In the planning and operation of power systems, actions are taken in different processes and time-horizons. The purpose of these actions is to secure a high reliability level. Although the three main processes (grid development, asset management, and system operation) are described in literature, there has been no explicit study on the time-horizons (long-term, mid-term, and short-term) and actual time-scale (decades, years, months, etc.) that these processes focus on. This study aims at making a review of the various activities performed by transmission system operators while reviewing the concept of each time-horizon and methodologies developed in literature. As decisions taken in different time-horizons can influence each other, the interactions and overlapping are discussed.

With increased penetration of energy storage system in micro-grids, rapid and standardised information exchange is becoming essential for secure and reliable operation of energy storage system. This study presents an extensional information model for battery energy storage system (BESS) in micro-grid, which is based on the communication standards of the International Electrotechnical Commission (IEC) 61850. The implementation framework for BESS operation based on the extensional information model is proposed in detail; and the actual BESS operation tests are performed through an intelligent electronic device and a micro-grid test system. The experimental results show that the proposed BESS extensional information model and the implementation framework for BESS operation are available, which demonstrates an effective solution for flexible operation of BESS.

The hydrothermal scheduling (HTS) is formulated as a stochastic multiobjective short term HTS problem by considering stochastic production cost, NO _x emission, SO₂ emission and CO₂ emission curves for thermal generation plants and uncertainty in load demand. This study presents, a non-dominated sorting gravitational search algorithm integrated with disruption operator (NSGSA-D) to solve this problem. In this approach, a set of Pareto optimal solutions are obtained by adopting the concept of non-dominated sorting. Further, an elite external archive is introduced to keep the Pareto optimal solutions and guide the search process. In addition, a disruption operator is utilised to intensify the search process and also speed up the convergence of the solutions. Furthermore, the most suitable and efficient solution from the non-dominated solution set is obtained with the help of fuzzy decision making policy. The effectiveness of NSGSA-D approach is demonstrated on three sample test systems and simulation results thus obtained are compared with the results reported in literature. The obtained results affirm that the NSGSA-D approach yields good quality solutions and competitive performance for solving stochastic multiobjective short term HTS, while handling the diverse constraints of the problem effectively.

To efficiently detect non-technical loss and power blackout in micro-distribution systems, this study proposes using a cooperative game (CG) based inference mechanism under the advanced metering infrastructure technique. Fractional-order Sprott system is designed to extract specific features between the profiled usages and the measurement usages in real time analysis. The fractional-order dynamic errors are positive correlated with the changes in load usages, including normal conditions, electricity fraudulent events, and power blackout events. Then, multiple agents in a game and multiple CG based inference mechanisms are used to locate abnormalities in micro-distribution systems. For energy management applications, the proposed inference mechanism can identify the 2.5–20% irregular usages during normal demand operations. In addition, it can also identify the large changes >20% in usages, while a micro-distribution system is disconnected to operate in the islanded mode within a few hours. This function can address an outage occurrence and then quickly resume service using the service restoration strategy and distributed generations in a local grid. Using a medium-scale micro-distribution system, computer simulations are conducted to show the effectiveness of the proposed inference model.

In this study, the spark discharge risks on small relays in low-voltage circuits are evaluated based on the test current magnitude and the rate of current change of surge current. For the risk assessment of spark discharge caused by the high-voltage switching surge on the small relay in low-voltage circuits, there are fewer papers relevant to the topic. First of all, this study presents the construction of a test circuit model, in which the open contacts of small relays are energised by a set of spark discharge generators. The actual current waveforms are measured and analysed. This study provides a manner to evaluate the risk degree of the small relay in low-voltage circuits damaged by the surge current. Referring to the relevant IEEE standards concerning surge protection, a surge protection circuit of a signal line is applied. The test is done after installing this surge protection circuit, the test of spark discharge is done after installing this surge protection circuit, and the test result confirms that the use of surge protection devices can suppress the surge current, so this study can be applied to reduce the hazards of the low-voltage equipment.

