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Power networks, especially distribution networks, have been undergoing substantial changes since the application of new technologies. Technology development in the early part of the 21st century has opened up new horizons for automated, efficient and reliable power grids. New technologies, while enhancing the capability of the electrical networks and providing opportunities and innovative solutions to the challenges of future networks, can also cause drawbacks that should be investigated and taken into account. Distributed generation (DG) is one of the new technologies that improves the operation of power grids. Despite tangible benefits that integration of DG units brings to electrical grids, their notable impacts on protection systems of power networks raise many challenges and concerns on how a fault should be detected and isolated in active distribution networks. Many attempts have been made to investigate the downside of the interconnection of DG units and methods to mitigate their impacts have been proposed. This study reviews the impact of DG integration on protection systems addressed in other research works and recapitulates suggested methods provided by scholars. [ABSTRACT FROM AUTHOR]

This paper proposes a method to enhance the accuracy of power load forecasting by considering the variability in the impact of multi‐dimensional meteorological information on power load in diverse regions. The proposed method employs spatio‐temporal fusion (SF) of multi‐dimensional meteorological information and applies the Copula theory to analyze the non‐linear coupling of meteorological information from multiple stations with power load to achieve SF in the spatial dimension. To enhance the accuracy of load forecasting in the time dimension, this paper improves the core parameters of the variational mode decomposition (VMD) using the marine predators algorithm (MPA) and utilizes the weighted permutation entropy (WPE) to construct the MPA‐VMD fitness function for the adaptive decomposition of the load sequence. Moreover, this paper constructs input sets for the long short‐term memory model and the MPA‐LSSVM model by combining each component of the time dimension and each meteorological information of the spatial dimension to obtain the prediction results of each component. The prediction model corresponding to each component is selected according to the evaluation index and reconstructed to obtain the overall prediction results. The analysis results demonstrate that the proposed forecasting method outperforms the traditional forecasting method and effectively enhances the accuracy of power load forecasting. [ABSTRACT FROM AUTHOR]

Power transformers are vital to delivering energy in power grids and they bear considerable maintenance costs annually. One of the major issues for power transformers is the ageing of the insulation paper used in windings that affects the life of transformers significantly. Utilising an appropriate procedure for loading of transformers can reduce the ageing rate of insulation and can improve the life expectancy. Therefore, it is crucial to obtain the values for the ageing rate which are optimum and to prevent transformer fleet from accelerated ageing. Although techniques are available to calculate the ageing rate and loss of life of a single transformer, utilities looking into the transformer fleet ageing need a better tool to improve the ageing rate of all transformers together. The main contribution of this study is to provide a method for the transformer fleet ageing optimisation rather than single unit ageing approach. This study proposes a novel approach utilising different optimisation techniques that are capable of representing different factors in order to obtain an optimum ageing rate for a fleet of transformers. The optimum ageing rate can provide a technical tool for asset managers, utility engineers and owners for better power transformer fleet management. [ABSTRACT FROM AUTHOR]

Peak‐valley period partition of load curve is a key aspect of time‐of‐use (ToU) tariff to improve power load characteristics, such as shifting peak loads towards valley time periods. Fuzzy clustering algorithm is an effective and popular method commonly used to solve the peak‐valley period partition of load curves, but it still encounters the difficulty of dividing some data within the boundary regions of different time periods. Therefore, this paper presents a peak‐valley period partition and abnormal time correction scheme for ToU tariffs under typical daily load curves based on improved fuzzy C‐means (FCM) clustering algorithm. In order to improve the accuracy of peak‐valley period partition, modified fuzzy membership functions are proposed to improve the initialization of FCM clustering, and a loss function‐based method is presented for calculating the fuzzy parameters of those membership functions. To resolve the problem of abnormal time partitioning within the boundaries of different time periods, an abnormal time period recognition model and a correction model based on fuzzy subsethood are proposed to obtain the final corrected peak‐valley time period partitioning results. On the MATLAB R2020b platform, the effectiveness of the proposed method is verified through two real daily load curves with a time resolution of 5 min. [ABSTRACT FROM AUTHOR]

The integration of the renewable energy sources (RESs) into the power grid, drives a significant transformation in the conventional power generation landscape. This transition from traditional synchronous generators to inverter based RESs introduces unique challenges in maintaining the grid frequency stability due to the reduced system inertia. The inherent stochastic nature of the RES power generation, load demand, and grid inertia includes further complexity in the assessment of frequency stability. Existing studies have limitations, including neglecting the stochastic nature of RES generation and load demand fluctuations, relying on limited metrics, and lacking a comprehensive day‐to‐day assessment. To address these shortcomings of the existing approaches, this paper introduces a novel methodology for assessing frequency stability in power grids with high RES penetration. It proposes three indices for evaluating grid frequency sensitivity, resiliency, and permissibility amidst varying RES integration. Utilizing a stochastic approach, the study incorporates uncertainties in RES generation and load demand, offering a comprehensive framework for day‐to‐day frequency stability analysis. Additionally, it presents a systematic method to ascertain the necessary inertial support for maintaining desired frequency reliability in RES‐dominated grids. The effectiveness of these methodologies is validated through a case study on a modified IEEE 39‐bus test system, demonstrating their applicability in ensuring reliable grid operation under high RES scenarios. [ABSTRACT FROM AUTHOR]

With the development of the energy structure of the power system, the characterization of the observed oscillation in the power system has steadily evolved. With the increasingly high penetration of distributed energy sources and power electronic devices, such as the photovoltaic, wind power and charging pile, the basic mechanism, frequency ranges and propagation of oscillation would become more dynamic and complex. Therefore, the traditional parameter estimation, as well as the suppression methods would also suffer from dynamic oscillations. To this end, this paper first investigates the oscillation propagation and typical events caused by the oscillations. Next, the oscillation model estimation method including the model‐based and data‐driven based methods is discussed. The benefits and difficulties of various parameter estimate techniques are highlighted. Under this context, the validity and limitations of the current power system stability are summarized. Furthermore, the different oscillation damping and mitigation measures are compared, and the major adaptability and limitations are listed for the specific application scenarios. Conclusions are drawn, and the wideband oscillation becomes the future research objective where the future work is presented at the end of the paper. [ABSTRACT FROM AUTHOR]

