A microgrid (MG) is a cyber-physical system that facilitates integration of several distributed renewable energy resources. In the last decade, several efforts were made to standardise the framework of a cyber-physical MG network and its control structure. In this perspective, various studies discussing the different control techniques are reported in the literature. However, a comprehensive and systematic review of a cyber-physical MG is discussed rarely. In this study, a comprehensive review of a MG architecture and hierarchical control structure in both islanded and grid-connected modes are presented. The hierarchical control of the MG includes primary, secondary, and tertiary control. Recent studies provide significant opportunities in dividing the control task among various layers resulting in a distributed framework. This study analyses the cyber and physical networks separately while discussing the primary, centralised, and distributed secondary control levels with their merits, demerits, and typical applications. A Venn diagram analysis is also presented that clearly distinguishes the primary control scheme in different research sub-areas. Furthermore, the MG communication structure, protocols, design, constraints, and cyber security are also reviewed systematically. Finally, future trends are summarised based on the state-of-the-art MG research.

For series-compensated line, the distance relay finds its limitations during voltage inversion, current inversion, load encroachment, power swing and balanced fault during the power swing. These limitations can be overcome by wide-area backup protection schemes. This study proposes a novel fault detection technique utilising the synchrophasor data of voltage and current signals at system protection centre. The algorithm compares the phase angle difference between positive-sequence voltage phasor under system intact condition and real-time positive- or negative-sequence current phasor, which is computed from the synchronised data obtained from phasor data concentrator after identifying the possible critical buses to which the faulted line is connected. Different cases of fault type, distance and resistance have been considered to validate the proposed scheme with 3-generator, 9-bus western system coordinating council using MATLAB/Simulink platform. The results justify the suitability of the proposed scheme to be deployed for achieving more reliable performance.

The frequency control is the mandatory task in a modern power system because of load demand variation and the integration of renewable energy sources (RESs). The main objective of automatic generation control (AGC) scheme is to maintain the balance between generation and load demand. This study proposes a graphical robust characteristic ratio assignment (RCRA) approach for PIDA controller tuning based on maximum sensitivity () for AGC. The basic feature of this graphical approach is that characteristic ratios () in RCRA scheme are calculated in terms of . The important part of this design is that the analytical expressions for coefficient gains of PIDA controller are derived in terms of and system parameters. Here, the non-reheat steam-turbine and hydro-turbine based single and multi-area power systems are considered for validation of the proposed control scheme. The critical issue in controller design for a hydro-turbine based power system is the non-minimum phase behaviour. The robustness and performance of RCRA-PIDA controller are examined under system non-linearities, parametric uncertainty and disturbances. Further, the performance of proposed approach is evaluated in the presence of RESs. Finally, it is observed that the proposed control approach performs better in comparison to the recently published control schemes.

The controlled islanding problem is typically considered only for pure ac power systems, with the ultimate objective of either minimising power imbalance or power-flow among islands. However, as ac/dc hybrid power systems are becoming popular worldwide, current controlled islanding schemes should be redesigned to take into account the presence of high-voltage dc (HVDC) links, possibly connecting different islands. Accordingly, in this study, the authors solve the classic islanding problem combining HVDC power modulation with the conventional ac cutset search. The flexibility of the HVDC allows the authors' strategy to jointly capture the previously mentioned objectives, and provides even lower power imbalances than the minimum imbalance strategy, at a relatively small cost of increasing power-flow impact. Then, the optimisation problem is formulated as a mixed-integer linear programming problem, which can be conveniently solved with existing commercial solvers. Finally, they validate their proposed strategy in two case studies, corresponding to a modified IEEE-118 system and to the China Southern Power Grid system. In both cases, dynamic simulations show that their proposed approach outperforms classic algorithms where the presence of HVDC power modulation is not explicitly taken into account.

