This study presents a new wide-area voltage stability monitoring method using synchronised phasor measurements. The salient features of the proposed index are the following: (i) It ensures constancy, which is the ability to maintain the same scale even if the system changes. (ii) It is pseudo-linear with respect to the power system stability level, which enhances intuitiveness for real-time operation. Accordingly, stability can be uniformly compared in various situations, and thus, the index can be used as a solid criterion or threshold point for system operation. A verification study of the proposed index with regard to constancy is carried out using Korean power system operation data. Furthermore, an implementation of the proposed method for the Korean wide-area monitoring system is presented, and it is demonstrated that the proposed index detects event more clearly than previous stability index through an actual event measured using phasor measurement units.

A novel quasi-oppositional-based salp swarm algorithm (QSSA) is used to obtain the optimal values of controllers for automatic generation control of the two-area, assorted source of the generation-based power system. Thermal, hydro, and gas generating units are considered in the power system. Optimal values of proportional–integral–derivative (PID) controllers obtained using SSA and QSSA are compared with that of PID controllers based on differential evolution, teaching learning-based optimisation, and imperialist competitive algorithm. Observing the superiority with a QSSA-based PID controller, the study is protracted to obtain the optimal values of two-degree-of-freedom conventional PID (2DOF-PID) and 2DOF fractional order PID (2DOF-FOPID) controller with SSA and QSSA techniques. It is evidenced that QSSA outperforms SSA and also the QSSA-based 2DOF-FOPID controller establishes a better dynamic response than other controllers. 2DOF-FOPID controller is also employed for the system with generation rate constraint (GRC). The complete analysis is carried out by applying a step load disturbance of 1 p.u. in area-1. Robustness of the controller is verified by varying the systems' parameters and a randomly varying loading pattern in both areas with and without GRC. In both cases, the proposed QSSA-based 2DOF-FOPID controller is found firmly robust.

This study investigates the impact of embedded voltage source converter-based high voltage direct current (VSC-HVDC) links on AC grids transient stability. Firstly, using transient energy functions, it is demonstrated that VSC-HVDC links controlled to track constant power references, do not inherently improve transient stability of the surrounding AC grid as an AC line naturally does. Then, a control law using the feedback linearisation technique on a simple but representative power system is derived. The control law highlights and combines the three main actions the VSC-HVDC link can offer to enhance rotor angle stability: fast power reallocation, injection of synchronising power and injection of damping power. The control law is implemented and validated in EMT simulation. It is then shown that an HVDC link can assure the synchronisation of different AC areas even if no AC transmission lines interconnect them. Through another case study, it is shown how the HVDC link can help to share dynamic frequency reserves to not jeopardise the stability of the system. The last example investigates the effect of a DC fault on AC transient stability and how the control can help improving the system response.

In this study, power quality (PQ) improvement has been addressed, in the form of total harmonic distortion (THD) minimisation, as well as, voltage regulation using two cascaded schemes. The first scheme is the optimised triple action controller (TAC)-based pulse width modulated voltage source inverter. TAC consists of a proportional resonant controller, selective harmonic compensator, and a new added current-assisted feed forward controller. The second scheme is the optimised cascaded dual-level control of a standalone microgrid. Cascaded level control consists of droop, secondary, and synchronisation control loops. The two approaches have been optimised for best parameter selection out of the possible solution space using a particle swarm optimisation algorithm to satisfy the study objectives. The optimisation objectives/constraints were to minimise THD and minimise overshoot/undershoot, rise time, and steady-state error for voltage compensation under two disturbance scenarios, sudden load change, and voltage flicker injection as a power frequency disturbance. These research results have been compared to other existing simulation and experimental work. The results proved to be better in output voltage, frequency, response time, and THD. Furthermore, the proposed schemes ensure power factor improvement, high efficiency, overall system PQ, and reliability at various load conditions.

This study presents a single stage grid-interfaced solar photovoltaic (SPV) system using a multifunctional complex coefficient reduced ordered generalised integrator (CC-ROGI) based frequency-locked loop (FLL) control. The main contributions of this study, include (i) the extrication of fundamental active components from load currents using CC-ROGI-FLLbased control to generate the reference grid currents for voltage source converter (VSC) switching, (ii) VSC works as a distribution static compensator, which performs multi-functions like harmonics mitigation, reactive power compensation, unity power factor operation and grid currents balancing, (iii) this CC-ROGI-FLL also extricates the fundamental grid voltages component even under grid voltage harmonic distortion and grid voltages unbalancing. Moreover, SPV power feed-forward component is assimilated in this control to reduce the oscillations in grid currents under variable irradiance. Simulated and experimental results show satisfactory behaviour of the system at different conditions like load unbalancing, variable solar irradiance and abnormal grid conditions. The comparative performance of CC-ROGI-FLL control with other FLL and phaselocked loop controls are shown in this study. This CC-ROGI-FLL control has manifested a good steady state performance and dynamic response. The total harmonic distortions of grid currents are found well within the limits of the IEEE-519 standard, even under abnormal grid conditions.