With the emergence of renewable energy sources (RESs), the power grid all over the world is going through a paradigm shift. The inverter based RESs are replacing the conventional rotating synchronous generators and this trend is expected to continue in coming years. Consequently, the grid strength is decreasing, which can pose significant challenges on the grid stability, especially during integration of IRESs. This paper presents a thorough analysis on the integration challenges of IRESs in weak grids. The paper also presents a comprehensive investigation on the impacts of factors, such as available fault level at the point of interconnection (POI), feeder length and grid nature on the POI voltage, and maximum allowable power injection by IRES. This is followed by maximum allowable IRES power injection sensitivity analysis to quantify the impacts of the aforementioned factors. The paper concludes with a thorough case study on the IEEE 39‐bus test system to numerically show the impact of diminishing grid strength on the integration of IRESs. [ABSTRACT FROM AUTHOR]

A large‐scale AC/DC hybrid power network has recently been constructed in China because of the fast development of high voltage direct current (HVDC) technology. The receiving AC system must have sufficient system strength to guarantee the safe operation of the DC side. The paradox is that raising the AC side system's strength will increase the short‐circuit current (SCC) level, endangering the safety of the system. In order to resolve the contradiction between the system strength of multi‐infeed DC receiving‐end power networks and SCC, this paper proposes an optimal transmission switching strategy. Firstly, the system strength is characterised by the multi‐infeed short‐circuit ratio (MISCR), followed by constructing a comprehensive constraint set that considers the MISCR and SCC simultaneously. Secondly, to optimize SCC with MISCR and N−1 safety constraints, a mixed integer linear programming model is developed. Finally, to enhance the computing performance for large power systems, a new connectivity constraint set and decision space reduction techniques are provided. The proposed method is tested for effectiveness using the IEEE 30‐bus and IEEE 118‐bus systems. [ABSTRACT FROM AUTHOR]

The development of foreign electricity markets has been relatively complete, while China's electricity market started late and the design of the market mechanism needs to be improved, so the selection of a suitable market model and the design of the market mechanism in hydropower‐rich regions is conducive to the healthy development of the electricity market. While most of the first eight pilot regions in China have entered the long‐period continuous operation stage, and all the second batch of six power spot pilots have started the simulation trial run. However, the construction of power markets in hydropower‐rich regions of China, Sichuan, and Yunnan, still faces multiple problems to be solved, such as ensuring the reliability of medium‐ and long‐term power supply, improving the efficiency of hydropower resources utilization and consumption scale, and maintaining the stability of market prices. In this paper, the authors establish a multi‐scale joint clearing model for different market models considering both long‐term and short‐term operation strategies, and conduct simulations of different market models at different time scales to compare and analyze the optimization results and electricity price fluctuations of different market models. It can stabilize the market price and reasonably reflect the true value of hydropower, and also promote the consumption of clean energy and guarantee the reliability of power supply in the medium and long terms. Finally, suggestions are made for the selection of electricity market models, the security of energy supply and the design of sustainable development mechanisms for hydropower in hydropower‐rich regions such as Yunnan and Sichuan in China, with a view to providing useful references for the construction of China's electricity market. [ABSTRACT FROM AUTHOR]

The rapid growth in the number of electric vehicles (EVs), driven by the 'double‐carbon' target, and the impact of uncontrolled charging and discharging behaviour and discharged battery losses severely limit electric vehicles' low carbon characteristics. Existing research on systemic low‐carbon emissions and electric vehicle charging and discharging issues is usually determined by considering only carbon trading markets or charging and discharging management on the source side. In this regard, a coordinated and optimized operation model that considers the participation of electric vehicle clusters in deep peaking and the source network load and storage adjustable resources is proposed. The upper layer establishes a real‐time price‐based demand response mechanism for the load side with the minimum net load fluctuation as the objective function; the middle layer establishes a comprehensive operation mechanism for the source and storage side that includes an orderly charging and discharging peaking compensation mechanism for electric vehicles, and a deep peaking mechanism that takes into account clean emission, and constructs an optimal operation model with the minimum comprehensive operating cost as the objective function; the lower layer establishes a distribution network loss minimization model for the network side that takes into account the orderly charging and discharging of electric vehicle as the objective function. The optimal load model with the objective function of minimizing the distribution network loss is established at the lower level. Finally, the original problem is transformed into a mixed integer linear programming problem, and the model's effectiveness is verified by setting different scenarios. The model reduces the total cost by 22.22%, improves the wind power consumption rate by 19.55%, reduces the actual carbon emission by 16.66%, and reduces the distribution network loss by 13.91% compared to the basic model. [ABSTRACT FROM AUTHOR]

With the increase in power rating of electric vehicle chargers, concerns regarding their integration to the grid have likewise grown. This paper investigates a novel technique for start‐up of high‐power fast electric vehicle (EV) charger using a solid‐state inrush current limiter (SSICL). The circuit consists of three similar sets of bidirectional switch and limiting resistor that utilizes a control strategy based on a simple Kalman filter (KF) to suppress the converter start‐up current and transient over‐voltages. In fact, the built‐up profile of the inrush current is dictated in accordance with the estimated current by the slow dynamic KF. Compared to alternatives, such as start‐up resistors, the presented SSICL achieves faster start‐up with comparable peak current, tends to provide lower distortion, and provides a good balance between speed and efficiency. Simulation and experimental results confirm that the proposed method can considerably suppress inrush currents, while improving the total harmonic distortion. Comparing the behaviour of the SSICL to other relevant techniques underlines the advantages of the proposed solution. Furthermore, although the focus of this paper is start‐up of the fast EV chargers, the proposed circuit can act as an inrush‐current limiter in most AC to DC converter structures. [ABSTRACT FROM AUTHOR]

