This study presents a simplified control algorithm for constant active power delivery to a weak-grid/standalone load from a variable speed-wind energy conversion system (VS-WECS). The proposed system consists of a permanent magnet synchronous generator (PMSG)-based WECS connected to a weak-grid/standalone through a direct matrix converter-based solid-state transformer (SST) along with a bidirectional buck–boost battery energy storage system (BESS). The power from the WECS is processed through the SST using Venturini-based control algorithm together with the voltage-oriented control scheme. This scheme effectively regulates active and reactive power as well as voltage gain of the SST. Wind turbines maximum power point tracking power curves are used to set reference for active power. While the reference for reactive power is taken as zero. The bidirectional buck–boost-based BESS is used to smoothen the power generated by the PMSG-based VS-WECS. It absorbs the surplus power from the WECS during over generating period and delivers power back under power shortage period. To validate the performances of the proposed scheme, extensive simulation has been performed and exclusive hardware built by dSPACE1104 using MATLAB/Simulink.

With development of two-way communication technology, residential users are able to reshape their energy consumption patterns based on demand response signals. This study proposes an optimal residential energy resource scheduling model to minimise the home electricity cost while fully considering the user's life convenience, the user's thermal comfort, and renewable uncertainties. The proposed model accounts for the characteristics of shiftable appliance, air-conditioning system, electric vehicle's charging pattern, and renewable generation of both wind and solar power. Wasserstein distance metric and K-medoids-based scenario generation and reduction techniques are used to address the renewable uncertainty. An adaptive thermal comfort model is employed to estimate the user's indoor thermal comfort degree. A waiting cost model is applied to measure the user's preference on the household appliance's operation. In addition, a recently proposed metaheuristic optimisation algorithm (the natural aggregation algorithm) is used to solve the proposed model. The simulation results show the proposed model is effective in minimising the household's daily electricity bill while preserving the user's comfort level.

In the literature, many works detail the benefits of Volt-VAr control to minimise the losses in a distribution system. However, it is also important to understand the impact of it on the life of the other assets in a distribution system. Since, distribution transformers (DTs) are the important assets of a distribution system, the main objective of this paper is to appraise the impact of Volt-VAr control on the life of DTs. The paper presents a detailed methodology to estimate the loss of life (LoL) of the DTs under various Volt-VAr control schemes, such as base-case (without any control), voltage control, and Volt-VAr control (VVC). The proposed methodology is implemented on modified IEEE 13-bus and IIT-Roorkee distribution systems considering the voltage-dependent load models, seasonal load influences, and harmonics. The simulation results are presented to explore the ability of VVC in reducing the hottest-spot temperature in the DTs during peak hours. The results reveal that the life of the DT can be extended by a considerable amount by optimally controlling the voltages and reactive power flows in the distribution system. Moreover, it gives a significant reduction in energy losses and improvement in power factor in distribution systems.

Nowadays, with the development of distributed energy resource (DER) technologies, various DERs would be widely applied to residential houses. By integrating electricity, thermal energy, natural gas, and other forms of energy into residential sectors, it provides an opportunity for energy users to exploit the complementarity of multi-energy resources. However, it is also a formidable challenge for users to manage such a multi-energy system (MES) designed for residential houses. The authors propose an integrated architecture for residential MES incorporating multi-energy resources, such as electricity, thermal energy, natural gas, and renewable energy. Besides, an optimisation model for MES is developed for coordinating energy generation, storage and consumption devices, and minimise energy cost under time-varying pricings. Additionally, the thermal comfort level is considered. An International Organization of Standard for the thermal comfort model is employed to precisely estimate and maintain residents' thermal comfort. The interaction among multiple energies is investigated via the model. The results show that the proposed model can offer significant cost-saving while maintaining user comfort through optimal scheduling of household devices and management of multi-energy sources.

This paper presents a multi-time hierarchical stochastic predictive control (MHSPC) scheme for an island microgrid, in which electric vehicles (EVs) can be used as mobile energy storages to improve power balance and realise load-frequency control (LFC) with micro-turbines (MTs). At the upper layer, a stochastic model predictive control is proposed to handle the EVs uncertainties on a long time scale, while optimising controllable power adjustment of MTs, the charge/discharge energy of the battery electric storage (BES) unit and guaranteeing EVs to be fully charged at the expected plug-out time. At the lower layer, the coordination between EVs and MTs for LFC is achieved by a standard MPC framework on a short time scale. In this way, the power balance is met, and the frequency fluctuation is inhibited. Finally, simulation results are presented to illustrate the satisfactory operation of the island microgrid.