This study describes the research and design of a novel and compact very low frequency cosine-rectangular (VLF-CR) and damped alternating current (DAC) voltage generator that can be used to test the insulation condition of the medium-voltage power cables. Further, a complete system based on a voltage multiplier (VM), which can be cascaded to increase the output voltage, is proposed to simultaneously realise VLF-CR and DAC voltages for the withstand voltage and offline partial discharge (PD) tests, enabling the test system to be lightweight and efficient. The system principle and operating characteristics associated with the generation of two different voltages are analysed in detail according to the new circuit topology of the proposed generator. Furthermore, oscillation suppression and multiple output units are considered to improve the voltage waveform and provide power supply to the VM module, respectively. A laboratory prototype is also developed and tested. Finally, the integrated generator is used for the PD testing on cables with artificial defects, verifying the practicability of the proposed system.

In this study, a novel 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 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.

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

With the conversion of the global power economy and energy structure, access to a large amount of renewable energy has led to a decrease in power system inertia. The slight abnormal disturbance in the distribution network may have a significant impact on social and economic development. Aim at enhancing power stability and system resiliency; this study focuses on the detection and location of multiple abnormal sources in the distribution network. Most traditional methods use models relying on precise line parameters, subject to poor adaptability to the distribution network with a large number of nodes, and rapidly changing topology. Therefore, this study proposes a novel random matrix model, driven by monitoring data from phasor measurement units distributed on the overhead transmission lines. In this model, linear shrinkage (LS) theory, and Marchenko–Pastur law are combined for noise reduction to ensure the dynamic character and anti-noise ability. Moreover, data dimensions and sample points may be at the same level in an extensive scale network. The LS and standard condition number rule (SCN) are used for estimating the number of abnormal sources. Finally, the effectiveness of this paper's model is verified in PSCAD. The results indicate that the method has specific dynamic performance and anti-noise ability.

In this study, the authors aim to develop a real-time and comprehensive fault detection and localisation method in the transmission networks in wide-area power systems and a two-stage process. In the first stage, the fault and faulty line are diagnosed and then the fault location is estimated accurately. For this purpose, the authors design a robust deep Gabor filter convolutional neural network (RDGCNN) to understand the features of the complex and non-linear signals during fault occurrence directly from the raw measured signals by the phasor measurement units (PMUs), on the basis of which a structure for fault detection, faulty line classification, and fault location estimation. The modulated Gabor-based convolutional layers are able to capture temporal features as well as enhance understanding spatial features with fewer parameters. Furthermore, to enhance the robustness in the noisy condition, which is unavoidable in modern power systems, a new loss function is reformulated. The performance of the proposed RDGCNN is examined in the IEEE 68-bus system in high noisy condition and the comparative results demonstrate that the designed robust deep network is fast, accurate, and reliable in the fault detection, faulty line classifying, and fault occurrence position.

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.

This study proposes controls and power sharing design and architecture for a 100% inverter-based transmission system. Such an operation scenario has already occurred for short periods in portions of several systems in the United States, Europe, and Australia, and is likely to be more frequent in the future. The proposed algorithm enables the inverter-based resources (IBR) to participate in power sharing based on an angle droop method that explicitly takes into account the IBR ratings and preferred set points. This strategy results in an essentially constant-frequency operation of the power system without relying on secondary controllers or communication for frequency restoration. The performance of the proposed architecture under different operating conditions is evaluated via extensive simulation case studies in PSCAD/EMTDC software.

Electricity network is leading to a low carbon future with high penetration of plug-in electric vehicles (EVs). However, it is extraordinarily difficult to acquire detailed information on regional EV electrification with an incomplete monitoring system for network operators. In this study, a flexible graph signal processing (GSP)-based non-intrusive monitoring on aggregated EVs is proposed to enhance the EVs visibility for operating power system safely and cost-efficiently. It can deduce the individual EV charging status with the highest possibility iteratively from the limited dataset using a GSP-based possibility calculation after processing a daytime EV characteristic charging patterns. The experiment is developed with realistic EV charging datasets collected in London, and the results show the daily EVs number in a specific region of 500 EVs daily aggregation can be estimated efficiently with an around 4.77% value of relative mean absolute deviation applying the proposed method.