This paper proposes a WECS based on a back to back diode‐clamped multilevel inverter systems (DCMLI) fired comparatively by sinusoidal pulse width modulation (SPWM) and third harmonic injection pulse width modulation (THIPWM) techniques. DFIG performance is compared using these technologies for different wind speed under normal operation condition. The proposed approach shows that the DCMLI systems generate a nearly sinusoidal voltage with reduced total harmonic distortion (THD) thus upgrading the power quality of that produced by DFIG. As SPWM and THIPWM MLI are most common usage techniques in research, we applied them in the system to discuss a comparison of using those techniques to determine the number of levels that achieve the IEEE 519 criteria of THD which is less than 5% for both techniques (5th level for SPWM and 4th level for THIPWM) in all operation wind speed. Compared with simple PWM, and THIPWM have many advantages as lower THD, minimal number of switching to decrease switching losses and the output fundamental voltage is increased. Lastly, the paper investigates the variation of the frequency of induced rotor voltage and the active power flow due to the wind speed change when the rotor speed changes from super‐synchronous to sub‐synchronous speeds. [ABSTRACT FROM AUTHOR]

The conventional distribution network is becoming an active grid due to widespread integration of distributed energy resources (DERs). This integration raises great concerns about security of the power system considering the growing interactions between the transmission and active distribution systems. One way to ensure stability of the integrated power system is prediction of critical contingencies which can jeopardize the power system security. Therefore, this paper aims to investigate transient stability contingency ranking in power grids considering the uncertainties raised by DERs of active distribution networks. To this end, probabilistic transient stability prediction framework is provided, in which the probability density function of transient stability condition is calculated based on the normalized stability indicators. The normalized stability indicators are based on the rotor angle and rotor speed. The normalized stability indicators are only utilized in the case of using fault data for prediction. Based on the proposed scheme, the instability of generators is anticipated through the proposed probabilistic transient stability prediction framework. Also, the effects of the probable topology changes on the line overload and also the voltage profile are investigated. Finally, the performance of the proposed method is validated and compared with the time domain simulation under various operating conditions. [ABSTRACT FROM AUTHOR]

Inertial and droop control are common methods for improving grid frequency control. Using the first‐order derivative of the frequency in the inertial control loop only investigates the rate of frequency variation, while other useful information is not taken into consideration. Accordingly, in this study, the application of a fractional‐order derivative (between 1 and 2) in the inertial control loop is proposed to have more useful frequency‐based information. To achieve this goal, firstly continued fraction approximations and secondly, the discretization is adopted by using the Tustin Method with Prewarping. Inertia loop and droop loop gain have a significant impact on the operation of the wind turbines and the power system frequency control. Therefore, in this paper, a novel method for the adaptive adjusting of droop and inertia control loops gains in DFIG is proposed. To utilize more frequency error information, fractional‐order adaptive law is proposed to update the loop gains and the inertia control loop. In order to have a robust system, which is permanently stable for every fractional order (FO), is used parameter space method. Simulation results demonstrate the proper performance of the FO‐based adaptive approach to increase the frequency nadir (FN) and decrease the frequency variations. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) charging will bring new challenges to the coordination of grid and EV load. To facilitate large‐scale EV applications, optimal scheduling of EVs has become essential. However, the power grid has no power to force EV users to charge or give up charging. The actual type and mode of user's charging, may deviate from the expectations of grid. When the number of deviation's EV is sufficient, the power grid schedule will not achieve the expected results. In this context, a multi‐objective scheduling method considering user's charging selection is proposed to determine the optimal EV charging. The novel contributions of this paper lie in the exploitation of the user's preferences and their criterion of charging selection in form of functions based on concepts from economics. Three types of charging preferences for EV users including radical, conservative and balanced are used to influence the charging cost of EVs and load variance of grid. Finally, the ideal scheduling and actual scheduling are used to simulate various scenarios. The extensive results show that by introducing a method considering the influence of EV user's selection, the efficacy of the proposed scheduling can be further improved. [ABSTRACT FROM AUTHOR]

A cluster with multiple AC or DC microgrids (MGs) based on flexible DC interlinking and distributed energy storage systems is studied in this paper, which has been identified to have the following issues in terms of its primary control scheme: coordinated power control among slack terminals in the MG cluster, seamless operation mode transition for the interlinking converters and the common DC bus voltage control. A novel flexible control scheme that unifies the control of all the MGs only using local measured signals without further communications is proposed in this paper, which aims to improve control stability, and operation reliability and flexibility. Theoretical introduction and analysis are presented to explain the proposed control. The detailed average value model and small‐signal model of an MG cluster with two AC MGs and two DC MGs are simulated, respectively, with the proposed control in power systems computer‐aided design/electro‐magnetic transient design and control to verify the effectiveness in control stability and flexibility enhancement, and the impact of control parameters on the small‐signal stability of the considered cluster is analysed through root locus. [ABSTRACT FROM AUTHOR]

Due to a variety of social and economic reasons, renewable energy resources (RES) have grown exponentially in the recent years. Although, with the inclusion of RES into the electrical grid, multiple predicaments like voltage stability are to be unequivocally foreseen. This paper proposes to use decentralised measurements gathered from the distribution grid. Exemplarily, an adapted Cigré low‐voltage benchmark network is used for simulation on a real‐time simulator (RTS). The voltage and VAR control (VVC) is implemented on a standardised measurement device, in addition to other smart grid functionalities. The VVC algorithm is executed on the measurement devices and uses real‐time analogue signals from the RTS for validating the implemented VVC functionality. The distributed measurements are then communicated to a central controller device using IEC 61850 architecture and the decisions of the VVC algorithm are processed back to the client devices for co‐ordinated VVC control strategies. These include transformer tapping, reactive power control, and network reconfiguration. The results also indicate the advantages of implementing VVC using decentralised measurements against the existing control strategy at the transformer with no decentralised measurements. [ABSTRACT FROM AUTHOR]