Security constrained optimal power flow (SCOPF) is a key operation function for today's power systems, extensively used, for example, in the dispatching centres. However, SCOPF is a complex optimisation problem for large practical power systems, mostly due to its highly non-convex nature. This study aims at changing highly non-convex SCOPF problem to a convex one. In this way, SCOPF can be solved with much less computation burden and more optimal solutions can be obtained for it by means of commercial solvers. For this purpose, the non-convex terms of SCOPF model (for instance, the terms associated with the valve loading effects of units and AC network modelling) are first reformulated using Signomial functions based on Taylor series. Then, the Signomial SCOPF formulation becomes convex by means of power transformation techniques. The constructed convex SCOPF formulation can be easily solved to obtain its optimal solution. The proposed solution approach is tested on well-known IEEE 30-bus, 118-bus, 300-bus and the polish 2746-bus test systems and its obtained results are compared with the results of several other SCOPF solution methods and published literature figures.

The integration of stochastic wind power has accentuated a challenge for power system stability assessment. Since the power system is a time-variant system under wind generation fluctuations, pure time-domain simulations are difficult to provide real-time stability assessment. As a result, the worst-case scenario is simulated to give a very conservative assessment of system transient stability. In this study, a probabilistic contingency analysis through a stability measure method is proposed to provide a less conservative contingency analysis which covers 5-min wind fluctuations and a successive fault. This probabilistic approach would estimate the transfer limit of a critical line for a given fault with stochastic wind generation and active control devices in a multi-machine system. This approach achieves a lower computation cost and improved accuracy using a new stability measure and polynomial interpolation, and is feasible for online contingency analysis.

An advanced combined co-phase traction power supply system is proposed by combining a single-phase traction transformer and an active power flow controller (PFC) in an electrified railway. In the new system, the power quality problems caused by single-phase traction load are solved in the grid side and continuous power can be provided to electric trains without neutral sections in the traction side. The mathematic model of the new system is built by power transformation analysis. The compensation currents of the PFC are calculated based on the power balance principle. According to the power quality standard in China, the optimised partial compensation algorithm is presented to replace the existing full compensation one. Moreover, the capacity of the PFC adopting the proposed algorithm is much less than those in the previous studies with the same outcome. The validity of the compensation algorithm and the control method are demonstrated by the simulation results and the effectiveness of the proposed system is verified by the case studies.

This study presents a mixed-integer second-order conic programming (MISOCP) model for the robust reconfiguration of electrical distribution systems, considering the minimisation of active power losses and reliability constraints. The uncertainty at the reliability data is considered by using a linear and adjustable robust approach. The indices used to evaluate the reliability of the system are the system average interruption frequency index (SAIFI) and the system average interruption duration index (SAIDI), both of which are calculated as functions of the switch status (open or closed). Under radiality constraints, the solution generated by the proposed model is robust in terms of the reliability, i.e. the SADI and SAIFI limits imposed by regulators are not violated even if the uncertain data changes stochastically. The use of an MISOCP model guarantees convergence to optimality by using existing convex optimisation solvers. To evaluate the robustness of each solution generated by the proposed model, a set of Monte Carlo simulations were deployed. Finally, all tests were executed in a 136-node real distribution system.

One of the major challenges in reliability evaluation of smart grid is the direct cyber-power interdependencies (DCPIs) impacts. The less effort has been devoted in the literature to investigate the DCPIs impacts, particularly in stochastic simulating space. This study proposed a novel methodology to determine the risk assessment of smart grid due to DCPIs under various distributed generation (DG) technology scenarios. The presented method is applied to a realistic distribution grid. The several sensitivity studies are performed to investigate the pattern of DCPIs impacts as DG penetration level in various scenarios. The test results show that regardless of the DG technology scenario, the DCPIs impacts gradually increase while the DG penetration increases, and it saturates when the penetration exceeds a certain level. The numerical result implies that the scenarios having more effective performance from the reliability improvement perspective such as those consist of dispatchable DG units such as microturbine are more affected due to DCPIs.