The fault classification of medium-voltage transmission lines consisting of wind farms connected to the high-voltage (HV) transmission networks is carried out using the power-spectrum-based hyperbolic S-transform (HST) powerful technique for analysing non-linear and non-stationary fault signals through the non-intrusive monitoring systems. The HST technique extracts the useful features in the time-frequency domain from measuring fault current waveforms of the HV utility side to discriminate the fault types. Parseval's theorem is applied to each HST coefficient to quantify the energy distribution of various fault types for reducing the size of inputs for recognition algorithms. Next, multiclass support vector machines achieve identification. The results have proved that the proposed classification technique is independent of fault resistance, source impedance, and fault inception angles. Extensive simulations are conducted using the electromagnetic transients program to show that the recognition accuracy of the fault classification for all types is up to 96.84%.

The topology of power distribution systems can be modified by altering the status of sectional and tie switches for load management and protection, while maintaining the required network radiality. Several effective optimisation algorithms and graph theory-based techniques for system radiality detection have been proposed in specialised literature to solve the distribution network reconfiguration problem, usually seeking to achieve power loss reductions and voltage profile improvements. This work aims to contribute to this line of research and its novelties are composed of proposing as solution method a methodology based in an enhanced version of harmony search metaheuristic called improved harmony search algorithm, and a new simple and effective system impedance matrix based process to detect islanding of nodes as a strategy to meet radiality constraint. The proposed methodologies were applied to 33-bus, 84-bus and 118-bus distribution networks known from technical literature, aiming to total active power loss minimisation. As comparison between methods, a key focus in analysis of results is related to discuss some advantages and effectiveness of improved harmony search over original harmony search algorithm to attain optimal radial topologies.

This study presents a trajectory tracking control strategy that modulates the active power injected by geographically distributed inverter-based resources to support transient stability. Each resource is independently controlled, and its response drives the local bus voltage angle towards a trajectory that tracks the angle of the centre-of-inertia. The centre-of-inertia angle is estimated in real time from wide-area measurements. The main objectives are to stabilise transient disturbances and increase the amount of power that can be safely transferred over key transmission paths without loss of synchronism. Here the authors envision the actuators as utility-scale energy storage systems; however, equivalent examples could be developed for partially-curtailed photovoltaic generation and/or Type 4 wind turbine generators. The strategy stems from a time-varying linearisation of the equations of motion for a synchronous machine. The control action produces synchronising torque in a special reference frame that accounts for the motion of the centre-of-inertia. This drives the system states toward the desired trajectory and promotes rotor angle stability. For testing, a reduced-order dynamic model of the North American Western Interconnection is employed. The results show that this approach improves system reliability and can increase capacity utilisation on stability-limited transmission corridors.

The number of electric vehicles (EVs) is expected to grow significantly, which calls for effective planning of charging infrastructures. While the planning of the charging infrastructure relies on an accurate charging demands, the behaviours of EVs charging are not always predictable and can be sensitive to many uncertain future environmental factors. Considering such uncertainties, this study aims to robustly and optimally determine the chargers and main switch board (MSB) capacities without violating queuing time constraints and load flow constraints. The non-parametric estimations of charging demands are derived with data-driven charging behaviour analysis considering diverse social factors, including travelling patterns, queuing, and changes of charging facilities. Then, the impacts of the EV integration are modeled by a stochastic load flow program. The samples of the stochastic load flow stipulate the conditional value-at-risk constraints for the planning of chargers and MSBs, which consider the probabilities and scenarios in a box of ambiguity with bounds. Afterwards, by limiting the frequency and severity of constraints violation, the total investment cost is minimized with a distributionally robust optimisation program. Simulation based on a real-world residential community in Singapore is carried out to testify the effectiveness of the proposed method.

The temperature gradient and mismatching between the thermal expansion of the core and flange readily lead to cracks and discharges on the core surface of the dry-type valve-side bushing, which severely impact the safety of power systems. It is vital to clarify the cracking risk of bushing cores under temperature gradients and establish corresponding control methods. The mechanical properties of epoxy resin impregnated paper (ERIP) material were measured in this study at different temperatures, and a thermal–mechanical coupling simulation model was established. The thermal and stress distributions of the core were obtained and the cracking risk was defined accordingly. The crack development mode was explored as it relates to the phase-field mode. Various elastic cushion materials affecting the stress distribution of the core were investigated. The results show that the mechanical properties of the ERIP material decrease rapidly as the temperature increases. When under severe working conditions, the maximum first principal stress of the core may be significantly higher than the tensile strength of the ERIP material resulting in significant axial cracks. Adding an elastic cushion layer made of polyurethane rubber can effectively relax the interface stress and reduce the cracking risk.