The ability of riding through the grid disturbances can increase the integration of microgrids into the distribution system. Consequently, a grid‐connected microgrid should provide ancillary services such as low voltage ride‐through (LVRT) capability and reactive power support to sustain the power system operations during abnormal grid conditions. The objective of this paper is to propose an LVRT scheme that improves the power quality of the entire microgrid. The developed method is implemented as the controller of the interface voltage‐sourced converter (VSC) of a distributed energy resource and consists of primary and secondary control levels. The former includes the cascaded voltage and current control loops and the droop controller, while the latter controls the reactive power injection during the balanced/unbalanced voltage sags/swells. The proposed scheme is developed based on the independent control of each phase and does not require calculation of symmetrical components. Moreover, it can be employed in the VSC control systems with various reference frames and is effective for droop‐based grid‐connected microgrids with both single‐phase and three‐phase four‐wire configurations. The proposed strategy is implemented using the hierarchical control system and preserves the plug and play capability. Several case studies are presented to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

The fault current limiter (FCL) has been envisaged as a feasible solution to defend against out‐of‐range short‐circuit currents (SCCs) in power systems. However, the existing studies mainly sited and sized FCLs under deterministic fault scenarios. Moreover, the influences of FCLs on power systems are complex including dynamic aspects, which makes it extremely difficult to configure FCLs optimally. This paper proposes a risk‐based many‐objective FCL configuration framework. Specifically, a data‐driven Proportional Hazard Model (PHM) is developed to evaluate the nodal long‐term short‐circuit probability considering equipment aging, weather statistics, and surrounding conditions. The risks in terms of out‐of‐range SCC, abnormal voltage sag, and transient instability are formulated as the objective functions of the FCL configuration model, as well as the overall FCL investment. The time‐domain dynamic response process of FCLs is considered in both the SCC limiting and the transient stability simulation process, mainly in the form of a time‐varying resistance. The state‐of‐the‐art NSGA‐III is deployed to search the Pareto‐optimal FCL configuration solutions of the established many‐objective FCL configuration problem. The numerical results verify that the risk‐based model configures FCLs more economically with a 7.5% decrease of average FCL investment compared with the deterministic model. [ABSTRACT FROM AUTHOR]

Uncertainities and variations of power generation through photovoltaic (PV) sources are major challenges for their integration with the distribution grid. Voltage rise and voltage drop issues limit the increase in PV penetration and loading levels, respectively. Moreover, it is important to maintain voltage levels as per grid code while ensuring that the PV power generation is not curtailed. In this paper, a voltage control method using smart transformer (ST) via dynamic optimal setpoints and limit tolerance is proposed in a residential distribution network. Performance indicators are developed to understand the impact of the proposed method on the system voltage profile. A method to determine the optimal inputs for voltage control methods depending on the day-ahead predictions of load demand and PV power profiles is developed. Further, a voltage control method of switching among three setpoints based on the voltage that determines the load side ac reference voltages for ST is proposed. The proposed method is compared with the method of switching between two setpoints based on current. The proposed method provides an improved voltage profile in the distribution network, which is tested on a CIGRE low voltage residential distribution network using PSCAD [ABSTRACT FROM AUTHOR]

Grid-connected converters are expected to provide ancillary service utilising their spare capacities during operation. This study proposes a novel control strategy for clustered micro-grids to compensate voltage-unbalance of the power grid at the point of common coupling. Every micro-grid are interfaced to the power grid through a micro-grid inverter (MGI). All MGIs are designed independently with positive-sequence (PS) and negative-sequence (NS) control loops. Every micro-grid autonomously performs grid synchronisation and mode switching. After grid-connecting, a dynamic capacity allocation method is proposed for the MGIs to optimise its PS and NS capacity according to the grid voltage unbalance factor. Furthermore, a V–I droop control of the NS control loops is developed, with which each MGI can regulate its NS current according to the NS voltage in a droop manner. With the proposed method, all micro-grids participate in grid voltage unbalance compensation according to their own potential capacities without communications. Finally, a micro-grid cluster model with three micro-grids is built on Matlab/Simulink to validate the proposed control strategy. [ABSTRACT FROM AUTHOR]

One of the most important tools for condition monitoring is the gas chromatography test of transformer oil, which is known as dissolved gas analysis (DGA). In this research, the DGA results of >3000 power transformers operating in Iran's power grid were carefully studied and from among them, the results related to transformers suspicious of being faulty were used to validate the fault detection accuracy of the presented fuzzy inference system (FIS). In most of the previously published papers, the detection and isolation of transformer faults has been based on one or two of the following parameters: absolute concentrations of free and dissolved gases in transformer oil, total dissolved combustible gases, total combustible gases, ratios of some gases to each other, and the rates of gas increase. However, in this research, most of these parameters have been used for fault detection and isolation, according to the IEC 60599 standards. Also, no attempt has been previously made to detect the decomposition of insulation papers of transformers; but the presented FIS is able to detect this fault as well. The overall performance accuracy of the presented system is F 1 = 91.2%, which seems to be a suitable value. [ABSTRACT FROM AUTHOR]

This paper investigates the planning and operational processes of modern distribution networks hosting distributed energy resources (DERs). While in the past the two aspects have been distinct, a methodology is proposed in this paper to co‐optimise the two phases by considering the operational flexibility offered by DERs already in the planning phase. By employing AC optimal power flow (OPF) to analyse the worst‐case scenarios for the load and distributed generator injection, the optimal set‐points for the DERs are determined such that the network's security is ensured. From these results, the optimised individual characteristic curves are then extracted for each DER which are used in the operational phase for the local control of the devices. The optimised controls use only local measurements to address system‐wide issues and emulate the OPF solution without any communication. Finally, the proposed methodology is tested on the Cigre LV benchmark grid confirming that it is successful in mitigating with acceptable violations over‐ and under‐voltage problems, as well as congestion issues. Its performance is compared against the OPF‐based approach and currently employed local control schemes. [ABSTRACT FROM AUTHOR]

AC transmission expansion planning (TEP) is a complex problem to solve due to its large scale, mixed‐integer, non‐linear and non‐convex characteristics. This paper presents an efficient sensitivity based approach which employs the primal‐dual interior point method (PDIPM), for tackling integer variables in AC TEP. PDIPM's Hessian is used to evaluate the sensitivities of the objective function with respect to the line candidates, which are then used to find a feasible AC TEP solution. The proposed approach solves this non‐convex mixed integer non‐linear programming problem, without resorting to any use of relaxations/approximations in the AC TEP model. Also, the need and superiority of the AC TEP over the conventional DC TEP is established by comparing both using the proposed approach. Solutions of AC TEP with reactive power planning and an integrated multistage AC TEP are also obtained to demonstrate the performance of the proposed approach. Superior solution quality and lesser computation time of the proposed approach are confirmed by comparing the same with that of the branch and bound/cut approach, constructive heuristic algorithm, merit function‐based approach, conic programming and particle swarm optimisation. The studies performed for the various test cases prove the efficacy and computational efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