The contamination of outliers severely damages the data quality, resulting in the inaccurate data-driven optimisation model. This study proposes a data quality aware chance-constrained model for the direct current optimal power flow (DC-OPF) problem under uncertainties. Under the framework of Bayesian statistics, the variational Bayesian Gaussian mixture model (VBGMM) is employed to extract the probabilistic information from the available historical data, i.e. realisations of random variables. VBGMM can identify the outliers by capturing their probability characteristics, in which way improving the data quality. Notably, VBGMM automatically determines the number of components, which is a remarkable difference from the conventional Gaussian mixture model. In addition, based on the affine policy, a method integrating VBGMM with chance-constrained programming is proposed to make VBGMM scalable. The proposed method is firstly tested on a 6-bus system for an illustrative purpose, and then on a 118-bus system for validating the potential practical application. Comparative studies verify the effectiveness of the proposed method.

The cooperative characteristics of resistive superconducting fault current limiters (R-SFCLs) and DC circuit breakers (DCCBs) have been investigated with regard to the fault clearing in modular multilevel converter (MMC)-based multiterminal direct current (MTDC) grids. However, research is lacking in complete protection solutions that combine R-SFCLs and mechanical DCCBs while considering the backup protection and the effect of R-SFCLs on the fault characteristics of MMCs. This study investigates a fault current breaking scheme that includes primary and backup protection. Moreover, the fault characteristics of MMCs with R-SFCLs are analysed, and the fault transient process is divided into three stages. Then two fault current limiting schemes with R-SFCLs located at the converter output or the line are proposed. These two protection schemes are applied to the DC test system, verified and compared. The results show that in both schemes, the size of the designed R-SFCL should be generally a few tens of Ω. These R-SFCLs maintain the converters unblocked until the primary breakers or backup breakers interrupt the fault currents, and the M-DCCBs are only required to break several kA currents. After a fault occurs, the system will restore within 200 ms for primary protection or 250 ms for backup protection.

The service restoration is a vital measurement to enhance the resilience of the electrical distribution network. With the integration of distributed generations (DGs) in the distribution network, the uncertainties are introduced, which have a considerable impact on service restoration. Meanwhile, the soft open points (SOPs) are electronic devices installed in the tie-line of the distribution networks. They have the ability to control the branch power flow, which can be utilised to assist the service restoration. This study proposes a data-driven stochastic and robust service restoration method to handle the uncertainties of DGs outputs, which is modelled as a two-stage conic optimisation programming problem. The non-parametric estimation method is introduced to estimate the probability density function of forecasted error based on historical data. Furthermore, the nonlinear constraints of the SOPs are reformulated into conic forms so that the proposed model could be solved efficiently. Numerical tests are carried out on the IEEE 33-bus and 123-bus distribution networks to show the effectiveness of the proposed method, and the results show the superiority of the proposed method.

The charging coordination of large-scale electric vehicles (EVs) for avoiding the voltages at some nodes to drop below feasible ranges in distribution networks, which is formulated as a class of optimisation problems with a certain class of coupled constraints, is studied. Then the alternating direction method of multipliers (ADMM) is introduced to obtain the optimal charging strategies. However, due to the non-separable property of the objective function which includes a non-linear term of the total charging power of EV populations, it is difficult to decentralise the update step of the charging strategy in the ADMM method. Consequently, a novel decentralised hierarchical method is proposed by further developing an iterative update of best responses of individual EVs at each iteration step of the proposed ADMM method, such that individual EVs can implement the coordination behaviours locally and simultaneously without sharing any other private information except the charging power. Furthermore, the proposed approach does not require the objective function to be continuously differentiable. The convergence and optimality of the proposed method are verified and some numerical simulations are studied to illustrate the developed results.