This study proposes a method to determine optimal load demand changes of power generation units, in order to complete a total load demand change for power grids in the minimum response time. The main feature is to exploit the information of actual ramp rates, which are the maximum changing speeds of generated powers in practice from power generation units. The proposed method is composed of two steps. First, actual ramp rates are estimated from historical data based on the piece-wise linear representations of generated powers. Second, optimal values of load demand changes are determined based on the solutions to an optimisation problem minimising the response time. A main challenge is on the uncertainties of estimated actual ramp rates and their effects on the response time. This challenge is resolved by exploiting Bayesian estimators to yield posterior probability distributions of the estimated actual ramp rates, from which the optimal response time and its confidence interval are obtained. Numerical examples are provided to support the proposed method and compare with existing methods.

This study presents the design and analysis of an adaptive second-order generalised integrator (SOGI) technique for controlling voltage source inverter in a three-phase three-wire distribution system. The function of the proposed shunt active power filter involves compensation of reactive power for power factor correction, harmonic elimination, load balancing, voltage regulation under non-linear load condition. In this study, an effective approach for load compensation is proposed by designing an adaptive SOGI trained using Levenberg–Marquardt technique and compared with conventional techniques which ensure smooth operation under normal and distorted grid condition. An experimental setup is developed and its performance is analysed during different loading conditions. The experimental results are in line with the expected simulation results. Experimental and simulation results are verified and analysed using Bode plot.

Doubly-fed induction generators (DFIGs) have drawn prominent interest in the field of wind power generation, but they are vulnerable to grid faults. Grid codes mandate DFIGs to employ a sort of fault ride-through (FRT) technique during faults. Fault current limiters (FCLs) always help to augment the FRT capability of DFIGs and a non-linear controller boosts their performances. In this study, a non-linear auto-regressive moving average-L2 (NARMA-L2) controller-based bridge-type flux coupling non-superconducting FCL (BFC-NSFCL) is proposed to enhance the FRT capability of the wind farm. The authors analysed the performance of the proposed NARMA-L2-based BFC-NSFCL (NL2-BFC-NSFCL) against that of the conventionally used series dynamic braking resistor (SDBR), bridge-type FCL (BFCL), and proportional–integral (PI) controller-based BFC-NSFCL (PI-BFC-NSFCL). They tested the performance of the NL2-BFC-NSFCL through multiple temporary and permanent fault scenarios and carried out the mathematical and graphical analysis in MATLAB/Simulink platform. They found that the proposed NL2-BFC-NSFCL's performance surpasses the performances of the SDBR, the BFCL, and the PI-BFC-NSFCL. Moreover, the NL2-BFC-NSFCL has faster system recovery capability after the occurrence of any fault than other competitors.

With the wide deployment of smart meters in the end-user side, demand response (DR) is gaining prominence. Estimating the potential response is a preliminary step to the DR implementation. However, how to select proper features, how to protect privacy, and how to capture the response uncertainty remains three challenges to the customer response potential estimation. This study provides a detailed response quantity estimation for each customer. The authors proposed a probabilistic response quantity estimation framework and solved the problem by alternating direction method of multipliers (ADMM) in a fully-distributed way. In particular, by utilising a similar consumption pattern matching principle, the feature for each DR day of each customer is selected based on the matched DR participants. Then, the pinball loss-guided ridge regression is formulated, so the quantiles are obtained to cope with the uncertainty. The training process can be solved by each customer at the local site in a fully-distributed way, which protects the privacy and reduces the centralised processing burden. Finally, in the case study, the assumption behind a similar consumption pattern matching principle is validated empirically. Also, the proposed method is confirmed to have good convergence performance and can produce reasonable estimation results.

