Faults diagnosis in power transformers has been traditionally based on the insulation resistance measurement, polarisation index, analysis of dissolved gasses in oil, dissipation/power factor measurement, and partial discharges within many other alternatives. Originally, all these techniques presented an offline implementation, that is, with the transformer out of service. Currently, some of them, such as partial discharges measurement or gas analysis (gas chromatography), are carried out online in those cases in which the importance of a machine justifies it. These techniques have been recently complemented with new alternatives, such as frequency response analysis, an offline application technique. At the same time, in recent years, development of online diagnostic strategies has been carried out only based in monitoring of electrical variables. These techniques have the advantage of being economical in relation to traditional ones. Its development are incipient and with high growth potential. This study presents a review of the most important techniques and a critical comparison between them.

How to improve the reliability has been a challenging task for transient protection, which has been affected seriously by the fault initial angle (FIA) and transient resistance (TR). Based on support vector machine (SVM), a novel smart transient protection method is presented in this study, which protects a bus and two transmission lines connected to the bus. The method is based on the measurements from the two close-in ends of the two lines. Hilbert–Huang transform is used to extracting instantaneous amplitude from the measured currents. The fault area is determined from the two instantaneous amplitude-integral (IA) of the transient fault currents, the difference of the two IAs, FIA, and the TR. SVM is utilised to determine the fault area. Two IAIs, difference of IAs, FIA and TR are treated as the input to SVMs. Faults with different FIA and TR are treated as a different class of fault, respectively. Correspondingly, a different criterion of discrimination is automatically employed by SVMs for a different fault class. The influence of FIA and TR is eliminated significantly, and the reliability of protection is enhanced substantially. The performance of the method is tested using ATP/EMTP with satisfactory results.

This study presents the design and development of a soft-core prototype of an overcurrent relay (OCR). The prototype is implemented on the field programmable gate array and its functionality has been verified using hardware-in-loop testing on the real-time digital simulator. Computational efficiency and memory requirement of the OCR is improved by using integer arithmetic Verilog design platform. Extreme inverse and very inverse characteristics of the OCR based on standard inverse-time characteristics as per IEEE standard C37.112-1996 is used and tested in the proposed design. Digital design of the proposed algorithm, emulation results, complete hardware setup and experimental test results are presented in this study. The performance of the OCR is evaluated for a large range of characteristic parameters (pick-up current and time-dial setting) and various operating conditions which validate the operation of the relay in real time with the power network. The designed relay has the ability to differentiate between fault and inrush current to avoid any mal-operation during energisation of transformers.

The accelerated thermal aging test is an effective method to simulate insulation material degradation in oil-immersed transformers. Traditionally, cellulose paper and mineral oil are heated up together at the same temperature when a thermal aging test is conducted. However, variation occurs between laboratory results and field conditions. Temperature gradients exist in real transformers, and each part of the winding is aged under various conditions. In order to rebuild temperature gradients and conduct a thermal aging test under this condition. First, 3D models with designed U-shape wingding which can guarantee different parts aged simultaneously under different temperatures are calculated for temperature field analysis. Then a thermal aging platform with a large current generator is proposed to construct temperature gradients in a thermal aging test. The large current generator helps to heat up the copper winding. Temperature sensors are installed in the aging tank to monitoring winding and oil temperature and control temperature. The aging temperature is selected according to the standard IEC 60076-7 for the over-load condition. The degree of polymerisation of the insulation paper is measured and properties of each layer of the insulation paper are analysed. Other aging products under both traditional test and method in this study are compared.

In power system analysis and optimisation, the B-coefficient loss formula is frequently used to estimate network losses. However, given the rapidly increasing penetration of renewable generations and responsive demands, nodal power injections of modern power systems appear to be highly variable, deteriorating the accuracy of the traditional B-coefficients loss formula. To address this issue, several typical variants of direct current power flow approximations combining with two different least square methods are streamlined in a unified framework, spawning several improved least square-based methods to estimate B-coefficients in network loss formula. The improved methods relax the restrictive assumption in existing literature that bus load is linearly dependent on system load, and account for load distribution variability, hence remarkably enhance the accuracy of B-coefficients estimation with highly volatile nodal power injections. Case studies performed on IEEE-39 and RTS-96 bus systems demonstrate that the enhanced methods outperform traditional ones.

Dispatch results depend on the forecast wind power in an electric power grid. High levels of uncertainty in wind power lead to large forecast errors (FEs). Wind power FE creates an imbalance between power load demand and supply, which poses risks to the power grid. To minimise the risk caused by uncertainty in wind power, FE was analysed. The actual and forecast power of wind generations were studied to determine which factors had strong relationships with FE. After being analysed by principle component analysis, these factors were used to build an assessment model to estimate FE. According to the output of the assessment model, risk factor (RF) was defined to evaluate the risk-level associated with wind power. Moreover, based on a grid including wind generation and fossil fuel-fired power plants, a dispatch model was built to account for the cost of fossils fuels and RF. This dispatch model was studied to find strategies for decreasing the impact of wind power on the grid. The results from their research will increase the safety and reliability of power grids with uncertain levels of wind power and promote the widespread use of wind power.