The wide proliferation of renewable energy and deregulation of power grid systems require small power utilization systems to deploy intelligent methods of adjustment to the user power demand. To accomplish this goal, the smart power demand forecasting and power consumption optimization methods and algorithms need to be developed. For this purpose, small power utilization systems can benefit from the techniques developed for the smart grid in general. The present paper is devoted to the development of a forecasting model based on the Long Short-Term Memory (LSTM) method and an optimization model based on Genetic Algorithm (GA) adopted for the use in home energy management systems (HEMS). The present work describes a smart microgrid architecture with a focus on LSTM and GA. The experiments demonstrate that the developed algorithms generate a stable pattern of daily power demand. The use of the developed algorithms allows automated shifting of power to achieve the lowest price without sacrificing their comfort. The main contributions of the present work are the inclusion of all parts of the smart microgrid architecture (non-invasive load identification, forecasting, optimization, renewable energy sources and storage elements) in the research proposing a fully automated control in HEMS rather than recommendation based only.

At present, most of the virtual power plants’ (VPPs) networks are static networks, which cannot effectively describe the characteristics of the distributed generation in VPP. Therefore, a hybrid VPP network with static–dynamic nodes is constructed by simulating the charging and discharging time series characteristics of electrical vehicles. The influence of timing characteristics on VPP topology is studied, and the complex network characteristics of static–dynamic hybrid VPP network are analysed. The experimental results show that the sequential network can describe the characteristics of VPP network completely, improve the accuracy of VPP real-time recognition, and verify the effectiveness of complex network method in analysing sequential VPP.

This study presents a probabilistic transmission expansion planning model incorporating distributed series reactors, which are aimed at improving network flexibility. Although the whole problem is a mixed-integer non-linear programming problem, this study proposes an approximation method to linearise it in the structure of the Benders decomposition (BD) algorithm. In the first stage of the BD algorithm, optimal number of new transmission lines and distributed series reactors are determined. In the second stage, the developed optimal power flow problem, as a linear sub-problem, is performed for different scenarios of uncertainties and a set of probable contingencies. The Benders cuts are iteratively added to the first stage problem to decrease the optimality gap below a given threshold. The proposed model utilises the Monte Carlo simulation method to take into account uncertainty of wind generations and demands. Several case studies on three test systems are presented to validate the efficacy of the proposed approach.

This study presents a dynamic equivalent method of wind farms with permanent magnetic synchronous generator (PMSG) wind turbines for power system stability analysis. First, a novel clustering indicator is set up based on the morphology similarity distance and cosine similarity between trajectories with the measurable output characteristics time series of wind turbines, and the K-means algorithm is applied to cluster the PMSGs. Combining silhouette coefficient, the robustness analysis of the clustering method under different scenarios is adopted. In each cluster, a trajectory sensitivity based key parameters selection is introduced to reduce the control parameters to be identified. Moreover, a multi-objective adaptive function is established and the multi-controllers aggregated parameters are optimised by adaptive evolutionary particle swarm optimisation algorithm. Thus, a wind farm model represented by multi equivalent wind turbines is obtained. The IEEE 39-bus system with a PMSG-based wind farm is used as test system to verify the validity of the proposed dynamic equivalent approach in time domain and frequency domain, respectively. It has been demonstrated that the proposed model can reduce the model complexity and improve the calculation efficiency of wind farms.

In the distributed load frequency control (DLFC) scheme, the compromised areas by attackers may endanger the stable and reliable operation of the entire power system. A credibility-based secure DLFC strategy is in this work proposed to sustain the stable operation of the power system under false data injection attacks. In this secure DLFC method, the gradient-variation-based credibility metrics are defined to detect potential attacked measurements. Then, the communication isolation decisions are made based on the adaptive thresholds. To compensate the impact of the communication isolation of misbehaving areas, predictions of future measurements by using the average gradient variation of stored healthy data are feeded back to the area controller. Simulation results of a four-area power system show the proposed secure DLFC can identify and cut off the communication of the misbehaving areas and still maintain the stability of the power system.

Accomplishing highly reliable distribution grids is more and more important to today's modern society. Along the same line, self-healing is one of the most distinguishing features of the smart grid that could improve the reliability of the system up to a logical extent. In this study, the reliability of the electrical distribution grid has been improved by optimal allocation of automatic switches and parking lots (PLs). Thus, the optimal places of switches and PLs are determined with the purposes of minimising a combined effect of the customer-based (system average interruption duration index) and cost-based [total reliability cost (TRC)] reliability indices. The TRC includes customer interruption costs, PLs and automatic switches investment costs, and the total cost of PLs incorporation in the service restoration process. The proposed approach is implemented in three different planning scenarios: switch placement, PL placement, and joint switch and PL placement. The particle swarm optimisation method is employed to solve optimisation problems. Finally, a standard reliability test system bus number four of the Roy Billinton test system (RBTS 4) is used to demonstrate the efficacy of the proposed method.

