This paper develops a novel dynamic three-phase symmetric distribution network reconfiguration (DNR) approach based on hierarchical clustering with timing constraints, which can divide the time period according to the time-varying symmetric load demand and symmetric distributed generations (DGs) output condition for a given time interval. The significance of the proposed technique is that by approximating the cluster center as the load status and DGs output status of the corresponding period, in this way, the intractable dynamic reconfiguration problem can be recast as multiple single-stage static three-phase symmetric DNR problems, which can effectively reduce the complexity of the three-phase symmetric dynamic reconfiguration. Furthermore, an improved fireworks algorithm considering heuristic rules (H-IFWA) is proposed and investigated to efficiently manage each single-stage static three-phase symmetric DNR problem. In order to avoid trapping into a local optimum or to facilitate the computational performance, the power moment method and the coding method based on heuristic rules are employed to reduce the solution space. The effectiveness of the proposed H-IFWA is validated on the IEEE 33, 119-bus system and a practical-scale Taiwan power company (TPC) 84-bus test system with DGs.

The characteristics of three‐phase imbalances are present in medium‐ and low‐voltage distribution networks. Integrating single‐phase distributed generation (DG) exacerbates network imbalances, resulting in increased power losses and potential safety hazards. To address these issues, a dynamic reconfiguration strategy (DNR) for three‐phase imbalanced distribution networks, considering soft open points (SOP), has been proposed. The objective is to alleviate the three‐phase imbalance and minimize the operational costs of the distribution network. Within the reconfiguration strategy, the constraints of DG current imbalance in practical system operations are considered. A three‐phase imbalanced DNR model that simultaneously considers the constraints of the SOP and DG current imbalances is introduced. This model aims to optimize the operation of all devices, including the SOP, to address the overall imbalance of the distribution network. This enables the authors to transform the non‐linear model into a mixed‐integer linear programming model, significantly improving the solution efficiency. To validate the proposed strategy, simulations of a modified IEEE 34‐node distribution system and an actual 78‐node distribution system were conducted. The results demonstrate that this strategy offers significant economic benefits and ensures the security of the distribution network.

The penetration of a high proportion of renewable energy sources (RES) into the power grid intensifies the source–load imbalance, which greatly weakens the network transmission performance and power supply quality, and the effect of relying only on individual regulation within the region is negligible. To enhance the capacity of interconnection and coordination among different areas of power systems and improve the accommodation level of RES and low-carbon efficiency, an optimal transmission switching model based on the bus tearing method is proposed in this article. Firstly, the complex power system is decomposed based on the bus tearing method, and thus, the interconnected power grid structure of the multiarea system is constructed. Secondly, the optimal model of interconnected power grid decomposition and coordination structure considering renewable energy generation is constructed, based on exquisite modeling, to reduce the difficulty of unified analysis and decision-making of the multiarea interconnected power system, and the expression of the model is simplified in the form of the matrix. Then, the analytical target cascading (ATC) method is used to decouple the complex model from the main problem and subproblem and solve the distributed parallel problem, to understand the optimization of the decomposition and coordination structure of the interconnected power grid with source–load coordination. Finally, based on the case studies of the IEEE 14-bus system and IEEE 118-bus system, the effectiveness of the proposed model and method is verified, the coordinated operation of the interconnected power grid and the optimal allocation of network resources are achieved, and the economy of power system operation is improved.

The high penetration of intermittent renewable energy requires a more flexible power grid. Electric vehicles (EVs), capable of rapid grid response, serve as efficient and economical flexible resources. However, EV users often prefer fast charging and are reluctant to participate in vehicle-to-grid (V2G), while overstay occupancy (OC) at fast charging stations (FCSs) results in penalties for them. Thus, leveraging the bidirectional flexibility of EVs is essential for efficient grid operation at FCS. This article proposes a method to quantify the flexibility region (FR) of FCS operation considering OC and EV user discharge willingness (EUDW). First, a FR model and evaluation indices are developed for FCS integrated with photovoltaic (PV) and energy storage systems (ESSs), enabling precise quantification of EV flexibility in different states and determining the adjustable boundaries of the FR. To address the randomness of EUDW, an incentive model is proposed, considering OC duration, net discharge compensation, and discharge margin to incentivize users’ participation. In addition, a dual-layer decision framework, incorporating behavioral economics and affine fuzzy logic control, is developed to enhance decision-making under EUDW uncertainty. Finally, a collaborative optimization scheduling model for the flexibility resources of FCS is proposed to maximize benefits for both operators and users. Case studies verify that the proposed model and methods effectively improve the operational flexibility of FCS by coordinating flexible resources, enhancing station revenue, balancing flexibility supply and demand, and reducing users’ expenses.

Because stochastic fault cases (i.e., opportunistic maintenance strategy) of the equipment are not considered in the condition-based maintenance decision of the system, which will deviate from the actual situation, a system condition-based maintenance scheduling model considering opportunistic maintenance strategy is proposed in this paper. To implement the system maintenance strategies, the correlation set is formulated by considering the relationship among different equipment. According to renewal process theory, the availability of the correlation set considering planned maintenance and opportunity maintenance is deduced and the maintenance strategy of the system is realized. Then, to reflect the relationship between equipment maintenance and system operation, a system state scheduling model aiming at minimizing the sum of maintenance risk and failure risk as well as considering system resource constraints is proposed, thus obtaining the optimal maintenance schedule based on system state. Finally, a simple test system and IEEE-RTS79 node system are employed to demonstrate the feasibility and effectiveness of the proposed maintenance model, and it also verified that the proposed model can be integrated into the power system condition-based maintenance theory.