This study presents the mathematical modelling and control design methodology of bidirectional quasi-Z-source inverters (qZSIs) for interlinking converter application in hybrid AC–DC microgrids. The proposed control scheme provides the maximum constant boost (MCB) control capability for the qZSI in both grid-connected and islanded modes of operation even in the presence of unbalanced AC loads. The proposed approach maintains the MCB without any additional control loop for regulating the voltage of the DC-side capacitor of the qZSI. This is done by determining the shoot through duty cycle of the qZSI based on the inverter modulation index. Moreover, maintaining the MCB condition, the proposed control scheme provides a high stability margin for the qZSI network. The effectiveness of the proposed method is demonstrated through simulation studies conducted on a typical AC–DC hybrid microgrid in MATLAB/Simulink environment for both islanded and grid-connected modes of operation.

In China, subsynchronous oscillation (SSO) appears continually at the Hulun Buir (HB) power plant, which is part of the extra-high-voltage (EHV) AC and DC hybrid transmission networks from the HB League power base to the Northeast. Related closely to the power delivered by the EHVDC link, these oscillations lead to fatigue accumulation, life-time reductions and even failures in the turbogenerators at the HB power plant. After a study of the oscillations, an inverse energy injection method is proposed to suppress the SSO phenomenon. According to the method, a bulk power electronic device is developed that is based on a multilevel voltage source converter to generate inverse energy. The mitigation device is implemented at the HB power plant. Field tests are conducted, and the results demonstrate that the device can depress SSO to levels that exceed the requirements, proving the effectiveness of the mitigation device.

This study presents a coupled electric–magnetic–thermal–mechanical analysis of busbar systems under short-circuit currents. The analysis is carried out by making use of the finite-element method, which enables one to closely model two-way interactions among separate continuum physics. In contrast to previous works, which only consider the peak value of the short-circuit current, this method evaluates the magnetic force, the temperature rise, the mechanical displacement and their interactions over the simulation time of interest. The mechanical displacements are obtained by means of a three-dimensional analysis. It is found that the type of busbar support can markedly affect the conductor displacement during the short-circuit current. The temperature rise due to the short-circuit current flows is found to have a slight effect on the displacement of busbar conductors.

Model predictive control (MPC), that can consider system constraints, is one of the most advanced control technology used nowadays. In power systems, MPC is applied in a way that an optimal control sequence is given every step by an online MPC controller. The main drawback is that the control law cannot be evaluated before the MPC controller is put into service. Therefore, system operators may not validate its performances in advance. To overcome this drawback, the explicit MPC (EMPC) method is introduced and applied to obtain an explicit control law. In addition, another major contribution is that an improved partition algorithm of EMPC is studied which enables the EMPC method to be extended to a system of large number of state variables and more constraints. A simple single generator single load case is used to illustrate the whole procedure of EMPC and then the EMPC is applied to an actual isolated power system for frequency control. Simulation results show that the explicit control law of EMPC is able to restore system frequency to its nominal value under large disturbance. Moreover, the physical meaning of the explicit control law given by EMPC can be clearly explained for the studied system.

The optimisation of unit commitment (UC) problem in the daily operation and planning of the power system may save the electric utilities millions of dollars per year in production costs. Though many works in the literature uses evolutionary techniques to solve the pre-dispatch of thermal power generating units, search for optimal generation schedules in order to minimise total operating cost is still an interesting research task. In viewpoint of this, a new population-based bio-inspired algorithm namely grey wolf optimisation (GWO) has been implemented to solve thermal generation scheduling problem and the core objectives such as minimisations of total operating cost, emission level and maximisation of reliability are optimised subject to various prevailing constraints. Additionally, real coding scheme is adopted in order to handle the constraints effectively. The effectiveness of real coded GWO (RCGWO) has been verified on standard 10, 20, 40, 60, 80 and 100 unit systems. Further, a practical 38-unit system has been utilised to show the feasibility of the RCGWO. The simulation results show that RCGWO is very competent in solving the UC problem in comparison to the state-of-the-art methods.