This paper presents photovoltaic (PV) system control as distributed static compensator (DSTATCOM), termed as PV-DSTATCOM, operated with active current control (ACC) and feed-forward control loop (FFCL). Besides active power injection into the utility grid, the proposed PV system autonomously transforms into a DSTATCOM to provide various ancillary services including source current harmonic suppression, load reactive current compensation, zero sequences component mitigation, and power factor correction. Since PV-DSTATCOM operates with ACC, it precisely extracts the fundamental in-phase and quadrature components of current. It introduces high-gain at the third-order harmonic and thereby alleviates stationary errors in the current control loop of PV inverter. The proposed ACC+FFCL structure is computationally efficient and unconditionally stable. Practically, FFCL addresses the challenges emerged due to nonlinearity introduced by the PV unit and ensure a rapid power balance between the PV unit and electric grid. Further, a simplified perturb and observe based maximum power point tracker has been employed to evacuate the maximum power from the PV array. The proficiency of the developed ACC+FFCL structure is investigated through a comprehensive set of transient studies using MATLAB/Simulink software. Finally, a laboratory setup has been developed using the dSPACE-1104 platform and experimental results are recorded with detailed comparative evaluation.

The transition from conventional towards renewable energy systems requires additional transmission capacities and higher operational flexibility to overcome contingency situations. This study presents a novel transmission expansion planning approach for the simultaneous placement of AC systems and power flow controlling technologies including high voltage direct current, phase shifting transformers (PSTs) and thyristor controlled series compensators (TCSCs). The approach is formulated as a mixed-integer linear programming optimisation problem and the operating point of power flow controlling devices is endogenously determined by minimising expansion costs. Both PSTs and TCSCs are integrated into the optimisation problem by means of new mathematical formulations. PSTs are presented in more detail considering the PST impedance, which is modelled as an equivalent phase shift. The controllable series impedance of TCSCs is also represented as an equivalent phase shift. Exemplary results based on a synthetic 120 bus system show a significant potential of PSTs and TCSCs to reduce expansion costs as well as to lower the requirement for new transmission capacities. The simultaneous employment of these technologies reduces the expansion costs within the test system between 18.7 and 32.4% compared to those costs generated by the sole reinforcement by AC systems.

Transmission networks consist of thousands of branches for large-scale real power systems. They are built with a high degree of redundancy for reliability concerns. Thus, it is very likely that there exist various network topologies that can deliver continuous power supply to consumers. The optimal transmission network topology could be very different for different system conditions. Transmission network topology control (TNTC) can provide the operator with an additional option to manage network congestion, reduce losses, relieve violation, and achieve cost-saving. This study examines the benefits of TNTC in reducing post-contingency overloads that are identified by real-time contingency analysis (RTCA). The procedure of RTCA with TNTC is presented, and two algorithms are proposed to determine the candidate switching solutions. Both algorithms use available system data: sensitivity factors or shifting factors. The proposed two TNTC approaches are based on the transmission switching distribution factor (TSDF) and flow transfer distribution factor (FTDF), respectively. FTDF-based TNTC approach is an enhanced version of the TSDF-based TNTC approach by considering network flow distribution. Numerical simulations demonstrate that both methods can effectively relieve flow violations and FTDF outperforms TSDF.

The frequency responses of a power system following a generator outage are closely related to the commitment states of generators, which describe the droop and inertial characteristics and system pre-contingency power dispatch. This study presents a new model to estimate the transient and steady state frequency responses of two-area power systems at any moment following the loss of an online generator. In the proposed model, the deviations of tie-flow, area frequencies and rate of change of area frequencies as well as the extreme values of these functions and their associated time of occurrence following the outage of a generation unit are derived as modified analytical functions. A new approach is also proposed to linearise the modified extreme deviations based on pseudo-Boolean function theorem. In addition, a frequency-constrained unit commitment model with modified frequency-dependent constraints incorporating primary frequency regulation reserve is presented as a mixed-integer linear programming problem. The results indicate that the proposed method gives acceptable approximations for post-contingency responses and can ensure power system security from frequency viewpoint.