The minimisation of discrimination time between main and backup overcurrent (OC) relays is one of the most important issues in power system relays coordination. On account of the massive computation burden and complexities for determining power system breakpoint, the implementation of the previously reported OC protection methods in large interconnected networks is almost impossible or at least cumbersome. In this regard, a variety of optimisation algorithms have been presented for coordination between relays and finding optimal operation time (OT) of the protection system. The previously reported single-objective optimisation algorithms have some limitations/drawbacks regarding OT of relays and their coordination. In this study, a new multi-objective optimisation algorithm is presented for coordination of OC relays in interconnected networks, based on multi-objective particle swarm optimisation (MOPSO) and fuzzy decision-making tool (FDMT). Then, using some useful assumption and recommendations of IEC-6090 and fault calculations for the microgrids including distributed energy resources, the proposed method is generalised for OC relay coordination in microgrids. Finally, the proposed method has been successfully implemented on different test systems and the obtained results have been compared with other reported methods to prove accuracy, authenticity, and efficiency of the MOPSO/FDMT-based protection and relay coordination algorithm.

It is expected that different energy infrastructures and resources to be operated and planned simultaneously in the future smart energy systems. Recently, the concept of energy hub and its corresponding management systems has been proposed in multi-carrier energy systems. The presented study develops a two-stage stochastic mixed-integer linear programming model for a day-ahead energy scheduling of a multi-carrier energy system, considering the time-varying energy price signals and volatility feature of renewable energy resources. In the framework of the proposed method, the objective is set to minimise the energy hub's total cost, while finding the optimal values for decision variables. A set of valid scenarios is considered for the uncertainties of loads and solar energy resources. Finally, the proposed stochastic day-ahead optimisation is tested in a case study situation. In the process of minimising the operational cost, an energy hub operator is able to fix some decisions such as energy exchange with the main grid and unit commitment, before the actual realisation of the uncertain parameters is observed. The unit commitment results also are compared with those produced by a deterministic model for the case in which the electricity flow is bidirectional.

Trade-offs between power system's optimal operational performance and the minimal number of control adjustments necessary to attain a desired operating point make optimal reactive dispatch (ORD) solutions practical to system operators. In this study, a multi-objective ORD model that provides, in terms of weighting factors, trade-offs between minimal active power losses in transmission systems and minimal number of control adjustments in generator voltages, tap ratios and shunt controls is featured. This multi-objective ORD is formulated as a mixed-integer non-linear programming (MINLP) problem, and the proposed resolution methodology is based on translating the original MINLP problem into non-linear programming (NLP) problem deploying a sigmoid function, enabling the use of NLP solvers. Both original MINLP and translated NLP models are implemented in GAMS and numerical tests with IEEE test-systems with up to 300 buses are conducted using DICOPT, KNITRO and CONOPT solvers to validate the proposed ORD model and its resolution methodology. Results demonstrate the relation between active power losses and the number of adjustments in control variables, which is valuable information for operation planning. Another fundamental result is the high computational performance of the method when compared to specialized MINLP solvers.

This study presents a method for determining optimal droop settings of dispatchable distributed generation units in a droop-controlled microgrid (DCMG). The objectives are to (i) minimise the operational cost and (ii) minimise the emission in the DCMG while meeting all the operational constraints. The proposed formulation takes into account the electricity demand, load uncertainties and renewable power uncertainties in the MG. Load and renewable power uncertainties are modelled by Hong's point estimate method. The bi-objective optimisation problem is solved using fuzzified particle swarm optimisation. The proposed method is validated on a 6-bus DCMG test system. The results show the effectiveness of the proposed method.

High-voltage overhead transmission lines feature both electrical conductivity and mechanical strength properties. Current studies of the aeolian vibration of transmission lines focus primarily on the mechanical properties of these lines but rarely address the lines’ enhanced heat transfer properties, which directly affect transmission line ampacity. In this study, the authors analyse the vibration-enhanced heat transfer characteristics of an energised transmission line undergoing aeolian vibration based on the coupled fluid–solid numerical method. The allowable ampacity is calculated using the heat balance method, which accounts for the heat transfer enhancement effect arising from aeolian vibration. Various parameters, such as the vibration amplitude and the ratio between the natural frequency of the conductor and the frequency of the vortex shedding, are investigated. The results demonstrate that aeolian vibration can effectively improve the heat dissipation effect of the conductor and significantly increase the line ampacity. The maximum heat transfer effect occurs in the lock-in region, in which the allowed ampacity can increase by more than 6%.

Dynamic optimal power flow (DOPF) in active distribution networks generally relies on a perfect forecasting of uncertainties such as intermittent distributed generations and time-varying loads, which is generally difficult to achieve in practise. To make DOPF possess the ability to deal with uncertainties, especially for the satisfaction of operating constraints in an uncertain environment, an interval DOPF (I-DOPF) model is derived in this study, by using affine arithmetic and interval Taylor expansion. To solve the I-DOPF problem efficiently, the solving method based on successive linear approximation (SLA) and distributed optimisation strategy is further discussed. The proposed I-DOPF model and its solving method are subsequently applied to a modified IEEE 33-bus network and a real 113-bus distribution network. The simulation results demonstrate that the I-DOPF model has a good performance on boundary constraint satisfaction under uncertainties; the SLA-based solving method can be well integrated with distributed optimisation to meet the practical requirements of data exchange in large-scale active distribution networks.

