With the continuous expansion of the power system scale and extensive application of phasor measurement units (PMUs), the secure operation of power systems has been increasingly concerned. In this paper, an integrated scheme for online dynamic security assessment (DSA) based on feature selection and regression prediction is proposed. First, partial mutual information (PMI) and the Pearson correlation coefficient (PCC) are used to select the key variables in the feature selection process. Second, an iterated random forest (IRF) is applied to predict the transient stability margin (TSM) based on the selected variables. Combining the feature selection process and regression prediction, a DSA model is constructed. Finally, a spatial-temporal dynamic visualization approach is proposed, which can intuitively provide real-time dynamic security information of power systems. The integrated scheme, which is tested on the IEEE 39-bus system and a practical 1648-bus system provided by the software PSS/E, exhibits desirable assessment accuracy and is suitable for online application. In the robustness test, some impact factors for power system operation are considered, such as topology change, variation of generator/load power distribution and variation of load characteristics. Moreover, the impacts of missing data and measurement noise are studied.

Identification of the optimum location and capacity of Static Synchronous Compensator (STATCOM) in power grids has been given much attention to maximize its technical performance while minimizing operational cost. In this regard, a new multi-objective optimization model that minimizes power loss, enhances system stability and reduces operational cost of STATCOMs is presented in this paper. To overcome the issue of the harmony search (HS) optimization algorithm in solving high-dimensional multi-objective optimization problem, an improved differential evolution harmony search (DEHS) algorithm is proposed. In this algorithm, mutation and crossover operations are adopted instead of the original pitch adjustment operation adopted in the HS optimization algorithm, which enhances the algorithm global search ability. Moreover, opposition-based learning technique is incorporated to the process to broaden the diversity of variables and hence improving the search efficiency of the algorithm. The proposed algorithm is employed to identify the optimal allocation and sizing of multiple STATCOMs within the IEEE 30-bus system. Results reveal the superiority of the proposed optimization algorithm over the conventional multi-objectives adaptive harmony search algorithm.

Suspended submarine cables are prone to likely mechanical damages due to ship anchors, which represent a significant threat to the reliability of power transmission and information communication networks. This paper is aimed at presenting a detailed investigation to the dynamic response of a ship anchor impacting the suspended section a submarine cable in order to reduce the risk of cable damage. In this regard, a three-dimensional and dual nonlinear model of the anchor affecting a subsea cable is established using ABAQUS finite element analysis software. The damage effect due to the ship anchor on the suspended and buried-in-soil sections of the cable is studied. Results show that when a ship anchor hits a suspended section of the subsea cable, the mechanical stress is concentrated at the impacted point and is progressing to both sides of the suspended section with a significant cable deformation. On the other hand, the buried section of the cable suffers from a short impact process, and the deformation is relatively small. To reduce this impact effectively, a detailed technical comparison of two common dumping and filling methods is conducted, and the better protection method is proposed.

As an emerging and active entity in China’s electricity market, electricity selling companies call for a more reliable operational mechanism and new consumption mode to broaden their profit margins. Aiming at distributed power generation-based sales companies and by considering the participation of virtual power plants (VPPs), this paper presents the relevant operating systems in the Chinese power market. Then the paper proposes a new platform for power transactions and optimal dispatch based on a master-slave game optimization model. The model is built so that the main gamer, power sales company, can achieve maximum profit while at the same time the secondary gamer, represented by the VPP attains the lowest internal dispatching cost. The energy of both parties is linked together, and the two parties continuously exchange their own strategies and optimize the operational decisions and scheduling plans iteratively. The results of the investigated case study reveal the benefits to retail electricity companies from adopting the proposed model to aggregate and manage decentralized resources, and optimize decision-making. The platform facilitates the use of controllable loads and distributed energy sources to participate in market transactions on a large scale, and optimize the operational strategies of electric utilities.

It is a challenge to the stable operation of the active distribution network (ADN) with the distributed generation (DG) and electric vehicle (EV), and the reconfiguration is an important method to improve the stability of the system. The multi‐objective reconfiguration model is established under the battery‐swapping mode, the network loss and the voltage deviation index (VDI) are set up as the optimisation functions, and the number of switching operations is considered as the constraint. The global optimal position is updated through the niche technique; the optimal compromise solution is chose from the Pareto solutions using the fuzzy satisfaction evaluation decision method. Finally, the effects of different scenarios on the target value and the voltage of each node are compared and analysed from the simulation results in IEEE69 nodes system. The results show that the proposed method can effectively improve the stability of the system.