This paper describes the assessment of the resistance to tracking of various polymers after (i) flashover voltage (FOV) and flashover gradient (FOG); and (ii) partial discharges (PDs) measurements in dry, clean and salt fogs on one insulator model using standardised electrodes; the aim being the development of optimised methods based on flashover and PDs to the conception of new generation of piercing connectors. The investigated materials belong to two distinct classes widely used in the electrical industry: thermoplastics (namely polyphenylene sulfide and high density polyethylene) and thermosetting cycloaliphatic epoxy resins namely one unfilled material (UnCEP) and another unfilled and hydrophobic resin (UnHCEP). FOV measurements are based on the electro-geometrical parameters of each specimen and the resistance to tracking, both may be assessed through the slope of FOV curves against the leakage distance as an indicator of surface damages. Regarding PDs, the suggested technique is devoted to clean and salt fogs and provides quicker and more accurate information about PDs effects on materials deteriorations rather than IEC60109 where the exposition time to discharges is much longer at lower voltage levels by using only liquid contaminants such as sulfuric or nitric acids or ammonium chloride as described in IEC60587 or ASTM D2303.

This study emphasises on a new comprehensive approach for generating the reference compensator currents for distribution static compensator (DSTATCOM) under unbalanced and distorted source and load conditions. A shunt connected DSTATCOM is configured using a three level neutral point clamped inverter topology to achieve load compensation. The behaviour of shunt compensator is analysed using synchronous detection method (SDM) and its different approaches. To overcome the drawbacks of SDM, improved equal current (IEC) SDM with the extraction of fundamental positive sequence component is proposed. Moreover, the performance of the proposed algorithm is compared with the most robust and widely accepted instantaneous reactive power theory. The proposed control algorithm works more effectively under magnitude and phase unbalance as well as distorted source conditions. The detail simulation and experimental results are presented to validate the superiority of the proposed method.

One of the most significant tasks for loss reduction and reliability improvement in active distribution networks is feeder reconfiguration. Uncertainty associated with load, generation and reliability parameters in active distribution network requires distribution system operators (DSOs) to consider risk management in distribution network reconfiguration. On the other hand, by employing several forms of reward/penalty schemes in active distribution networks, DSOs have been exposed to financial risk for providing reliable service to the customers. In such circumstance, DSOs can do network reconfiguration in a way that the minimum cost can be spent in the minimum risk. This study presents risk-based reconfiguration of electric distribution networks in presence of reward/penalty scheme with considering load and generation uncertainty. Scenario theory and particle swarm optimisation are used for risk modelling and optimisation problem solving, respectively. To verify the proposed method, it was implemented in a real distribution network.

Lightning surge analysis of protective structures is significant for the design of system. However, simulation models are limited. In this study, a Faraday cage with four air terminals and 2 × 6 grounding rods built to protect a switchyard control building in a 380 kV substation is simulated in alternative transient program for the analysis of lightning surges. Distributed line modelling is used for cage conductors. Down conductors are represented by considering non-uniform variation of the conductor parameters. Current waveforms through the system and voltages at some critical points after a lightning stroke are computed. The traditional lightning parameters needed in structural protection such as lightning peak current, maximum current derivative, current rise time and current duration are determined. The effects of mesh size and some system parameters such as grounding resistance and lightning surge impedance are investigated.

A multivariate statistical analysis (MSA)-based power-grid-partitioning method is proposed. Considering the effectiveness of automatic voltage regulation of generators, network modelling is based on the quasi-steady-state sensitivity of voltage with respect to reactive power. The MSA-based power-grid-partitioning method contains two stages: a quantitative method for determining the appropriate number of zones and allocation of nodes into a number of zones. The proposed method is applied to an automatic voltage control system and an N − 1 robust pilot node selection method is presented. Simulation studies on IEEE 14-bus, 39-bus systems and a real provincial power system in China are described to illustrate the effectiveness of the proposed method.