A tool to visualise real-time phasor measurement unit (PMU) data of a transmission line is proposed, named PQ chart. It is a simple and intuitive visualisation aid for operator situational awareness. The use of PMU data helps in capturing both steady-state and dynamic behavioural aspects of the transmission line. The tool is based on basic active and reactive power equations of a transmission line. The locus of active and reactive power flow corresponds to a circle in which the radius depends on voltage regulation. If the circle is imagined as a wheel, then the spokes of it correspond to the voltage angular difference across the transmission line. The PMU data is plotted on this canvas and its progression in time is observed. The occurrence of power swings, angular and voltage instabilities lead to a trajectory on the chart. A system operator can be alerted when any such movement occurs. The tool provides a single view from which deciphering active power flow, reactive power flow, voltage regulation, and voltage angle difference across a line becomes easy for the operator. Case studies with PMU data of 400 kV transmission lines in the Indian grid are presented to illustrate the tool's capabilities.

This study proposes a binary version of the pathfinder algorithm (BPFA) inspired by both the collective movement of animals and the leadership hierarchy of swarms in order to solve the existing bus splitting optimisation (BSO) problem encountered by transmission system operators. Some existing efficient algorithms, such as particle swarm optimisation, binary grey wolf optimiser, and salp swarm algorithms, are also utilised to obtain a suitable solution in the BSO problem and to compare it with the BPFA. The objective function of the BSO problem is built to restrict the short-circuit current and to provide the N − 1 security criteria. A new mathematical approach is proposed so as to assess the security performance of the transmission system during the solving of the BSO problem. The efficacy of the proposed algorithm is tested on well-known benchmark functions as well as IEEE 57 and IEEE 118 bus systems. Various transfer functions and position updating rules are implemented to each of the algorithms to acquire a better transition from continuous context to the binary format. The results obtained of the statistical indicators and the pairwise comparisons validate the efficiency and reliability of the BPFA algorithm in solving the compelling real-world problem.

High volatility renewable penetration increases the security risk of the market participants. In order to ensure the security of the reserve market under uncertainties, the authors have proposed a novel optimal bidding strategy based on bivariate pair copula-based security-constrained unit commitment economic dispatch (SCUCED) for the generation companies (GENCOs) while considering the volatility of wind power generations and load variations under different (N − k) contingencies in ancillary service market. The expected profit of GENCOs are based on the ramp-up and ramp-down optimal reserve curves in each time interval are submitted to the independent system operator. The profit of wind farms is obtained and the risks due to uncertainties with wind farms are also analysed while participating in the reserve market. Conditional value-at-risk is considered for the optimal placement of wind farms in the network. The risk-based SCUCED model is solved by mixed integer linear programming. Moreover, a factor called joint Pareto tail factor has been also developed to provide information regarding the fat tails in the lower end of the bivariate marginal distribution of different GENCOs. The effectiveness of the proposed approach has been tested on a modified IEEE 30 bus system.

Fossil fuel-fired power plants are still the principal power producers in most power systems. Retrofitting these pollutant generators with carbon capture and storage (CCS) technology can be a key solution to decarbonisation, especially for power systems with low expansion potential for renewable and hydroelectric energy resources. This study presents a coordinated generation and transmission expansion planning (G&TEP) and CCS expansion planning model for carbon emission constrained power systems. The proposed model determines the optimal order and time of retrofitting carbon emitter generators with CCS technology coordinated with the G&TEP. The limits on renewable resources capacity expansion potential and the yearly emission reduction targets are considered. Additionally, the proposed model allows for determining the incentives that are to be offered by the central planning authority to the pollutant generators to incentivise their participation in emission reduction through CCS retrofitting. The problem is formulated as a mixed-integer linear programming model and is decomposed into a master and three subproblems to tackle the large-scale nature of the developed optimisation problem. Numerical results demonstrate that a coordinated G&TEP and CCS expansion planning is a least-cost planning solution for emission constrained power systems with low expansion capacity potential for renewable and hydroelectric resources.