Recent complexities in interconnected power system operation call for more efficient and fast approaches for operational problems including network-constrained unit commitment (NCUC). In this study, an algorithm called period-elimination Benders decomposition (PEBD) is proposed to enhance the computational efficiency of AC NCUC problems. After linearising the AC NCUC, two subproblems (SPs) are defined to ensure power balance at buses as well as constraints of branches and inter-regional transactions. In the classical Benders decomposition (BD), all time periods are solved at all iterations up to convergence. However, in the proposed PEBD, a time period that satisfies a SP in an iteration is eliminated from the solution procedure of that SP at next iterations. After both SPs are satisfied for all time periods, the solution is checked for interrelation constraints and a few more iterations may be needed to finalise the solution. The efficiency and accuracy of the proposed PEBD method are verified by examining it on two test systems. It is found that the PEBD greatly enhances the speed of NCUC, especially in larger power systems due to eliminating unnecessary calculations for satisfied time periods.

This paper presents a new technique for very high speed detection of fault during power swing on a hybrid transmission line consisting of an overhead line and an underground cable. The wavelet packet transform with the mother wavelet db1 is utilised to segregate the high-frequency components from three-phase current signals recorded at the relay point and a fault detection index is calculated using these components to detect faults during power swing. The proposed method is tested on a 400 kV double circuit transmission system and a 400 kV 3-machine 9-bus Western System Coordinating Council system simulated in electromagnetic transient program software for both symmetrical and asymmetrical faults, different fault resistances, load angles, and fault inception times at random locations on the transmission line. Its performance is also analysed for close-in faults, high dc offset current, and the faults on the series compensated transmission line. The method is very fast to detect faults during power swing irrespective of the variations of fault conditions, and a comparative assessment with the existing methods justifies its merit.

The stability and control performances of grid-connected inverters can be significantly influenced due to the uncertain grid impedance and large grid voltage background harmonics. The system stability and resonance of the grid-connected inverter were investigated separately. Thus, their relationship needs to be identified further. In this study, the equivalent impedance model and the current control model of the grid-connected inverter are established. Based on the three resonance cases: positive incomplete resonance, complete resonance, and negative incomplete resonance, the relationship between the system stability and resonance is identified. Moreover, the principle of harmonic amplification of the grid injected current is analysed thoroughly. It is revealed that the harmonic amplification is always accompanied by low stability of the system, and the centre frequency of harmonic distribution is where the system has the lowest stability. In order to alleviate the harmonics of the grid injected current, it is inevitable to ensure that the system maintains a sufficient phase margin to thwart the grid voltage background harmonics and the inverter output voltage harmonics. Finally, the simulation has been accomplished in MATLAB/SIMULINK software, and the hardware platforms are built with a single phase grid-connected inverter in order to verify the proposed comprehensive analysis further.

This study develops a model predictive controller for single-phase distributed generator with seamless transition between the grid and off-grid modes of operation. In addition, a simple synchronisation mechanism is developed to achieve the smooth transition between the grid and off-grid modes, thereby avoiding the complex multi-loop controls. The voltage vectors, hence the switching pulses are generated by using space vector modulation technique based on the minimisation of the cost function of the predictive model. The two cost functions considered are instantaneous power errors and instantaneous voltage errors, respectively, for the grid and islanded operation of the single-phase generator. The performance of the developed controller for feeding the set-point powers in grid connected mode and serving the load at nominal voltage and frequency in off-grid mode is verified using simulations. The simulation results are experimentally validated on a prototype.

Here, a novel approach is proposed to compute discrete value of converter tap position in AC/DC hybrid multi-infeed HVDC power flow solution. The approach is based on Newton–Raphson (NR) technique and sequential power flow method. An algorithm for the estimation of discrete tap position is devised by re-converging DC system to eliminate the error between discrete tap position and actual value of tap. The proposed technique computes new value of gamma for discrete value of tap which solves convergence problem of DC system caused by AC-voltage fluctuations. Theoretical bases and numerical results are presented to support new proposed approach. The technique is successfully applied to dual-infeed LCC HVDC feeding into the same AC system which is more practical scenario. The results validate the approach and show advantages in term of accuracy and convergence.

