Due to the widespread application of the wide area measurement system in power systems, it has become feasible to identify the transient stability of a power system on-line. A real-time transient stability identification method combining state-plane trajectory and relative kinetic energy is proposed. First, the correlation between the minimum value of the state-plane trajectory and the system stability is analysed in a single-machine infinite system. On this basis, the relationship between the concavity–convexity of the trajectory and the transient stability is discussed in detail. Second, the calculation of the transient energy is introduced to analyse the energy transformation and a sub-criterion is presented. The comprehensive application of trajectory characteristics and energy criteria can accurately determine the transient stability of all of the units, which is of great practical significance for accurately cutting off the unstable units when system faults occur. A simulation analysis with the IEEE New England 10-machine 39-bus system verified the correctness and effectiveness of the proposed method.

As wide-area measurements and control techniques are being developed and deployed for a more resilient power system; the modern power grid is strongly integrated with its communication network. By combining power systems with communication network simulator, co-simulation technique or platform enables the simulations of electric power systems in which communication network properties can be taken into account. In this study, a real-time hybrid simulation platform is proposed and implemented, which can be used to implement electromechanical transient real-time electric power simulation of a large-scale power system and emulate the measurement, control and communication process of wide-area power grids. Applications to study the phasor measurement unit measurement error and wide-area monitor and control are presented, which further illustrates the important role of this platform in power system simulation and analyses.

Due to non-ideal behaviours and switching characteristics, dc bias might be generated in the dual active bridge converters. It could be more serious in the high-frequency transformers because of small loop resistances. It could also restrict the range of operating flux density due to the threat of saturation. This study analyses the steady-state dc bias and divides it into two categories. Then an active flux-balancing control method is proposed to eliminate these dc biases. It uses separate proportional integral controls and adjusts duty ratios of both sides independently to achieve flux balance. A generalised average model is established to verify its dynamic performance and stability. Simulation and experimental verification on a laboratory prototype confirm the performance of this approach.

This paper presents a novel magnetically coupled dual switches three level dc–dc converter with high-voltage boost and reduced power device voltage stress ability. The topology can achieve high-voltage boost ability by using coupled inductor and low MOSFET voltage stress by using three-level idea. However, unlike other high step-up three level converters, its gain is increased by reducing turns ratio. The name inverse is used for representing the inverse proportion principle of the proposed converter. Aiming at existing leakage inductance, introduced diode and capacitor circuit not only absorbs the leakage energy but also further boosts the gain. In addition, the proposed converter only utilises one magnetic core. Operating principles and relevant theoretical analysis of the proposed converter are described. In order to verify the proposed converter's performance, the relevant experiment is performed.

This study extends the superposition method proposed by the Electric Power Research Institute to calculate electric field distribution on the ground near high voltage alternating current-high voltage direct current (HVAC-HVDC) shared tower transmission lines under ultra high voltage (UHV). Maximum electric field on the ground can be easily superposed by electric field when two circuits act separately, and when one circuit acts, thhe other circuit is regarded as ground wires. The ac field is calculated by method of images. The dc field is calculated by a finite element method (FEM). A precise time-domain FEM is used to calculate the hybrid electric field for comparison. Dispersion between results of superposition and time-domain FEM confirms that the superposition method is less time consuming and can satisfy engineering precision.

Permanent-magnet synchronous motor (PMSM) has obtained more attention, acquired more applications, and received great reputation due to its high torque density and simple structure. While exploiting its high torque capability, PMSM's control strategy faces great challenge at high overload scenario due to core-saturation effect. This study presents a detailed physical description and analysis on the effect of cross-coupling magnetic saturation in PMSM. Applying the conventional i _d = 0 control strategy on a 1.5 MW surface mounted permanent-magnet synchronous generator, this study discusses the cause and influence of cross-coupling effect, presents the unbalanced magnetic permeance between direct-(d-) and quadrature-(q-)axis magnetic circuit. Either d- or q-axis electromotive force (mmf) would generate both d- and q-axis flux, especially those induced by permanent magnets. Then a permeance-fixed finite-element analysis is applied to separate the influence between permanent magnets and armature current. Finally, this study proposes a revised maximum-torque-per-ampere trajectory for surface-PMSM at high overload situation.

A convolutional sequence to sequence non-intrusive load monitoring model is proposed in this study. Gated linear unit convolutional layers are used to extract information from the sequences of aggregate electricity consumption. Residual blocks are also introduced to refine the output of the neural network. The partially overlapped output sequences of the network are averaged to produce the final output of the model. The authors apply the proposed model to the reference energy disaggregation data set dataset and compare it with the convolutional sequence to point model in the literature. Results show that the proposed model is able to give satisfactory disaggregation performance for appliances with varied characteristics.