This study investigates the feasibility of advanced metering infrastructure (AMI) based on narrowband power line communications (NB-PLC) by incorporating all possible types of low voltage (LV) and medium voltage (MV) power line channels. The extensive field measurements are carried out on six selected sites that include residential, commercial, and industrial LV and MV NB-PLC channels. On the basis of measured results, NB-PLC channels of various under evaluation sites are segregated into two classes i.e. worst and good channels for both LV and MV networks. The simulation models for the modelling of LV and MV NB-PLC channels by considering the practical data of measured sites are developed and thus proposed. The proposed methods are validated by comparing the measured and simulated results. A sophisticated mechanism for the modelling of LV and MV network impedances and capacitive coupling device is formulated. The proposed analyses and simulation-based NB-PLC channel models can play a key role in examining the characteristics of various types of NB-PLC channels. This research work will help to standardise the future smart metering equipment and sensing devices of power system protection.

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.

Secondary direct-current loss within a substation is a severe event. In China, each line protection device is generally powered by one set of secondary direct current (DC) power system within a substation of 110 kV voltage level. In this case, the line protection devices will be immediately taken out of service when the secondary DC is lost, and the lines protected by them will lose their corresponding protections. Once a fault occurs on the line, only the remote back-up protection can be relied on to isolate the fault, which expands the fault influence and increases its clearance time. To handle the above problem, a novel wide-area protection algorithm based on compensation voltage moduli comparison is proposed, which is independent of multi-terminal data synchronism. Then, a comprehensive protection strategy composed of the proposed protection algorithm and the original local distances protection is proposed. The results from a power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC)-based simulation verify that the proposed protection algorithm has higher sensitivity. The comprehensive protection strategy could cope with most line faults effectively, even if only partial data are available, the selectivity and speed of which are better than that of distance protections.

Microgrid inverters in the presence of faults, unavoidable modelling uncertainties, disturbance and harmonic current resulting from nonlinear loads should have small steady state tracking error, small THD and high robustness hence this subject has turned one of the motivations of this investigation. To achieve the stated goals, fractional adaptive sliding mode controller (FASMC) is proposed in this paper. The proposed controller increases the robustness, flexibility and degree of freedom. As far as in practice it is not easy to define the bounds of disturbances and guarantee the system stability, hence in next step, to overcome this challenge the adaptation laws are suggested. Then for the problem of determining the controller parameters, Particle Swarm Optimization (PSO) algorithm is used. The performance of the proposed technique is investigated for an islanded microgrid under different disturbances, also to verify the advantages of the proposed controller, the results are compared with other controllers. Finally, the proposed controller and PID controller are implemented experimentally on Arduino mega 2560 microcontroller.

In this research, digital image processing method (DIPM) is used as an innovative approach to predict precisely the shape of electrical tree (ET) in cross-linked polyethylene (XLPE) power cables in the presence of air voids based on the field calculation using finite-element method (FEM). With the help of DIPM, two case studies are held to detect the accurate parameters of either the first initiated major branch or the tips of the major branches of ET. A hyperbolic needle-to-plane simulation model is proposed to illustrate the ET inception and propagation stages. The non-uniform electric fields thatare accompanied with the electrical treeing phenomenon are calculated using FEM as one of the most effective numerical methods to deal with non-uniform shapes. The predicted shapes of ET initiation and growth are provided in an innovative manner with the implemented hybrid connection between FEM and DIPM for the two proposed case studies. Direction branching approach and deviation angle branching approach are provided in this work to predict the shape and the direction of ET branched voids. The validity of the proposed model is assessed with the help of available previous experimental and simulation data.

A novel islanding detection technique by hybridising empirical mode decomposition (EMD) and multi-scale mathematical morphology (MMM) is proposed to detect the islanding condition in a distributed generation system to ensure personnel and equipment safety. The proposed method first uses EMD to efficiently separate the collected raw signal into the number of intrinsic mode functions (IMFs) with different frequency scales and the signal is reconstructed considering important IMFs which carry transient features for further analysis using their correlation coefficients. MMM is used for determining a ratio index named as MMMRI, the threshold value of the proposed MMMRI decides islanding and other power quality (PQ) disturbances. The proposed hybrid method name coined as EMD-MMMRI. The main motivation behind hybridising two signal processing techniques is to reduce detection time and improve accuracy. The efficacy of the method is demonstrated for different PQ disturbances and islanding events simulated on a grid-connected, heavily wind energy penetrated distributed generation system using MATLAB/Simulink environment. The test bench validation of the proposed technique is obtained through TMS 320C6713 Starter Kit (DSK) in digital signal processor platform. The efficacy of proposed work is demonstrated with large number of simulation studies.