A microgrid is a well known solution to increase the technical and economical capability of distributed generations. Recently, DC microgrids, as small-scale DC networks, have attracted more attention due to lower losses and simple control structure. Stability of DC microgrids can be an important issue under high penetration of constant power loads (CPLs). In this study, stability analysis of the DC microgrid system including hybrid wind/battery and CPLs is studied, and then three different types of stabilising compensators are presented in two groups to increase the stability margin and to stabilise the system under high penetration of CPLs. The proposed stabilising compensators modify the voltage reference, current reference and duty cycle by adding active damping signals in the external, middle and internal parts of the interfaced converter control loops. These active damping signals are obtained by the feedback of the output voltage and current and modify the DC microgrid control structure. To evaluate the system stability under different stabilising compensators, small signal and frequency response analyses are done with and without active damping signals. Simulation results based on a detailed DC microgrid model are given to verify the effectiveness of the proposed compensators.

The randomness of new energy generation and variation in load demands bring uncertainty to large AC/DC grids. Traditional deterministic power flow equations have difficulty coping with the uncertainties of new energy generation and load. Here, an affine arithmetic (AA)-based uncertainty power flow algorithm for hybrid AC/DC grids incorporating voltage source converters (VSCs) is presented. VSC station and DC grid models are established using AA. Diverse VSC control modes are considered in the power flow iterations. A comparison using the Monte–Carlo method shows that the proposed algorithm is able to obtain a feasible solution. The proposed method can be used by power system operators and planners to monitor and control AC/DC grids under various uncertainties.

With the increasing penetration of renewables in power systems, frequency regulation is proving to be a major challenge for system operators using slower conventional generation, and alternative means to provide faster regulation are being actively sought. The participation of demand side management in ancillary service provision is proven in some energy markets, yet its full potential to benefit frequency regulation, including the exploitation of fast power ramping capability of some devices, is still undergoing research. In this study, a novel approach to improve the speed of response of load frequency control, a secondary frequency control approach is proposed. The proposed control is enabled by an effective location identification technique, is highly resilient to anticipated system changes such as reduction of inertia, and enables fully decentralised power system architectures. The effectiveness of the approach is demonstrated and compared to that of present day regulation control, by means of real-time simulations incorporating appropriate time delays conducted on a five-area reduced model of the Great Britain power system. The applicability of the method is further proven under realistic communications delays and measurements experimentally using a controller and power hardware-in-the-loop setup, demonstrating its critical support for enabling the stable operation of future power systems.

Based on theoretical studies and practical experiences in power systems, electricity market by itself cannot create an effective condition for optimal investment in generation capacity (GC) expansion. On the other hand, the political, social, and economic consequences of shortage of power generation are inevitable under any condition. Thus, several incentives have been introduced to support investment in GC. Currently, the capacity payment mechanism is used for this purpose in the Iranian power market. In addition, the mechanism, along with its benefits, is suffering from some inadequacies and inefficiencies. The present study aimed to introduce Iranian power market and the specifications of the capacity mechanism used in this market. Accordingly, a new incentive called ‘Capacity Certificate’ which has been adopted for Iranian power market is modelled and analysed, along with explaining its characteristics. Regarding the advantage of system dynamics, the effect of this mechanism on the long-term performance of the power market was evaluated from the perspective of the GC expansion and was compared with the capacity payment mechanism. The results revealed that using the capacity certificate mechanism in Iranian power market can be considered as a step forward toward a better system reserve and lower cost.

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.

This paper outlines a Hamiltonian energy-balance function for computing stable and unstable regions of power systems. Once the generator model is defined, a certain number of variables (holonomic constraints) specifies its state properties (prefault, fault-on, and postfault) entirely. The change between the postfault (final) and prefault (initial) states is expressed by an energy balance equation (crucial for solving many dynamical problems). State equations (instead of swing equation) with the properties (or functions) of the system are built using the prefault and postfault energies (kinetic and potential) of the generators. When a large disturbance occurs, the ‘migration’ from one state to another is computed using concepts of least action principle, conservation, and dissipation of energy, perturbation theory and calculus of variations. The method is tested with two electric power systems, where the classical model represents the synchronous generators. Prefault, fault-on, and postfault regions are clearly characterised on 3D energy surfaces indicating whether the generators remain (or not) stable after a fault in the power system. The trajectories of the Hamiltonian energies of the generators are projected on 2D planar projection maps. The results provided important insights into transient stability problems not seen so far.