The magnetic flux leakage (MFL) detection of defect in tank floor is of great significance to ensure the safety of the tank. The existing methods for defect analysis are based on one-dimensional MFL signals, which lead to simple quantification or two-dimensional contour identification of defect. In this study, the characteristics of the three-dimensional (3D) MFL signals of the bottom of the tank floor have been analysed. The sensitivity and correspondence of the components of MFL signals to various types of edge of defect have been studied, along with the correlation between signal intensity and the defect depth. This study also proposed a defect imaging method based on 3D MFL signals. This method adopts the Prewitt operator to detect the defect edge. Then, a finite element method is used to establish the corresponding relationship between defect depth and signal intensity, to solve the depth of a real defect. The method proposed in this study can achieve the contour recognition and depth estimation of the defect accurately, and further realise defect imaging. The finite element simulations test has verified the feasibility of the proposed method.

In this study, the author considers an operation strategy of energy hubs for commercial buildings based on tiered temperature control, with the objective of balancing the operation cost and comfort level. A tiered temperature deviation penalty tariff is formulated to measure different levels of temperature deviation. Considering a set of uncertain factors, including photovoltaic output, load demand and outside temperature, this stochastic optimisation model can be converted into a mixed-integer linear program, solved by commercial optimisation solver, CPLEX. Numerical simulations verify the efficiency of the proposed operation strategy.

To ensure the photovoltaic (PV) system can still output maximum power under changing environmental conditions, a modified hill climbing algorithm is proposed. The algorithm uses a variable step-size strategy to reduce the steady-state oscillations and prevent operating point from diverging away from the maximum power point by introducing boundary conditions. To verify its effectiveness, the proposed algorithm is compared with the conventional and adaptive hill climbing method under the environmental condition of irradiance step change and gradual change. The simulation results show that the proposed algorithm can increase the dynamic response speed of the PV system by 75% under varying irradiance, and can achieve a steady-state tracking accuracy of 99.8%. Besides, the proposed algorithm only needs to embed several lines of additional programs in the conventional hill climbing maximum power point tracking (MPPT) control program and does not require additional hardware components, which reduces the cost of PV power generation.

For the thermal inertia of houses and buildings, air conditioning (AC) cluster shows the potential in load frequency control. In this study, the authors propose a complete control framework for friendly accepting ACs to participate in secondary frequency regulation service without causing discomfort. An aggregator is hired to continually estimate the regulation capacity of ACs cluster by a heuristic simulated search algorithm, which could be guaranteed in a given duration. The external characteristics of the AC aggregations are set like a virtual power plant, which takes a droop curve for primary frequency control and a translation character for secondary frequency control. Simulation shows the capability for AC aggregations in load frequency control.

In recent years, China's renewable energy has developed rapidly. The installed capacity of wind power and photovoltaic power has ranked first in the world. While at the same time, China is also facing a serious problem of curtailment of wind and photovoltaic energy. In this study, the statistical characteristics of high-penetration renewable energy accommodation were analysed using power system operation simulation. The sensitivity of the bottleneck is quantified based on the operation simulation results. The contribution degrees of peak regulation and transmission capacity are analysed using the proposed metrics. Finally, the proposed methods are used to analyse the characteristics of renewable energy accommodation in a provincial power grid of China in the scenario of 2020.

In this study, small-signal stability issue associated with uncertainty excitation is investigated by using differential inclusion theory. Specifically, a polytopic linear differential inclusion (PLDI) model for Energy Internet is developed, in which a modified non-sequence Monte Carlo method is introduced to identify a series of time-variant operation states. Additionally, a simplified small-signal model of renewable energy sources (RES) with virtual synchronous generator control is proposed, and the outputs of RES are modelled as time-varying elements in PLDI model to reflect the inner stochastic excitation in the linearised matrix. The stability criterion for the stochastic time-varying system is mathematically deduced based on convex hull Lyapunov function. Simulation demonstrates the benefits of the proposed model in describing system stochastic characteristics and reducing computational burden.

