the effectiveness of the proposed planning model. Results show that peer-to-peer energy transaction among distribution networks through energy routers can effectively reduce the comprehensive cost of distribution networks, significantly improve the power quality of the distribution networks, and reduce the impact of power fluctuation on the upstream grid incurred by the distribution network.

The power system is susceptible to failures, and further interruptions by subsequent outages which may cause extended events in the formed island. Most of the literature reviewed has focused on island formation after the disconnection of the main grid supply. However, there is still a need to analyze the post-restoration failures to improve the resilience and minimize the pro-longed disconnection of priority customers. The current research investigates the behavior of islanding schemes under secondary collapses and provides an adaptive solution to withstand such severities. A new total active critical node finding methodology is presented which eases the rearrangement of the initially formed island when affected by multiple faults or DG failures. The concept of single islanding with the coordination of multiple DGs is also discussed, in which the DG's power-sharing capacity is not confined to the boundaries of only particular islands. An economic plan is also proposed to select the controlled type DGs to reduce the overall cost of generation by reducing fuel cost. To evaluate the network's effectiveness and robustness, the proposed adaptive method is deployed on an updated IEEE 69-bus distribution system.

Line parameters play an important role in the control and management of distribution systems. Currently, phasor measurement unit (PMU) systems and supervisory control and data acquisition (SCADA) systems coexist in distribution systems. Unfortunately, SCADA and PMU measurements usually do not match each other, resulting in inaccurate detection and identification of line parameters based on measurements. To solve this problem, a data-driven method is proposed. SCADA measurements are taken as samples and PMU measurements as the population. A probability parameter identification index (PPII) is derived to detect the whole line parameter based on the probability density function (PDF) parameters of the measurements. For parameter identification, a power-loss PDF with the PMU time stamps and a power-loss chronological PDF are derived via kernel density estimation (KDE) and a conditional PDF. Then, the power-loss samples with the PMU time stamps and chronological correlations are generated by the two PDFs of the power loss via the Metropolis-Hastings (MH) algorithm. Finally, using the power-loss samples and PMU current measurements, the line parameters are identified using the total least squares (TLS) algorithm. Hardware simulations demonstrate the effectiveness of the proposed method for distribution network line parameter detection and identification.

An energy router can effectively optimize the network loss and power quality of distribution networks. The optimal configuration of the energy router is relatively complex because issues dynamically influence each other, such as the location of the energy router, optimal number and capacity of its ports, and building new distribution lines for the ports. Presently, there has been very few research studies on the practical problems for the energy router. In this paper, a planning model of an energy router combined with the distribution network is established, which fully exploits the active and reactive power control abilities of the energy router to optimize the operation of the grid. The configuration problem is decoupled into two stages. The upper layer determines the location of the energy router and the parameters of the candidate new distribution lines for the ports. The lower layer calculates the optimal configuration of the energy router by minimizing the total annual cost. Because of the same rated bus voltage in the distribution network, the existing structure of the energy router is changed to be more applicable for the distribution network, and then the power flow model of the energy router is also modified. Due to the nonlinearity of the model, the planning model is converted into a mixed-integer second-order cone model to solve efficiently. In addition, some core factors influencing the optimal scheme of the energy router are also analyzed in this paper. Simulation results show that the optimal scheme of the energy router can significantly improve the economic deployment of the energy router, and optimize the network loss and power quality of the distribution network.

Power systems can suffer outages, causing complete or partial disconnection of their power supply to load centers within the distribution networks. Distributed Generation (DG) plays an essential role in power systems. DG can be used as a back-up power source to enhance the resiliency and reliability of a power system. Island mode operations after outages in an active distributing network (ADN) is an effective way to maintain continuity of the power supply to significant loads. It is a quite complicated task for power system operators to find the power flow path. Previous studies have primarily used pre-defined guidelines to find feasible power flow paths, and have focused on multiple islands for restoration. In these studies, possible restoration pathfinding with DG was the fundamental weakness, and furthermore, the power of DG was limited to pre-defined boundaries in the form of islands. Therefore, in this study, a new algorithm has been proposed, which uses the minimum spanning tree (MST) method to find the most feasible path. The proposed algorithm starts at any random node (in this case, DG), and progresses by selecting the next node with the least cost (weight), thus considering all the nodes through which power will flow. The proposed model is formulated as a multi-objective program considering the priority of loads and minimum power loss. The effectiveness of the proposed model is tested on a modified IEEE69-bus distribution system with the penetration of multiple distributed generation sources at different nodes. Results were compared with the strategies found in literature, and the proposed method was found to be feasible and efficient.