The condition monitoring and fault diagnosis method based on decomposed component analysis (DCA) for SF₆ gas-insulated equipment, which mainly aiming at AC SF₆ gas-insulated equipment, has become a research hotspot. Therefore, SF₆ positive DC partial discharge (PD) decomposition experiments under four typical insulation defects were conducted in this work. The result showed that there is a significant correlation between the generation rules of the five SF₆ decomposition components (CF₄, CO₂, SO₂F₂, SOF₂ and SO₂) and the types of defects. The phenomenon was attributed to the variations in the properties of the four insulation defects. In addition, comparing with AC PD experiment, for the protrusion, contamination and gap defect models, the amounts and generation rates of the five characteristic decomposition components under positive DC are less than those under AC by the same defect; however, for the particles defect, it is by contrary. This could be attributed to the essential difference between AC PD and positive DC PD. Therefore, the theory of AC DCA could provide reference to construct DCA diagnostic model for DC SF₆ gas-insulated equipment, but cannot be applied mechanically.

This study proposes a multi-stage expansion model for coordinated transmission and generation of expansion planning of a multi-area power system (MAPS) wherein each region seeks to benefit from the changes. The proposed model adopts a bi-level optimisation approach. In the first level, the expansion cost and carbon emissions are calculated for each region separately for expansion planning. In the second level of optimisation, the calculated cost and emission values are used as the upper limits for the cost of expansion and emissions of the regions in multi-area expansion planning. The proposed bi-level approach prevents one region from bearing additional expansion costs without compensatory benefits and provides advantageous collaboration for the participant regions in the MAPS expansion. The proposed linear model requires fewer computational expansion models for long-term planning of the MAPS, but takes the uncertain generation of renewable units into account.

As large-scale integration of wind systems into the power grid is on the rise, advanced control techniques for wind power generators are highly desired. This paper proposes a simple but effective control technique for doubly fed induction generators (DFIGs) based on the multi-objective model predictive control (MOMPC) scheme. The future behaviors of the DFIGs are predicted by using the system model and the possible converter switching states. The most appropriate vector is then determined by a cost function. By properly modifying the cost function with active and reactive powers as the control objectives, fast grid synchronisation, smooth grid connection, flexible power regulation and maximum power point tracking (MPPT) can be achieved, respectively. In order to reduce the switching frequency for switching loss reduction, a nonlinear constraint is integrated into the cost function. The controller is simple without using any Proportion Integration (PI) regulators, current loops, and switching tables. A numerical simulation of a 2MW system based on MATLAB/Simulink is built to verify the effectiveness of the proposed method. The results show that the proposed method can achieve quicker transient response, better steady-state performance, and lower switching frequency compared to the conventional switching table based direct power control (DPC).

Complex network theory is introduced to solve the islanding problem in an emergency of distribution networks. In this study, the authors put forward an intentional islanding method based on community detection. In this method, a new index has been defined called electrical edge betweenness, on the strength of edge betweenness in complex networks, which fuses electrical characteristics with topological features of actual power lines. Based on the index, the Girvan–Newman algorithm is employed to detect the community structure of distribution networks. Through referring to the modularity value (function Q) and coherent generator groups, they can get a reasonable amount and regions of communities. Then the whole distribution network can be partitioned into several self-sustainable islands meeting the stable operation constraints. The effectiveness of the authors’ proposed method is tested on a standard IEEE 118-bus system.

This study aims to investigate the topology characteristic indices which have a close relationship with reliability of distribution networks via mathematical tools. First, a practical network is extracted into a topology and presented by weighted adjacency matrix associated with a failure degree matrix, which contains more significant information than that of original adjacency matrix. Second, singular value sequence and vertex/edge sharing are proposed as two similarity indices. Finally, similarity functions are applied on two cases to establish the relationship with reliability by curve fitting and clustering. optimisation strategy based on modified contingency-load-loss index is elaborated to improve the reliability and guide to distribution network planning.

Risk evaluation of wind-power-integrated power systems requires a distinctive wind speed modelling technique. Existing techniques of mid- and long-term risk assessment mainly focus on annual wind speed pattern rather than its monthly and daily patterns, which cannot reflect the time-varying characteristics of power system risk. This article proposes a time-periodic model of wind speed which incorporates two parts. The first part is the monthly wind speed patterns which can be represented as time-periodic functions, while the other one is the fluctuation in daily wind speeds that can be denoted as a random variable following a certain probability distribution. With this model, a risk evaluation procedure for wind-power-integrated power system is developed. Collected wind speed data from four representative sites in China are used to verify the proposed model. The application of the proposed wind model and risk assessment method is tested by calculating annual and monthly risk indices of a modified IEEE-RTS79 system. Results can provide references for power system planning, mid- and long-term dispatching, and monthly generation scheduling.