The variable step size modified least mean square (VSSMLMS) learning algorithm based multifunctional double‐stage grid interactive photovoltaic (PV) system is implemented in this paper which feeds power to the grid and the load, ensures unity power factor operation and compensates reactive power. Along with this, it mitigates high grid neutral current during unbalanced loading condition. This algorithm uses variable step sizes to have a smooth dynamic and steady state performances. The boost converter (booster) is used in the first stage to extract peak power from a PV array using perturb and observe peak power point tracking technique. Next to this, a four leg voltage source converter (VSC) is placed to interlink the solar PV system to the grid and the loads. VSSMLMS‐based control technique is used to filter the fundamental component of load current and hence gate pulses are generated for the four‐leg VSC. This system is simulated in SIMULINK/MATLAB software under several working conditions and the obtained simulation results are validated on a developed laboratory prototype. The performance of the VSSMLMS‐based control technique is compared with that of the traditional LMS‐based technique. All results validate the IEEE‐519 standard. [ABSTRACT FROM AUTHOR]

This study validates an alternative restoration of a critical load area using remote black‐start units. Using the conventional restoration, switching actions on a nominal system voltage create switching transients, especially when energising a transformer. The transients maybe close to the resonance frequencies of a weak island system, which may induce high voltages, delay the restoration and damage the equipment in the grid. This study proposes an alternative restoration procedure where, to avoid switching transients, hundreds of kilometres of transmission lines and several transformers are energised using a gradually increasing voltage, which is controlled by the synchronous generator exciter. This study presents detailed procedure flowcharts, a proof of concept for the proposed procedure using a Finnish and an Austrian field tests and theoretical analyses of the tests. The results show that with the gradually increased voltage, harmonic resonances and switching transients during the initial system energisation maybe avoided. In addition, the study shows that variations in the system frequency may cause voltage problems in a weak system during restoration since the system reactance is dependent on the system frequency. Thus, large frequency variations and the unstable operation regions of turbine governors should be avoided during the restoration. [ABSTRACT FROM AUTHOR]

The quality of electric power equipment directly affects and decides the securable and stable operation of the power grid. Revealing the quality problem causes and influencing factors are considered as the key point to improve and guarantee the quality of power apparatus. However, the data of power supplies quality problems have the features of diversity and complexity. It is of great value to take the full advantages of the multi‐source heterogeneous data, especially the possess flow information tracing time and space, to locate vulnerable processes, problem causes and influencing factors. This study put forward a data source system, which includes general information, quality problem information, process flow information and other supplementary information. Furthermore, an improved neural network model utilising knowledge–data fusion method is proposed. In this way, the efficiency and accuracy of analysis for quality problems is available and enhanced. To verify the validity of the knowledge–data fusion model, a case study with 2084 sample data of gas‐insulated switchgear is carried out, proving help to strengthen the management and control measures of power equipment quality problems. [ABSTRACT FROM AUTHOR]

With an increasing number of power converters using fast switching technologies, more cases of interference between devices in the frequency range from 2 to 150 kHz occur. The most widely used technique in such devices is pulse‐width modulation (PWM) [e.g. in photovoltaic inverters (PVIs), active harmonic filters, battery storage systems and some types of electric vehicle chargers]. Only little is known about the behaviour of those sources, the factors influencing their emission and the interaction with other devices and the propagation in the network. To extend such knowledge, reliable and accurate models are required. In this study, a quantitative model for the prediction of voltages and currents in this frequency range is developed and verified. Since in most cases no information about internal circuits and controls of the devices is available, a measurement‐based black‐box approach is used. The emission around the switching frequency of single‐phase voltage‐source power converters is combined into a single emission source represented by a Thévenin equivalent. The general method to parameterise the model is presented and exemplarily applied for two PVIs and one battery‐electric vehicle charger. Moreover, the interaction of two devices at a joint point of connection is simulated and compared with real measurements. [ABSTRACT FROM AUTHOR]

A novel combined probabilistic forecasting method based on an improved Markov chain for photovoltaics (PVs) to enhance the accuracy of probabilistic PV power forecasting is presented. First, a Markov chain (MC) forecasting structure combining precise factors is proposed that considers more influence factors beyond the statistical information of historical data as compared with conventional MCs. Rough set theory is then used to refine the major factors to quantify the influence of those factors. Furthermore, a k‐nearest neighbours algorithm is used to select similar samples for building an accurate forecasting model. Based on similar samples, the changing PV trends are more obvious than when using whole historical samples, thus further improving forecasting accuracy. Finally, the effectiveness and superiority of the proposed method are verified by comparing results from simulations with the results from competing methods for two cases using datasets from DESERT KNOWLEDGE AUSTRALIA Solar Centre and GEFCom2014. The simulation results show that the proposed method can provide probabilistic forecasting results with better performance, also, the proposed method can be adapted to various forecasting scenarios. [ABSTRACT FROM AUTHOR]

A well‐designed scheme is essential for assessment and protection of the stability of power system after an unanticipated event. This paper proposes a strategy for regulating three‐phase faults and other events that endanger frequency or voltage stability of the system. The aim is to promptly identify such events utilizing supervised learning‐based classification modules, and initiate suitable emergency control. The imbalances of active and reactive power after an event have been utilized to predict the stability of system. A new optimization‐based formulation has been presented for estimation of reactive power imbalance. An event predicted as unstable is counteracted by prompt load shedding. Conventionally, load shedding is based on frequency or voltage information independently which reduces the effect of load shedding. This work proposes a new load shedding procedure considering both active and reactive power. The proposed scheme is tested on New England (NE) 39‐bus system and Northern Regional Power Grid (NRPG) 246‐bus system, and results of load shedding have been compared with two existing load shedding schemes. The results indicate the accuracy of classification modules in identifying faults and unstable events, and the proposed load shedding restores stability of the system with less amount of load shed and better voltage profile. [ABSTRACT FROM AUTHOR]