Local blackout occurs when the transient stability limit is exceeded after a transmission line fault. As to global blackout, a recording of the 10 August 1996-WECC blackout shows that it was accompanied negative damping. A turbine-generator swinging against an infinite bus is used to approximate the dynamics leading to the WECC blackout. There is no analytic solution when non-linearity is included. Small-signal linearisation shows that negative damping can occur but cannot produce the waveform recorded in the WECC blackout. Therefore, the graphical phase-plane method, which is easy to use, is resorted to. The study shows that the kernel of non-linearity consists of the gradients which produce limit cycles. Positive or negative damping is produced by shifting the gradients of the limit cycles to the right or left in the direction of the trajectory. The study makes a contribution by showing that phase plane can be used to study the impact of multiple independent controllers. A worked example shows when transient stability limit is exceeded, local blackout occurs. The swing equation of local blackout is applied to the WECC blackout. As proof that negative damping was due to non-linearity, a waveform having the frequency of the recorded WECC blackout is presented.

With the integration of more and more renewable energy generations (REGs), the structure of traditional distribution networks is hard to accommodate the volatile power injections of REGs. As a new power electronic device, soft open point (SOP) can be installed to control both active and reactive power flow among active distribution networks (ADNs). This paper presents a comprehensive optimization method for allocating SOPs within an ADN with high penetration of REGs. In order to find proper SOP candidate locations, a selection strategy based on two technical indices is proposed. To mitigate the risk of voltage violation caused by REG forecast errors and improve the adaptiveness of allocation results, a two-stage robust optimization model for SOP allocation is formulated to minimize the total cost of SOP investment and network operation. The proposed model is converted into a mixed-integer second-order cone programming (MISCOP) problem, which is then decoupled into a master problem of planning and a subproblem of operation and solved by column and constraint generation (CCG) algorithm. Simulation results show that the proposed method can effectively find the optimal SOP allocation schemes. Comparisons with different mathematical formulation and solution methods show the advantages of the proposed method.

Cooperative microgrids (CMGs) can effectively solve the energy interaction between microgrids (MGs) while increasing the penetration rate of renewable energy systems (RESs) and reducing the interaction frequency with the grid. However, the uncertainty of RESs will bring new challenges to the energy management and economic dispatch of CMGs, especially in increasing the number of MGs connected to the grid. Taking into account this uncertainty, it is extremely unlikely that the forecast uncertainty information will be at the worst values in every period, and this forecast uncertainty information is near the expected values in most cases. Therefore, a two-stage robust optimal model under expected scenarios for CMGs is proposed in this study to improve the conservatism of traditional models and minimise the daily cost. In this model, the first-stage decision results (FDRs) are determined by minimising the daily cost of CMGs under the expected scenarios. The proposed model is transformed based on two-stage zero-sum game theory and dual theory, a column and constraint generation algorithm is first used to test the robust feasibility of the FDR, and the second-stage decision results can be obtained without changing the FDR. Case studies verify that the proposed model can effectively solve energy transactions between MGs while mitigating the uncertainty disturbances in the operation of CMGs.

Flexible DC distribution system has become the research and development trend of the future distribution network with its unique advantages such as high efficiency and flexibility. However, the DC fault identification and protection is challenging due to the fact that the short-circuit current provided by converters is limited and last for a very short period, how to identify and isolate faults reliably using limited fault transient information becomes a serious problem faced by system protection. Based on the analysis of the fault characteristics of three typical faults in the DC distribution system, the setting principle and the calculation methods are proposed, and the reasonable range of protection setting boundaries is derived. According to the requirements of protections, the parameters of the actual DC distribution system are used for setting calculations, and a complete set of DC line protection schemes is designed in this study. Finally, the performance of the proposed protection scheme is verified in PSCAD/EMTDC simulation platform, the built simulation model has been successfully applied to the analysis and calculation in the commissioning of the DC distribution system.