These main goals of the restoration in distribution networks are to reenergise loads in the area where the power outage occurs. In this study, a new multi-stage restoration process by the aid of the decision-making tree algorithm is proposed to maximise the restored loads and also to minimise switching operations in the distribution networks with distributed generations (DGs). This method includes three stages of initial restoration, reconfiguration and optimal load shedding. In order to reduce the search space, the network switches are categorised into different sets which avoid moving to any inappropriate result space. The simulations are carried out on the 69-bus distribution system and the results show the high capability and accuracy of the proposed method in the restoration of distribution networks.

This study establishes a multi-objective model for comprehensive energy system scheduling optimisation with wind farms, combined heat and power units, power to gas technology, circulating fluidised bed boilers and gas boilers. The goal is to minimise the operating costs and minimise the discharge of pollutants while meeting the constraints of the material balance of the circulating fluidised bed boiler. The improved weak robust optimisation theory is used to deal with the uncertainty of wind power, and the weak robust coefficient is introduced. By adjusting the coefficient, the optimal solution under the different tolerances of the deterioration of the objective function is obtained. The improved bacterial population chemotaxis algorithm is used to optimise the comprehensive energy system scheduling model, and a feasible solution with certain robustness is obtained. Sensitivity analysis under different risk levels is done. The simulation verifies the correctness and effectiveness of the optimised scheduling model and the improved algorithm.

Today, with the restructuring of the power systems, it is possible to implement a program, such as the demand response for the harmonic issues, and use customers to reduce the harmonic level of the network. In this study, a new method is presented based on harmonic pricing to control the harmonic level of the network. Given the fact that the power system is usually infected by the background harmonics, the basis for pricing is the harmonic contribution determination in order to impose a fine fair on the customers. Usually, the determination of the harmonic contribution at each harmonic order is done separately; therefore, a new index is presented, to sum up, the dominant orders in determining the harmonic contribution. This can provide an appropriate impression of the harmonic emission level at the point of common coupling. Simulation results on the standard IEEE 14-bus network show that customers are encouraged to control their harmonic level with a fair harmonic pricing, otherwise, the independent system operator can install harmonic filters at appropriate buses, using the fines received from the customers.

The hybrid AC/DC microgrid with different types of distributed generations (DGs) and load demands is considered to be the preferred microgrid mode in the future. For hybrid AC/DC microgrid, autonomous and bidirectional power flow between AC and DC subgrids with superior dynamic performance is the fundamental objective to realise proportional power sharing and robust operation. In this study, an improved active power control strategy of the bidirectional AC/DC main converter (BMC) based on virtual synchronisation machine (VSM) for inertia improvement of the AC bus frequency and DC bus voltage of the hybrid microgrid is proposed. The VSM control is derived through the virtual inertia equation and the virtual capacitance equation, which can manage the AC frequency and DC voltage simultaneously. Then, the small signal and large signal characteristics analysis of the BMC are conducted to analyse the VSM control feature with different control parameters. On the basis of the small signal analysis, a proportional power sharing principle to select the control parameters is given to make DGs share the power commensurate with their power ratings. Finally, simulation cases are carried out to show the validity and efficiency of the proposed control strategy.

Spinning reserve (SR) serves as an efficient tool to respond to a sudden outage of power system components caused by either natural events or physical attacks. Contrary to natural threats, the intelligent physical attacks are strongly influenced by the measures taken by the system operator to defend the system and exhibit no stochastic behaviour. As a consequence, the probabilistic methods of SR provision and allocation do not prove to be appropriate to confront intelligent attacks. In this study, the interaction between the system operator as the defender and the intelligent attacker is investigated within a game model. In this model, the SR is allocated in such a way that the highest interruption cost that the attacker can impose is minimised. The technical limitations of SR provision together with operational constraints are taken into consideration. The efficacy of the proposed method is examined by conducting case studies of single and multiple-target attacks on components of IEEE 24-bus and IEEE 118-bus test systems. The results show that the proposed scheme produces a considerable reduction in the system interruption cost in comparison with the probabilistic methods.