Commutation failure immunity index (CFII) is a useful indicator to quantify the immunity level to commutation failures in line commutated converter-based multi-infeed HVDC systems. Instead of using simulation tools which inevitably lead to heavy workload and long computation time, the analytical expressions of ‘local CFII’ (LCFII) and ‘concurrent CFII’ (CCFII) are derived based on the minimum extinction angle criteria. Using these expressions, the impact of the system parameters on commutation failure immunity levels in the inverter side can be determined quickly and effectively. Moreover, the derived analytical expressions will make the parametric sensitivity analysis more comprehensive and complete compared to the traditional simulation-based methods. Furthermore, in order to give an insight into how inter-inverter interactions influence the concurrent commutation failure behaviours, an improved index ‘weak coupling multi-infeed interaction factor’ (WCMIIF) is proposed. The validity and accuracy of the proposed index and analytical expressions are verified by the simulated results based on a dual-infeed HVDC system in PSCAD/EMTDC, which indicate that LCFII has an approximately linear correlation with the local effective short-circuit ratio (ESCR) of the faulted ac system, and that with the WCMIIF unchanged, CCFII has an approximately linear correlation with the local ESCR and an inverse correlation with the multi-infeed interaction factor.

This study proposes a novel islanding detection method adopting single-phase-operating circuit breaker (CB). The method aims to utilise the operation of CB to generate specific electric information to the distributed generator (DG), instead of using a dedicated signal generator at the substation. When islanding forms, the CB opens three-phase circuits asymmetrically to indicate the islanding, which causes asymmetric operation of the local system within a predefined short time. During this period, negative-sequence voltage with certain duration is obtained at DG side. Furthermore, the varying characteristics of three-phase voltages from close status to open status of CB are the same, which can be utilised to distinguish the formation of islanding from system disturbances. The method is tested based on a typical medium-voltage distribution network with synchronous DG interconnection. Test results show the effectiveness of the proposed method under both islanding formation and system disturbance scenarios.

In this study, a three-phase power flow solution method using graph theory, injection current, and sparse matrix techniques for large-scale unbalanced distribution networks is proposed. In the bus frame of reference, a direct iterative method is adopted. To integrate the electric characteristics of transformers and step voltage regulators into the proposed method, the existing component models are modified by equivalent injected currents. To validate the performance and effectiveness of the proposed method, four three-phase IEEE test systems and random test systems are used for comparison purposes. As the size of the network increases, the proposed direct Z _BUS method drastically shows its superiority over the other methods. The results reveal that the proposed method has good potential for improving the computational efficiency of optimal planning and design as well as real-time power dispatch applications in large-scale distribution systems.

A new method to analyze the stability of power system with multiple operating conditions considering the stochastic characteristic of wind speed is proposed in this study. First, the parameter Weibull model is used to do fitting prediction of the wind speed variation trend in the short term. Second, the wind speed is divided into different intervals, and the probability density matrix of the conditional featured wind speed in each interval is calculated. Then, the system operating conditions are determined according to the conditional featured wind speed. On this basis, the continuous Markov power system model with multiple operating conditions considering the stochastic characteristic of wind speed is established, and the Lyapunov functional containing the continuous Markov power system model is constructed. Then, by applying the Dynkin Lemma to the weak infinitesimal operators of the functional, the robust stochastic stability linear matrix inequality (LMI) which satisfies the disturbance attenuation degree is derived. Finally, transform the robust stochastic stability LMI to the feasibility problem, so that the stability of power system could be identified. Time-domain simulation tests verify that the proposed method could identify the stability of power system with multiple operating conditions quickly and efficiently.

This study proposes an intelligent traveling-wave (TW)-based protection algorithm for parallel transmission lines. In the proposed algorithm, Karenbauer's phase to modal transform is applied on three phase current signals. Teager energy operator is then applied on the modal components to extract TWs. First extracted TW of each modal component along with well-designed fuzzy systems are used for internal fault identification and fault type classification. In order to find the fault location, the time difference between the first and the second TWs and the TW propagation speed are utilised. Test signals are generated in PSCAD/EMTDC software and the algorithm is implemented in MATLAB. Results show that the proposed algorithm is an ultra-high-speed algorithm for the reliable protection of parallel transmission lines.

