To realize the potential of active distribution networks (ADNs) for improving power system flexibility and to cope with multiple uncertainties, a coordinated robust reserve scheduling (CRRS) model for the coupled transmission and distribution networks (CTD) is proposed in this paper. This model coordinates the generation resources both in the normal state and re-dispatch state to enhance the cost-effectiveness and reliability in a system perspective. A fully distributed framework based on the alternating direction method of multipliers (ADMM) is employed to solve this problem in a decentralized way. As the regional problem of the transmission system is non-convex, a two-layer iterative process (TIP) is presented to enhance the convergence property of standard ADMM. Since only the boundary information needs to be exchanged between the transmission and distribution systems, the communication burden is light and regional information is encrypted. Case studies on the T6D2 and T118D10 systems demonstrate the effectiveness of the proposed model and approach.

The ever-increasing integration of variable wind energy requests for a power system with high flexibility. In this paper, we formulate the real-time economic dispatch problem as a multi-stage robust program to leverage flexible resources, especially energy storage systems, in a broader timescale, and also to avoid the risk of high costs in critical scenarios. The multi-stage robust program is decomposed to the dynamic programming form and the fast robust dual dynamic programming (FRDDP) algorithm is developed to solve it efficiently. To tackle the nonconvexities caused by the inter-temporal constraints of ESSs, an estimation-correction method is developed, and measures of the approximation accuracy are presented. Comprehensive case studies comprising units up to 1371 are carried out to verify the effectiveness of the proposed model. Numerical results show that compared with the existing ones, the proposed multi-stage robust model achieves lower cost under the worst-case scenario and shows better scalability in large-scale systems.

Nowadays Distribution generation (DG) has achieved to further precious awareness, especially inside the power system fields, so the strength and dependability specifically in the distribution system. Optimum scheduling of DG not only focuses on the size of DG only too puts a load on the optimal location of generators. Install for DG at the optimum location along with optimal size into the distribution system would improve the system performance and also give price effectual solved to the planning of the distribution network. The positive impact of optimum DG position into the distribution system would improve system voltage profile, reduction in line losses, improved power standard, make better reliability and strength of the distribution network. GWO is modeled based on the unique hunt, searching for a target, encircling target, and attacking prey, are executing to perform the optimization. The GWO is determined to the IEEE-16, 30, 57 and 118-bus test systems radial distribution network as well as considering multiplier DG units in the system. The better study outcome of the attained to without DG, with DG, type 1 DG, type 2 DG, with type 3 DG at 0.9 pf and with type DG at unity pf. Moreover, the obtained is compared as well as the net outcome of the proposed procedure for the sequence to see the efficiency and effectual and the distribution systems.

To naturally characterize the long-time sequence coupled equipment such as energy storage systems (ESS) and to enforce the non-anticipativity of dispatch decisions under uncertain renewable energy, a multi-stage robust dynamic unit commitment (MRDUC) model is proposed in this paper. MRDUC transforms the multi-stage robust unit commitment into a dynamic programming form, which is the first attempt to combine day-ahead optimization with intra-day multi-stage robust dynamic dispatch. The unit commitment problem is solved in the pre-stage, and a simulation of intra-day multi-stage economic dispatch is done thereafter, which further refines the UC decision in an iterative way. A pre-extended -fast robust dual dynamic programming (PE-FRDDP) method is proposed to efficiently solve the MRDUC problem, which simultaneously optimizes the day-ahead UC and the intra-day decision policies. Case studies on the modified IEEE 6-Bus and 4 large-scale systems from 300 to 1888 buses demonstrate the effectiveness of the proposed model and the solution methodology.

Along with the improvement of electrical equipment reliability, people’s unsafe behaviors and human errors have become one of main sources of risks in power systems. However, there is no comprehensive study on human factors and human reliability analysis in power systems. In allusion to this situation, this paper attempts to analyze the impact of human factors on power system reliability. First, this paper introduces current situation of human factors in power systems and the latest research progress in this field. Several analysis methods are proposed according to specified situations, and these methods are verified by some power system practical cases. On this base, this paper illustrates how human factors affect power system operation reliability from 2 typical aspects: imperfect maintenance caused by human errors, and impact of human factors on emergency dispatch operation and power system cascading failure. Finally, based on information decision and action in crew (IDAC), a novel dispatcher training evaluation simulation system (DTESS) is established, which can incorporate all influencing factors. Once fully developed, DTESS can be used to simulate dispatchers’ response when encountering an initial event, and improve power system dispatching reliability.

Conventional power systems are developing into cyber-physical power systems (CPPS) with wide applications of communication, computer and control technologies. However, multiple practical cases show that the failure of cyber layers is a major factor leading to blackouts. Therefore, it is necessary to discuss the cascading failure process considering cyber layer failures and analyze the vulnerability of CPPS. In this paper, a CPPS model, which consists of cyber layer, physical layer and cyber-physical interface, is presented using complex network theory. Considering power flow properties, the impacts of cyber node failures on the cascading failure propagation process are studied. Moreover, two vulnerability indices are established from the perspective of both network structure and power flow properties. A vulnerability analysis method is proposed, and the CPPS performance before and after cascading failures is analyzed by the proposed method to calculate vulnerability indices. In the case study, three typical scenarios are analyzed to illustrate the method, and vulnerabilities under different interface strategies and attack strategies are compared. Two thresholds are proposed to value the CPPS vulnerability roughly. The results show that CPPS is more vulnerable under malicious attacks and cyber nodes with high indices are vulnerable points which should be reinforced.