Microgrids play an important role in modern power systems which can integrate different kinds of distributed energy resources (DERs). To deal with the uncertainty from various factors such as renewable generation, robust energy management for microgrids has become a significant problem. In this work, a novel multistage robust energy management model for grid-connected microgrids is developed which considers the uncertainty of renewable generation and load demand. The multistage energy management problem is complex and computationally difficult. To solve this problem, a robust version of dual dynamic programming method is proposed which includes a forward pass and a backward pass procedure and has a similar framework with the common stochastic dual dynamic programming (SDDP) method. Based on real datasets, a case study is carried out to validate the effectiveness of the proposed model and solution methodology. Numerical results show that the proposed approach can effectively achieve the robust optimal solution, and the comparison with other methods also testifies the advantage of the proposed multistage robust model.

In polistic electricity market structure, each power producers can maximise its profit through bidding strategy. Also, with the advent of renewable generation mostly wind has shaped a new prospect in the bidding process. Although, the wind power output uncertainty, wind power suppliers facing an inevitable uncertainty problem in an emerging power market. To alleviate the adverse impact of this uncertainty on wind power bidding, Weibull distribution is used to model wind power scenarios and the forward-reduction algorithm is utilised to reduce scenarios. Furthermore, an overestimation and underestimation cost function is modelled to measure the deviation of wind power output. The bidding strategy with the inclusion of wind power is proposed in this study to maximise profit. However, the uncertainty of rival's behaviour affects the bidding process, which minimised by utilising the normal probability distribution function. The proposed problem is tested on the IEEE standard 30-bus and 57-bus systems and solved by the gravitational search algorithm (GSA). The results are obtained without and with wind power and shows that the effects of wind power on market clearing price and bidding strategy. Moreover, GSA gives higher market clearing price and net profit as compared with particle swarm optimisation and genetic algorithm.

Power system restoration after a major blackout is a complex process, in which selection of energising paths is a key issue to realise unit and load restoration safely and efficiently. In general, the energising path scheme made beforehand may not be executed successfully due to the possible faults on the related lines under the extreme system condition, so it is necessary to provide alternative path schemes for system restoration. In view of this, the energising path optimisation based on the minimum cost flow model is investigated, then an iterative searching method for alternative path schemes based on mixed integer linear programming is proposed. The iterative method for alternative path schemes could determine more than one scheme with minimal charging reactive power efficiently. In order to make a comprehensive evaluation of the alternative schemes, an evaluation index set is established, and the method based on similarity to ideal grey relational projection is introduced to achieve the final evaluation. The New England 10-unit 39-bus system and the southern Hebei power system of China are employed to demonstrate the effectiveness of the proposed method. The proposed method can provide more efficient and comprehensive decision support for the dispatchers to select reasonable energising paths.

The common way to isolate the line fault in line-commutated converter-based high-voltage direct current (LCC-HVDC) transmission grids is regulating the trigger angle of converters on both terminals of the faulted line, which usually depends entirely on the conventional controller and goes with large current peak and lengthy overcurrent duration. In this study, a trigger-angle setting approach with adaptability is, therefore, proposed to provide a theoretical basis for the generation of fault isolation strategies under different scenarios. First, equivalent circuits of solid pole-to-ground line faults at rectifier and inverter terminals are established, and time-domain expressions of the fault and converter currents are obtained. Secondly, based on the analysis of current characteristics, the non-linear programming method is utilised to obtain the optimal trigger-angle sequence after the fault, which can be applied in the following fault isolation. Finally, the proposed approach is verified via power systems computer aided design (PSCAD)/electromagnetic transients including DC (EMTDC) simulation. The results show that it can effectively reduce the current peak and the overcurrent duration of the converter, which is of positive significance for maintaining the power system security and stability.