For intelligent power utilisation of demand side management, the implementation of non-intrusive load identification is an important technology. This study proposed an event-based non-intrusive load identification algorithm for residential loads combined with underdetermined decomposition and characteristic filtering. This method first needs to monitor the circuit in real time. After detecting an electrical switching event, the load decomposition and identification are performed. By combining the operating habits of the electrical equipment, the problem that the single current signal is difficult to solve by multi-dimensional under-determination is optimised as a one-dimensional under-determination problem. The objective function is established based on the sparsity of current in the frequency domain. The two-step iterative shrinkage threshold algorithm is used to get the optimal solution to achieve load decomposition. Then, according to the unique harmonic components of each power load, this study establishes the characteristic filtering to filter the decomposition current, which realises load recognition. The algorithm is verified by actual data measured in a household. It can obtain the individual load current and accurately judge the load status, which proves the accuracy and effectiveness of the algorithm.

In the long-term transmission system hardening, critical components in transmission infrastructure should be identified and hardened to reduce the load loss risk in the presence of scheduled and unscheduled outages. Generally, the probabilistic information of assets in power systems can be evaluated via historical statistics. On the basis of the prior probabilistic information, this study proposed a tri-level optimisation model to deal with the problem of long-term transmission system hardening, in which the risk assessment is taken into account in the objective function. Furthermore, the problem is formulated as a two-stage robust optimisation model. To address the non-linear problem in the inner model, logarithmic transformation and piecewise linearisation are utilised to exactly linearise the non-linear terms in the model. Finally, the standard column-and-constraints generation algorithm is employed to solve the proposed model with a master–sub-problem framework. The test results on a standard IEEE RTS-96 system show the effectiveness of the proposed model.

Voltage dips/sags are one of the major concerns for electricity consumers as well as utility service providers. Therefore, the characterisation of voltage dips/sags is required. This study presents a set of mathematical expressions for characterising different types of voltage dips/sags and their associated phase-angle jumps, which are typically found due to faults and/or disturbances in electricity networks. The expressions are derived analytically from the model of the power network containing generators, transmission and/or distribution lines, transformers etc. Four types of voltage dips, namely, A, B, E, and G, which are associated with four major types of faults including balanced three-phase faults, single line-to-ground, double line-to-ground, and line-to-line faults, are considered to derive the analytical expressions. Dynamic simulation results, using a test distribution system, approve the validity as well as the accuracy of the developed expressions. The influence of fault-types and fault-locations is investigated from the mathematical expressions; further, validation is conducted through a simulation study. The analytical expressions, presented in this study, are a valuable tool in the planning stage since the expressions can be employed to characterise during-fault voltage dips at different buses in electricity network without conducting a large number of repeated dynamic simulations.

In this study, the post-disturbance coherency of buses is added to the conventional phasor measurement unit (PMU) placement problem to find the minimum number of PMUs at different depths of unobservability. To do that, different scenarios are defined based on probabilistic parameters. Then, in each scenario, central buses are determined based on the similarity of post-disturbance variations using subtractive clustering algorithm. The central bus in each area is the bus that its post-disturbance variations are similar to the highest number of buses in the area. The PMU placement problem is then solved considering the number of scenarios where each bus has been selected as a central bus. The resulted placement scheme is more suitable for monitoring the power system dynamics compared to the conventional method. In order to reduce the number of PMUs, the placement problem is solved for higher depths of unobservability. In each depth, the voltage phasor of unobservable buses is obtained using state estimation methods. The results of applying the proposed methodology on 68-bus, 16-machine system show its better performance compared to the conventional method.

The introduction of renewable generation to South Africa's grid has introduced challenges to the management and regulation of power quality (PQ). These have been addressed by establishing PQ compliance criteria in line with local circumstances and by the introduction of a Power Quality Guideline for renewable power plants (RPPs). A key challenge to RPPs has been meeting emission limits for harmonics. This has been addressed in South Africa's RPP Guideline by the development and introduction of a Group Harmonic Distortion limit which provides some flexibility to RPPs in making individual harmonic emission limits. The use of 95th percentile harmonic impedance envelopes is discussed and recommendations for impedance envelopes are made for different voltage levels within the South African Grid, based on actual network data. A lesson learnt is that using international standards and guidelines provides a starting point for compliance rules when introducing renewable generation. Developing countries that share economic and electricity network characteristics with South Africa should tailor the PQ rules and guidelines for RPPs to meet local conditions.