Resiliently designed and constructed integrated gas-electric distribution networks (GEDNs) against natural disasters are crucial to social welfare. In this study, a two-stage robust optimisation-based co-expansion planning model is proposed to attain an integrated GEDN with a given resilience level, by optimising the investment strategies of hardening and selective expansion of power distribution feeders and natural gas pipelines, as well as the location and capacity of natural-gas-fired distributed generation. In the first stage, the overall annual investment and operation cost is minimised under normal operation conditions while in the second stage, the feasibility of the investment decisions under the identified worst-case natural disaster scenario is checked with an adjustable load shedding cost criterion. The proposed model is formulated as a mixed integer second-order cone programming problem with the column and constraint generation algorithm employed to seek the optimal solution. Case studies on two integrated GEDNs demonstrate the performance of the proposed methodology.

In this study, model predictive control (MPC) with constant switching frequency is proposed for four-leg distribution static compensator (FL-DSTATCOM) to compensate the current related power quality issues. MPC techniques having many advantages compared to conventional pulse width modulation and hysteresis control techniques. In MPC, the future behaviour of the controlled variable is predicted using the model of the system and a cost function is formed using reference and predicted variable. MPC for DSTATCOM applications consider the difference between the reference and actual DSTATCOM current as a cost function and selects the switching state which minimises the cost function. However, while using MPC, the switches of DSTATCOM operate in variable switching frequency and sometimes the values are also very high. Due to this reason higher switching losses, unequal stress appear across the inverter switches and it also reduces the lifetime of the switch. Therefore, in this study, the concept of three-dimensional space vector modulation is adopted to achieve a constant and user-defined switching frequency MPC for FL-DSTATCOM to conquer the limitations of conventional variable switching frequency MPC. The validation of the proposed work is achieved using simulation and experimental studies.

Power systems have to be reinforced to accommodate a high penetration of renewable energy sources. Recent research shows that the stability margin of the grid degrades with the penetration of grid-tied photovoltaic generators into the grid. In the model presented in the study, the critical level of photovoltaic penetration is associated with a Hopf bifurcation in the field dynamics of the synchronous generators which severely limits the operating domain of the grid. It is shown that the judicious introduction of synchronous condensers in the modelled grid delays this dynamic instability. A small-signal analysis is performed for a system where the reactive power and inertial response is supplemented using a synchronous condenser. The study shows that the modified network tolerates much higher participation of photovoltaic generation in the grid. It is shown that the modified network retains the classical power system control approach and also does not demand a change in the way the photovoltaic generation is injected, thereby making it a natural implementation. The synchronous condenser augments the operational domain of the system significantly, nearly eliminating the need for renewable energy curtailment. A case-study approach is used to present results on improvements in damping ratio, feasibility domain and transient stability.

Hybrid AC/DC microgrid is regarded as a low inertia system due to the extensive integration of renewable energy sources. Thus, the AC bus frequency and DC bus voltage are easily damaged when a step change or random fluctuation appears, which threatens the system power quality. Focusing on this problem, this study proposes an adjustable inertia implementing method for the two-stage bidirectional power converter (BPC) to enhance the dynamic performance of the hybrid power system. Concretely, the first stage of the BPC is controlled as a virtual synchronous generator to support the AC subgrid and plays the role of imitating the inertia frequency response in the AC bus. The second stage controls the built-in capacitor of the BPC to implement adjustable inertia for the DC subgrid and improves the DC bus voltage response. Besides, the terminal voltage of the built-in capacitor will be restricted to ensure the normal operation of the BPC. The small-signal analysis of the hybrid system is provided to illustrate the stability of the proposed control method. Finally, the experimental results based on the real-time hardware-in-loop platform demonstrate the effectiveness of the proposed method.

An artificial neural network (ANN) architecture for real-time estimation of available transfer capability (ATC) has been reported in this study. The real-time data obtained from phasor measurement unit (PMU) is utilised to generate target output (ATC) using the pattern search optimisation-based method. The set of information provided as input to the pattern search-based ATC optimiser along with its output forms the input and target output for ANN training. The input information consists of active and reactive power injected along with voltage and current vectors measured at PMU buses. The ATC optimiser is functional as long as ANN is under training. Once the ANN is trained, it receives input set directly from PMU and produces ATC values. PMU emulation is employed for archiving the PMU data. The proposed method is tested on modified IEEE 24-bus, IEEE 30-bus, and IEEE 118-bus test system. The proposed method has also been implemented on real-time digital simulator.