Photovoltaic microgeneration (μG) located near the domestic consumers is expected to increase more in the future. Known issues regarding high μG penetration are voltage rise and reverse power flow. The concept of self‐consumption and storage is emerging as a way to improve network power supply quality and to facilitate the integration of small renewable energy sources in low voltage networks. This paper intends to give a further contribution by assessing the improvements provided by allowing domestic clients to consume and store the energy they produce. The tool at hand to study the situation is the unbalanced three‐phase load flow algorithm, based on the power summation technique, improved with the capability of explicitly compute the neutral voltages. The behaviour of a test radial distribution grid is assessed in different operating conditions, namely winter/summer, μG penetration level and μG operating mode. Voltage profile, active power flow in the service transformer and losses are monitored. The results suggest that self‐consumption with storage operating mode is a promising solution. Voltage excursions above normal grid voltage operating limits were not observed, the situation of reverse active power flow does not occur and the power losses are reduced. [ABSTRACT FROM AUTHOR]

Voltage and frequency are both significant index of city grid. Electric vehicles (EVs) have the potential to provide ancillary services for power grid since they are in stop state at most time during a day. This paper proposes a novel unified EV charging and discharging strategy by controlling active power to provide voltage and frequency regulation in city power grid. The objective of the strategy is to solve the voltage drop/rise and frequency fluctuation in city power grid with minimum influence on EV owners travelling demand. The available V2G regulation power is obtained according to the EV owners' transportation demand, initial and real‐time battery SOC and departure time. In case of voltage and frequency deviation out of the limitation, the EVs can participate in correspondence regulation by fast adjustment of charging or discharging power within the limitation. Simulations on an urban distribution network and an urban power grid are presented for voltage regulation and frequency regulation, respectively. The results have demonstrated the effectiveness of the proposed strategy. It can be concluded from the results that EV can be scheduled to solve the city grid voltage drop/rise and frequency fluctuation with the proposed strategy. [ABSTRACT FROM AUTHOR]

This study introduces a predictive auto‐reclosure scheme based on faster‐than‐real‐time (FTRT) analysis for synchronous generator type of distributed generation (DG) units to decrease DG oscillations after successful reclosure and also enhance transient stability margin of the unit after unsuccessful reclosure. The FTRT analysis, as a new concept for the protective relaying, represents a powerful predictive auto‐reclosure scheme which is based on a state‐space model of the DG unit. After a fault scenario and the first operation of the associated breaker, the FTRT analysis predicts energy level of the DG unit and determines an optimum dead‐time corresponding to the minimum energy level of the DG unit for reclosure that can provide an appropriate margin for transient stability. The effectiveness and accuracy of the proposed method are verified based on a test system. The results confirm that the proposed approach can effectively enhance transient stability for unsuccessful reclosure and reduce the corresponding oscillations after reclosure. [ABSTRACT FROM AUTHOR]

One of the effective methods to reduce the risk of load shedding and its subsequent blackout is to evaluate the risk of cascading outages and detection of key links in a power system. This risk assessment is getting more complicated considering the plans for integration of high wind energy. Therefore, in this study, a new sequential time approach has been proposed to evaluate risk of cascading outages considering the high penetration of correlated wind farms. The cascading processes are investigated using the extended OPA model using the graph traversal algorithm. Therefore, the problem of non‐convergence situations caused by the island formation is resolved. To deal with the future wind farms integration, a correlation is defined between them by a proposed method based on the Copula theory. The numerical results confirm that in evaluation of risk, the limited scenarios cannot always be reliable. The extended OPA model is then compared with a simple OPA to confirm the importance of islanding detection in the cascade simulation. Different aspects of cascading outages, i.e. fractional load shedding, cascade propagation level and number of line interruptions have been investigated. Finally, the impact of wind penetration and correlation of wind farms on results have been presented. [ABSTRACT FROM AUTHOR]

This paper deals with the design and analysis of a virtual synchronous generator (VSG) control strategy applied to a renewable‐based system devoted to energy production in a stand‐alone microgrid context. The studied hybrid energy production system consists of renewable‐based energy production systems, a diesel power plant (DPP), and an energy storage system (ESS). The first part of the study will deal with the design of a single renewable energy source controlled using the VSG control strategy. In the second part, multiple renewable energy sources, similar to the one presented in the first part, will be connected in parallel to form a renewable farm. Finally, in a third part, the studied renewable farm will be integrated in a full hybrid system. In each part of the proposed study, the system power output will be evaluated and the voltage and frequency variations will be carefully analysed. [ABSTRACT FROM AUTHOR]

Modern power systems consist of power electronics devices, which are used in renewable energy (RE) conversion. However, these devices, associated controllers, and uncertainty in RE output could bring new challenges to power system stability, especially oscillatory stability. Hence, the integration of battery energy storage systems (BESSs) is being developed to minimise the uncertainty and variability in renewables. Furthermore, to tackle the complex dynamics and inertia‐less characteristics of wind and PV plants additional controllers such as power oscillation damping (POD) control and virtual inertia scheme are sought. However, the primary challenges associated with the wide‐area oscillation damping controller are signal transmission delay, loss of communication signal, data drops, and others. This paper proposes a bat algorithm (BA) based resilient wide‐area multi‐mode controller (MMC) for enhancing oscillatory stability margin with high penetration of renewable power generations (RPGs) and BESSs. The Java 500 kV Indonesian grid is used to evaluate the performance of the resilient wide‐area MMC. From the results, it is found that the proposed controller effectively damp the critical mode of oscillation in the system even under communication failure as well as certain damping controller failures. [ABSTRACT FROM AUTHOR]