This study presents a method to consider the probabilistic nature of load impedance and harmonic currents by converting the conventional inductive–capacitive (LC) compensator into a multi-step type consisting of switchable units thus assuming that a single unit is not sufficient to ensure satisfactory results. The compensator steps are optimised based on economic criteria; minimising cost and maximising saving; in addition to cost-constrained performance criteria; maximising the power factor, minimising the transmission loss or minimising the voltage total harmonic distortion. The compensator values which would create resonance are constrained. Also the manufacturer's standard values for power shunt capacitors are considered. Genetic algorithm (GA) is used in the optimisation process plus numerical iterative method. GA is a search mechanism based on the principle of natural selection and population genetics. The contribution of the proposed procedure is demonstrated in examples taken from previous publications. Finally, simulated results show that the multi-step LC compensator provides a considerable improvement in the economics in case of probabilistic condition.

Internal turn-to-turn faults (TTF) are considered as a common cause of transformer failures. Such defects (especially minor TTFs) may result in minor changes in terminal currents/voltages as these are undetectable by conventional current and/or voltage-based methods. In this study, a simple, sensitive and robust method is proposed to identify the TTF locations in power transformers by using core flux based technique. In this approach, a few turns must be wrapped around the transformer core legs to sense and detect the related core flux. Passing asymmetrical flux through a transformer core leg (due to a TTF) induces different voltages in the related sensors, which are located at different places. Variation of the core flux in the corresponding sensors indicates the faulty phase and the TTF location on that phase as well. The proposed technique is verified by some simulations and experimental tests. The obtained results show that the proposed technique successfully (i) detects all the TTFs, (ii) identifies the faulty phase, and (iii) specifies the faulty region on the related phase. Although the proposed method requires a few search coils to be installed on the transformer core legs, installing these thin wires will not change the transformer design significantly.

Fast charging is a practical way for electric vehicles (EVs) to extend the driving range under current circumstance. The impact of high-power charging load on power grid should be considered. This study proposes an application of a hybrid energy storage system (HESS) in the fast charging station (FCS). Superconducting magnetic energy storage (SMES) and battery energy storage (BES) are included in HESS. Based on the quick response of SMES and the high energy density of BES, power magnitude and power change rate of FCS can be limited by compensation of HESS. A controller is designed to generate real-time power demand to HESS. As a part of the control strategy, the energy regulation control of SMES is highlighted. The regulation control is necessary for SMES to deal with energy imbalance in continuous operation; meanwhile it is beneficial for battery life. Finally, feasibility of this control strategy is verified by simulation.

Lead–acid battery is a storage technology that is widely used in photovoltaic (PV) systems. Battery charging and discharging profiles have a direct impact on the battery degradation and battery loss of life. This study presents a new 2-model iterative approach for explicit modelling of battery degradation in the optimal operation of PV systems. The proposed approach consists of two models: namely, economic model and degradation model which are solved iteratively to reach the optimal solution. The economic model is a linear programming optimisation problem that calculates the optimal hourly battery use profile based on an assumed value of the battery degradation cost. The degradation model, in turn, gives the battery degradation cost based on the battery use profile, temperature and battery characteristics. The models are solved iteratively to finally reach to the optimal battery use considering battery degradation. The proposed approach has been applied to a 4 kWp PV system and the performance of the proposed approach were evaluated. Applicability of the proposed approach in determining the optimal storage size and the economic battery life were also shown. Advantages and the capability of the proposed approach in considering PV generation and irradiation variations were also evaluated through seasonality analysis.

One of the significant impacts of the growing penetration of intermittent renewable energy sources is upon the frequency response of power system. Compared with the dispersive electric vehicle energy storage, electric vehicle battery swapping station (BSS), as an emerging form of storage, can provide a more reliable supplementary regulation service for frequency control. This study has proposed a new supplementary automatic generation control (AGC) strategy using controllable energy storage in BSSs, referred to as station-to-grid (S2G). A Monte–Carlo stochastic simulation method is utilised to estimate the equivalent controllable capacity (CC) of BSSs, and then the lumped S2G equivalent model subject to SOC limits and CC constrains is presented. A filter-based AGC coordinated strategy is used to allocate the regulation power between generators and BSSs. The proposed AGC strategy is validated in a two-area interconnected power system with significant load and wind power fluctuations. Comparison analysis demonstrates the availability of the proposed models and control methods.