The authors propose a smart transmission system islanding scheme during an out-of-step (OOS) condition using PMU data. An OOS condition leads to the formation of electrical centers on a few transmission lines. The distance relays on the lines misinterpret it as a bolted three-phase fault and trip leading to an uncontrolled system separation. The load-rich islands can blackout due to massive generation-load imbalance. Recent research has shown that the evolution of electrical centers can be tracked by PMUs and hence, distance relays on these lines can be temporarily blocked from operation. The authors now propose an adaptive islanding scheme wherein (i) the islands contain coherent generators and (ii) overall load shed is minimised. In other words, the authors propose a simple and efficient method for determining the optimal cutset using PMU data. The method does not require explicit coherency determination of generators and can be implemented within the time interval of two PMU frames (40 ms in India). Simulation results on the 16-generator system and the Indian power system demonstrate the efficacy of the proposed method.

Corona current is an important parameter to characterise the corona discharge on high-voltage direct current (HVDC) transmission lines. The spectral components of corona current are closely related to a variety of corona effects, such as audible noise. It is of great significance to study the frequency-domain characteristics of corona current. Here, the relationship between DC component and spectral components of corona current on HVDC transmission lines in the band of 2–20 kHz was analysed. First, a lot of corona current data were measured in two HVDC experiment bases. Then, the expression representing the correlation between DC component and spectral components of corona current within 2–20 kHz was established with the maximum surface nominal electric field intensity of conductor as an intermediate variable. Finally, the correctness and universality of the relationship found were verified. The research results here not only reveal the characteristics of corona discharge but can also provide a new way for obtaining the spectral components of corona current in 2–20 kHz with its DC component, and can lay the foundation to provide a new way to get audible noise indirectly based on the DC component of corona current in the future.

There is an increase in fault current levels seen by utilities due to grid expansion and the addition of new resources. Installation of superconducting fault current limiter (SCFCL) at transmission voltage levels is being explored to reduce the fault levels. The SCFCL limits the fault current by inserting an additional impedance in the network, which may impact the protection system. This paper discusses the impacts of SCFCL on the operation of line distance protection. It is observed that operation of SCFCL may not impact all the distance relays in the substation and near-by substation in the same way, thus a boundary definition method is proposed in this study to identify the affected relays. The definitions of boundary condition based on steady-state fault current values and critical current of the SCFCL are proposed in this study. The impact of SCFCL on the line distance relays which manifest as underreaching of the relays and may also lead to coordination issues and erroneous operation. An implementation method for mitigation which is compatible with existing substation relays is proposed and demonstrated to ensure proper operation of the relays. The proposed mitigation ensures that the system integrity is maintained during faults.

This article proposes a power system state estimation (PSSE) capable of dealing with distribution and transmission networks. The proposed approach combines decoupled techniques, complex per unit (cpu) system, and a switching branch representation to meet the increasing complexity of state estimation issue when associated with the emerging electrical systems. The result is an efficient tool that can easily deal with distributed generation, closed loop, or meshed operation and manoeuvres in distribution systems (DS) keeping the efficiency and ability of the fast decoupled estimator to process transmission systems (TS). Results obtained with several simulations carried out on two distribution test systems, a 136-node Brazilian feeder and a 907-node European feeder, and on the IEEE 14-bus TS, demonstrate the effectiveness of the proposed methodology.

This study deals with the formulation of a simple control strategy for the enhancement of the low-voltage ride-through (LVRT) capability of the grid-integrated permanent magnet synchronous generator (PMSG)-based wind generation system (WGS). The control warrants satisfying minimum required reactive current support to the ac grid as first priority with minimum loss of generation and maximum utilisation of the converter current capacity during LVRT compliance as per E.ON Netz German grid code requirements. The reference control variables in coordinated control of the stator-side and grid-side converters are altered so as to support the reactive current to the ac grid and, to store the excess active power in the system inertia for keeping the dc-link capacitor voltage in the safe limit during voltage dips at the grid side. The investigations have been made on the proposed strategy of LVRT enhancement with the speed (ω) and torque (T) controls of the direct-drive PMSG in grid-integrated WGS exploiting commonly used tip-speed-ratio and optimum-torque control algorithms of peak power tracking, respectively. Simulation results have been presented to validate the proposed strategy. The performances of the proposed strategy of LVRT enhancement has also been compared to the conventional method like dc-link braking chopper.