One of the recently arisen issues for transformerless grid‐connected photovoltaic (PV) systems is high‐frequency leakage current, which flows through the parasitic capacitance of PV system and the neutral grounding resistor (NGR) of the grid. This paper deals with a systemic analysis on the capacitance of large PV systems considering the interconnecting conductors. A new Y‐bus model is proposed to analyse the leakage current of PV strings/arrays of any size in high‐frequency domain. In the model, different capacitances of PV panels and the inductance and capacitance of interconnecting cables are considered. Subsequently, a two‐port circuit is derived by its admittance parameters, which is useful in leakage current studies. In the second step, a novel model for the common mode (CM) analysis of voltage‐source inverters is derived based on which, a new leakage current mitigation technique is proposed which provides capacitive CM paths for both the negative and positive legs of the inverter. The model is assessed using different simulations in various conditions. The results confirm the usefulness of the proposed model. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

This paper first presents a step‐by‐step tutorial on modal analysis of a doubly‐fed induction generator (DFIG)‐based series compensated wind farm. The model of the system includes a wind turbine aerodynamics, a sixth‐order order induction generator, a second‐order two‐mass shaft system, a fourth‐order order series compensated transmission line, an eighth‐order rotor‐side converter (RSC) and grid‐side converter (GSC) controllers, and a first‐order DC‐link model. Then, using modal analysis and time‐domain simulations, it is shown that a fixed‐series compensated DFIG is highly unstable due to the sub‐synchronous resonance (SSR) mode. In order to damp the SSR mode, the wind farm is interfaced with the gate‐controlled series capacitor (GCSC) ‐ which is a new series flexible AC transmission system (FACTS) device. A SSR damping controller (SSRDC) is designed for the GCSC using residue‐based analysis and root locus diagrams, and an effective input control signal (ICS) to the SSRDC is identified in order to simultaneously increase damping of both the SSR and super‐synchronous (SupSR) modes. The IEEE first benchmark model on SSR is adapted with an integrated DFIG‐based wind farm to perform studies. Matlab/Simulink is used as a tool for designing process, and PSCAD/EMTDC is used for time‐domain simulations. [ABSTRACT FROM AUTHOR]

Large‐scale electric vehicle (EV) charging will bring new challenges to coordination of grid and transportation. To facilitate large‐scale EV applications, optimal locating and sizing of charging stations have become essential. For the investors of a charging station, economic benefit is the primary and the only objective. In this context, this work studies the siting and sizing of EV stations based on the optimal economic benefit. Benefit changes with time, location and capacity. A planning model method considering net present value (NPV) and life cycle cost (LCC) is proposed to determine the site and the size of the charging stations. The model has integrated distribution network constraint, the user constraint and the traffic flow captured constraint. Origin–destination lines and voronoi diagram are selected to calculate the traffic flow and the service region of each charging station, respectively. The quantum genetic algorithm was adopted for a better convergence of the planning model. Finally, a coupled 33‐node distribution system and a 36‐node transportation system are used to simulate various scenarios in the coupled networks of grid and transportation. The simulation results show that by introducing a planning model method considering NPV and LCC, the charging station economical benefits can be further improved. [ABSTRACT FROM AUTHOR]

Converting the surplus power into rotor kinetic energy by changing the control functions of machine side converter (MSC) and grid side converter (GSC) is considered to be an efficient way for permanent magnet synchronous generator (PMSG)‐based wind turbine generator system (WTGS) to accomplish low‐voltage ride through (LVRT) without additional hardware components. However, because of the time delay of grid fault detection and the control system inertia, the dc‐link capacitor may still be subjected to overvoltage in the early tens of milliseconds after a grid fault happens. This study proposes a compositive control method of LVRT for PMSG‐based WTGS, in which the surplus power during LVRT is converted into rotor kinetic energy by controlling the electrical power of the PMSG according to the grid‐connected power of the GSC, and a crowbar circuit is reserved to consume the surplus power before MSC reacts to the grid fault. The proposed method does not change the control functions of MSC and GSC, and the related control parameters resetting can be avoid. Besides, it can also provide reactive power support to assist the grid voltage recovery. Simulations and experiments proved the proposed method to be feasible and effective. [ABSTRACT FROM AUTHOR]

This paper describes an intelligent sensor fault detection and compensation (FDC) scheme for a hybrid grid involving renewable energy (RE) sources with power electronic interfaces. To evaluate the sensor FDC scheme, a wound rotor induction generator (WRIG)‐based wind energy system connected to the hybrid grid is examined. The system employs a WRIG with excitation from DC RE grid via a single, rotor side converter. To analyse the dynamic performance, a decoupled voltage vector control is employed. The sensors involved in the control algorithm may not be ideal and if fault occurs might lead to system collapse. To overcome electrical sensor failure, a robust, intelligent sensor fault control scheme is proposed with ANFIS. A hardware‐free solution with PLL block is proposed for mechanical sensor fault. The ANFIS‐based FDC scheme involves a bank of observers that computes residuals, detects and isolates faults. When fault occurs, the observer output is utilised for the execution of control algorithm thereby avoiding system collapse. The focused system is simulated in MATLAB and experimentally tested with a dSPACE controller for various fault scenarios. The results show the effectiveness of the FDC scheme. [ABSTRACT FROM AUTHOR]

This paper presents a new hybrid method for solving the proposed multi‐level optimisation problem, as described in Part I. The hybrid method employs a novel two‐stage multi‐dimensional melody search algorithm (MSA) with an innovative alternative improvisation procedure (AIP). This hybrid method handles the different levels of the proposed multi‐level framework. The two‐stage multi‐dimensional MSA is a recently developed optimisation algorithm, which is derived from the harmony search algorithm (HSA). Unlike the HSA, the MSA uses different player memories and a group improvisation procedure for finding the best substitution of pitches within a melody. These two features can enhance the performance of the MSA in comparison with the HSA. In addition, to improve the efficiency of the proposed MSA, an innovative improvisation scheme based on the AIP is used for generating new melodies. The proposed methodology has been applied on the 46‐bus south Brazilian electric power grid and the IEEE 118‐bus test system under two different scenarios in order to demonstrate the feasibility and capabilities of the newly developed framework. The obtained results from case studies validate sufficiency and profitableness of the offered multi‐level framework. [ABSTRACT FROM AUTHOR]

