With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); soft open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.

Under the background of complicated interconnected network, the splitting criterion for accurately capturing the electrical center in real time is the prerequisite of power grid splitting. This paper studies the features of electric quantity in the electrical center in aspect of the instantaneous frequency, and proposes the out-of-step splitting criterion for power systems based on bus voltage frequency. Firstly, through the establishment and solution to the out-of-step model of the power grid, the analytical expression of the voltage frequency at any position is obtained in the out-of-step oscillation, and the voltage frequency features of electrical center and non-electrical center are analyzed in details. Then, this paper constructs the typical scene of migration of electrical center to study the change rules of voltage frequency. Finally, the splitting criterion based on bus voltage frequency is proposed as well as the instruction for use. This criterion is easy to be realized and can adapt to the migration of electrical center. Also it is free from the limits of power network structure and operational mode. Simulation results of CEPRI-36 system and interconnected network example of one actual region verify the accuracy and the effectiveness of the proposed criterion.

As the requirements of economical operation and reliability on power grid are enhanced gradually nowadays, the existing under frequency load shedding (UFLS) scheme is not quite fit for the modern power system that integrates high wind power. In this paper, the impacts of high wind power penetration on the UFLS are discussed thoroughly. A novel adaptive load shedding (LS) scheme is presented taking the high wind power penetration into account. In the proposed scheme, the equivalent inertia constant (EIC) is calculated accurately to improve the power deficit accuracy so as to reduce the error of LS. The dynamic correction of power deficit is able to solve the negative effects of the wind power output random reduction/the wind generator tripping. Besides, the locking criterion is capable of avoiding the influences of the wind power output random increase on the LS, thus cutting down the LS costs and even preventing the frequency overshoot. Moreover, in terms of the LS parameters setting, the coordination of the low frequency protection of the wind generator and the frequency threshold is addressed. The location and capacity model of LS, which is based on the load characteristics, can ameliorate the frequency recovery process. Finally, the validity and robustness of the proposed scheme are verified in the simulations on the IEEE-39 bus system with high wind power penetration.

The controlled islanding for the power system is an effective method to deal with the emergent situations caused by large disturbances. The size of the solution space would increase exponentially as the scale of the power grid increases. The goal of our controlled islanding strategy is to divide the system into several islands quickly. Meanwhile, the generator coherency and the power-flow disruption have to be taken into consideration carefully. This paper proposed a two-stage fast islanding strategy for large power networks, which is on the basis of large power grid graph theories. In the first stage, the Stoer-Wagner algorithm is employed to obtain the grouping cluster of coherent generators in the dynamic undirected liaison graph. In the second stage, the improved Dinic max-flow method is proposed to search the optimal splitting boundary so as to acquire the minimum power flow impact. Our two-stage islanding strategy does not need to reduce the whole power network. Simulations on IEEE 118-bus and 162-bus power systems showed that the proposed strategy can acquire high quality solutions effectively and efficiently.

To address the challenges posed by the strong uncertainty of high-proportion renewable energy sources (RES) to the secure and stable operation of distributed real-time power dispatch (D-RTPD) in new-type power systems, this paper proposes an integrated solution combining a neighborhood feature aggregation-based graph attention network (NFA-GAT) and multi-agent deep deterministic policy gradient (MADDPG). First, the D-RTPD problem is modeled as a decentralized partially observable Markov decision process (Dec-POMDP), which effectively captures the stochastic game characteristics of multi-regional agents and the partial observability of grid states. Second, the NFA-GAT is designed to enhance agents’ perception of grid operating states: by introducing a spatial discount factor, it realizes rational aggregation of multi-order neighborhood information while modeling the attenuation of electrical quantity influence with topological distance. Third, a prior-guided mechanism is integrated into the MADDPG framework to eliminate constraint-violating actions by setting their actor logits to negative infinity, improving training efficiency and strategy reliability. Simulation validations on the IEEE 118-bus test system (75.2% RES installed capacity ratio) show that the proposed method achieves efficient training convergence. Compared with the multi-layer perceptron (MLP) structure, it attains higher cumulative reward values and scenario win rates. When compared with traditional model-driven (ADMM) and data-driven (Q-MIX) methods, the proposed method balances solution efficiency, operational safety (98.7% maximum line load rate, zero power flow violation rate), and economic performance ($12,845 daily dispatch cost), providing a reliable technical support for D-RTPD under high-proportion RES integration.

In the global transition toward low-carbon power systems with high renewable energy penetration, pumped storage has emerged as a strategic cornerstone for modern power grids. However, the collaborative planning of pumped storage and backbone-grids faces critical challenges, including the lack of explicit quantification of the resilience value of pumped storage and the coarse treatment of N-1 connectivity constraints. This paper proposes a bi-objective resilient backbone-grid planning approach that integrates the pumped-storage hub effect, aiming to minimize total life-cycle costs and the system resilience mismatch index. The proposed framework incorporates network connectivity, N-1 connectivity (edge connectivity ≥ 2), and dual-scenario power flow security as rigid constraints. Furthermore, a three-stage constrained evolutionary algorithm TER-NSGA-II is developed. During the N-1 connectivity reinforcement phase, the max-flow min-cut theorem is employed to achieve precise validation and guidance for edge-connectivity enhancement. Case studies on the IEEE 118-bus system, together with extended validation on the IEEE 300-bus system, show that the proposed method can explicitly quantify the resilience value of pumped storage, obtain Pareto solutions that balance economy and resilience under strict edge-connectivity constraints, and demonstrate competitive overall performance in terms of solution-set quality, feasible-domain search stability, and scalability compared with NSGA-II and the more recent NSGA-III/NG benchmark.