The armature rotating permanent magnet synchronous motor has different vibration characteristics from other motors, as its electromagnetic exciting force has little relation to the frequency component about pole. In this study, analytical method was used to calculate the magnetic field and the electromagnetic exciting force of the proposed motor. Characteristics of the spatial distribution of the exciting force were displayed. Also, the finite element (FE) method was employed to simulate the vibration of the motor stator and obtain its vibration characteristics. The relationship between the electromagnetic exciting force and vibration mode shapes was analysed. The spatial distribution of the electromagnetic force is not the only decisive factor for the vibration mode shapes. To obtain the actual motor vibration, the motor stator modal and spatial distribution of the exciting force must be considered comprehensively. The results of the analytical calculations regarding vibration shapes and frequencies were basically consistent with those of FE simulations, and the results of vibration frequencies were in line with those of vibration tests. In this way, the analysis process of frequency got verified.

In this study, the Statistical Product and Service Solutions software is applied to analyse the massive data of electric distribution companies. A comprehensive evaluation of grid development and production and operation of basic electric distribution companies is the key to a company's investment and development strategies. This study proposes a comprehensive evaluation index system for electric distribution companies. In the method, the weight of each index is calculated using the improved analytic hierarchy process based on the Delphi method. Then, according to the actual operation situation of each enterprise, the differential weight of various indices is constructed, and the comprehensive evaluation and score of differentiation for electric distribution companies are realised, which can be used for locating the weak line of the power grid of each enterprise and putting forward an investment strategy of the power grid. Through the demonstration application of 98 electric distribution companies in Shanxi Province of China, this method exhibits a promotion of value and accuracy in carrying out a comprehensive evaluation for electric distribution companies.

Electricity consumption data are collected more frequently by high-quality meters in smart grids. Therefore, the load data volume and length increase dramatically. On the other hand, for advanced market-based applications, e.g. demand response, load service entities hope to identify or classify users better. In this study, a trend-based load characterising approach is proposed. Firstly, the concept of the candlestick chart is utilised as an innovative tool for load description. In addition, electricity trend indexes, e.g. stochastic oscillator and moving average convergence/divergence, are introduced as parameters for load characterising. Secondly, the stacked auto-encoders are utilised to forecast the future load based on the input historical trend indexes. Case studies in Guangdong province demonstrate that the proposed trend-based method is more applicable than existing approaches both in physical significance and accuracy.

Based on the turbulence model, the volatility of real-time wind speed is discussed, which is composed of an average component and a fluctuant component. By deriving the probability density function of fluctuant wind speed and investigating the probability density curve, the authors decompose the fluctuant wind power into the steady fluctuation and peak fluctuation. According to the properties of steady fluctuation and peak fluctuation, the authors determine that the energy storage system applied into the real-time wind power fluctuation should be of the performance of high power density, high energy density and long cycle life. Through the comparative analysis on the energy storage performance, the battery and supercapacitor are proved to be suitable for regulating the steady and peak fluctuation, respectively. According to that task assignment, the energy storage performance of a battery–supercapacitor hybrid system is investigated. Based on the wind power decomposition, this study develops a new capacity configuration method for the hybrid system and gives an example analysis. By that method, the battery and supercapacitor in the hybrid system can be allocated proper energy and power capacity to balance the steady and peak fluctuation, respectively. Consequently, their energy storage merits can be fully utilised.

The industrial robot is typically actuated by a permanent magnet synchronous motor (PMSM). In manufacturing applications, the position control performance of the PMSM actuation systems will directly affect the efficiency and precision of the industrial robot. This study proposes a cascade control method to achieve accurate position profile-tracking for a field-bus industrial robot. The proposed method is a data-based method, which implies that only process data is directly used for the controller design without system model information. The cascade position controller optimisation problem is formulated using the collected data from the plant to be controlled. Then, a multiple degrees-of-freedom solution is designed to obtain the optimal control parameters for all actuation PMSM systems. The effectiveness and robustness of the proposed method are demonstrated using an experimental example implemented on the developed field-bus industrial robot.

Low-frequency oscillation is one of the major threats to power system security. Online analysis and control decision system for low-frequency oscillation is in urgent need. Natural oscillation and forced oscillation are two types of low-frequency oscillation. Different oscillation types need different treatment measures. Thus oscillation-type identification is an important part of the defense system. A new multi-criteria integrated method for identifying low-frequency oscillation type is proposed. It has multiple criteria and overcomes the shortcomings of the previous single-criterion method which has low accuracy. It chooses harmonic content, characteristic index of starting oscillation waveform, and the startup-stage intrinsic damping ratio together with noise response damping ratio as criteria. The flowchart of the method is provided. The effectiveness of the multi-criteria integrated method is verified by real-power grid simulation cases. The results show that the method can reliably distinguish the low-frequency oscillation type and is practical in the real-power system.