This study presents a method for integrating power sharing and participation in primary frequency response of power system for distributed energy resources in microgrids. This controller is based on power‐angle droop and results in thorough power sharing in islanded mode and constant power in grid connected state. It can be employed in microgrids along with the feature of plug and play for any kind of distributed generation resources involving synchronous generators. Also, this paper analyses the stability of the proposed controller and the conventional power‐angle droops in a microgrid with modelling in state‐space form and linearising around an operating point. It has been shown that the proposed controller results in more stability and accuracy than the conventional controllers. Also, eigenvalues are evaluated to find the best controller parameters for the microgrid stability. Finally, the controller response in different operating conditions of a test microgrid is assessed. [ABSTRACT FROM AUTHOR]

This paper demonstrates how the range of stable power transfer in weak grids with voltage source converters (VSCs) can be extended by modifying the grid synchronisation mechanism of a conventional synchronous reference frame phase locked loop (PLL). By introducing an impedance‐conditioning term in the PLL, the VSC control system can be virtually synchronised to a stronger point in the grid to counteract the instability effects caused by high grid impedance. To verify the effectiveness of the proposed approach, the maximum static power transfer capability and the small‐signal stability range of a system with a VSC HVDC terminal connected to a weak grid are calculated from an analytical model with different levels of impedance‐conditioning in the PLL. Such calculations are presented for two different configurations of the VSC control system, showing how both the static power transfer capability and the small‐signal stability range can be significantly improved. The validity of the stability assessment is verified by time‐domain simulations in the Matlab/Simulink environment. [ABSTRACT FROM AUTHOR]

In the medium voltage direct current (MVDC) shipboard grid, the inherent inertial support from the DC capacitors is too small to resist step changes or fluctuations from the high power pulse load and propulsion load, which results in lower DC voltage quality. This study proposes a decentralised control algorithm for the MVDC shipboard hybrid energy storage system (HESS) to enhance the onboard survivability. This algorithm adjusts the droop control coefficient based on the bus voltage change rate adaptively, meanwhile the voltage differential signal processing and filtering are implemented by the trace differentiator. In addition, the proposed algorithm also has state-of-charge (SOC) balancing and SOC recovery abilities between multiple groups of energy storage devices. The parameter selection principle are analysed, and a variety of working conditions are simulated and verified in PSCAD. Theoretical analysis and simulation show that, HESS can achieve good power distribution and SOC management performance without communication compared to fixed droop coefficient control strategies, and the dynamic characteristics of bus voltage have been significantly improved. [ABSTRACT FROM AUTHOR]

This study presents a differential protection scheme based on ensemble empirical mode decomposition (EEMD) for AC microgrid. The fault current level is significantly lower during the islanded operation of a microgrid, which leads to the malfunction of the traditional over-current protection scheme. The proposed differential protection scheme uses the spectral differential energy of the first intrinsic mode function extracted from the decomposition of the current signal using EEMD for effective fault detection in the AC microgrid. The proposed EEMD-based differential protection scheme is validated on 10 bus and modified IEEE 34-bus AC microgrid test systems during various shunt faults. Moreover, the performance of the proposed EEMD-based differential protection scheme is evaluated under high fault impedance scenarios. The simulation results reveal that the proposed differential protection scheme can effectively detect the faulty line in an AC microgrid during seamless islanded and grid-tied operations. [ABSTRACT FROM AUTHOR]

In this study, a novel $H_\infty $H∞ predictive event-triggered load frequency control has been developed for a hybrid power system with renewable energy sources (RESs) to deal with denial-of-service (DoS) attacks, where the DoS duration (the time attack lasts) are boundless. A predictive event-triggered transmission scheme is built for the multi-area hybrid power systems under DoS attacks to reduce the load of network bandwidth while maintaining adequate levels of performance. Therefore, an observer-based predictive controller is developed in the presence of both external disturbances and DoS attacks by formulating the LFC problem as a disturbance attenuation issue. In the proposed method, a hybrid power system with RESs is used to achieve novel and better security strategies. Based on the new model, sufficient conditions are obtained using the Lyapunov stability theory to ensure a stable multi-area hybrid power system with a prescribed $H_\infty $H∞ performance. Moreover, an algorithm is provided to obtain the control strategy of DoS attacks. Finally, the simulation of a hybrid power system with RESs is presented to demonstrate the effectiveness of the proposed method in dealing with the DoS attacks. [ABSTRACT FROM AUTHOR]

To solve the problem of manpower and time consumption caused by power flow state adjustment in a large-scale power grid, a power system operation state adjustment method considering the static stability constraint based on parallel deep reinforcement learning is proposed. By introducing the process of adjusting the power flow state that satisfies static stability, the Markov decision-making process of adjusting power flow is constructed. Then, based on the positioning of the adjustment target, the selection of actionable devices and the calculation of the amount of action, a power flow state adjustment strategy is developed. The adjustment process is accelerated through sensitivity, transfer ratio and load margin. Then, a parallel deep reinforcement learning model is established, and it maps actions to power flow adjustment to form a pair of generator actions and realises parallel adjustment of multi-sectional objectives. In addition, the reinforcement learning strategy and the deep learning network are improved to promote learning efficiency. Finally, the New England 39-bus standard system and actual power grid are used to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms requires an optimal grid partitioning strategy. To obtain the requisite power grid partitionings, the authors first apply several graph theory based partitioning algorithms, such as the Karlsruhe fast flow partitioner (KaFFPa), spectral clustering, and METIS. The goal of this study is an examination and evaluation of the impact of grid partitioning on power system problems. To this end, the computational performance of AC optimal power flow (OPF) and dynamic power grid simulation are tested. The partitioned OPF-problem is solved using the augmented Lagrangian based alternating direction inexact Newton method, whose solution is the basis for the initialisation step in the partitioned dynamic simulation problem. The computational performance of the partitioned systems in the implemented parallel and distributed algorithms is tested using various IEEE standard benchmark test networks. KaFFPa not only outperforms other partitioning algorithms for the AC OPF problem, but also for dynamic power grid simulation with respect to computational speed and scalability. [ABSTRACT FROM AUTHOR]