The rapid discharging and slow charging processes of a DC-link capacitor in a voltage-source converter (VSC) have become the primary issues in VSC-based DC systems, resulting in greatly prolonged fault recovery times. Therefore, blocking measure for capacitors is necessary, but limits the principles of fault location being based on the transient component. Moreover, as the main bottleneck in the development of DC system protections, the DC circuit breakers (DCCBs) adopted in low-voltage systems have yet to be fully developed. Hence, it is necessary to propose a fault location principle based on steady-state currents and a fault isolation scheme based on ACCBs. This study presents a 2-step isolation scheme adopting thyristors and ACCBs to facilitate fault location and clearance. This method retains the harmonic component of the fault current and creates a current zero-crossing point. Next, a single-terminal fault location method adopting a steady-state harmonic component is used to realise the exact fault location function with different fault resistances and to restore system operation within 160 ms. The protection method economising many communication modules and DCCBs is suited for low-voltage distribution DC systems.

This study presents a synergistic operation between a battery energy storage (BES) and a photovoltaic generator (PVG) system to assist management of microgrids. The BES and the PVG work synergistically in a virtual single agent. The single agent consists of a group containing the BES, the PVG, and the loads in a feeder. The single agent results in a virtual distributed energy resource, capable to obey orders imposed by the supervisory controller (SC). The loads within the single agent seem not existent anymore to the SC, but they kept fed all the time. This is convenient to the microgrid in terms of management because the SC interacts with only one element and not more with all elements within the single agent. The synergistic operation arises when the SC demands orders to the single agent. To make the single agent obey the SC, the BES and PVG need to decide their operation mode, working synergistically for each other. The conservative power theory is applied to quantify active power, reactive energy, and harmonic currents in points of interest along the microgrid. The efficacy of the synergistic operation is verified through experimental results.

With the development of smart grid, the demand for voltage measurement along the overhead transmission lines is increasing. However, the installation of voltage transformers in the existing lines entails numerous difficulties. This study proposes a new non-contact measurement method by inversely calculating the voltages on AC overhead transmission lines based on the power-frequency electric field measurement data. To improve the calculation accuracy, the 3D model of transmission lines is built, and the relations between the 3D electric fields and voltages are presented. An improved algorithm that intermingles with the particle swarm algorithm and genetic algorithm is developed to ascertain optimal inverse solutions, meanwhile to improve the convergence speed and calculation stability. To further reduce the computational complexity, the constraint relations between the voltages and electric fields are derived, thereby the simplification from three decision variables to one is achieved. Then, some simulation cases with different measurement errors and voltage running states are conducted to show the good robustness and high accuracy of the proposed inversion method. Finally, a three-phase experimental system is built and the actual measured data are used to inversely calculate, which verifies the practicability of the proposed non-contact voltage measurement method.

In this study, first, it is shown that the least-squares (LS) algorithm outperforms well known methods such as extended Kalman filter and unscented Kalman filter for synchronous generator (SG) parameters estimation using phasor measurement unit (PMU) data. However, as the LS algorithm may estimate the SG parameters inaccurately if the initial values of SG model state variables are not valid, a modified LS (MLS) algorithm, which estimates the initial values of SG model state variables alongside SG parameters, is proposed. In addition to parameters estimation of an SG classical model, the performance of this algorithm in the estimation of whole electromagnetic parameters and rotor inertia constant of an SG full-order model is evaluated. Note that conventionally, measurements of generators rotor angles were used to estimate SGs full-order model parameters; nevertheless, in the proposed MLS algorithm, online SG parameters estimation is accomplished using PMU data without relying on rotor angle measurement that is difficult to be obtained in practise. Simulation results demonstrate the effectiveness of the proposed algorithm in SG parameters estimation for various disturbances and noisy measurements. Furthermore, the effect of mechanical torque signal unavailability on the proposed algorithm capability is studied, where the efficacy of this algorithm is proven.

The main purpose of this study is to show how the emissivity and absorptivity of a pavement surface above underground cables affect their ampacity. The use of cool pavements whose surfaces absorb less heat from the Sun than they emit to the ambient is considered as a novel method to control the thermal environment of underground cables. The method predicts that the trench along the entire length of a 110 kV cable line is completely filled with quartz sand and paved with a cool pavement. Quartz sand would provide good conduction of heat from the cables to the earth and pavement surfaces, while a paved surface of the trench would establish approximately unchangeable convection and radiation boundary conditions along the entire cable line route. It is assumed that the three-phase system is balanced and that the boundary conditions along the earth and pavement surfaces are the most unfavourable. The novel method is based on the results of experimental research, generalised and verified numerically using the finite-element method in COMSOL. Finally, it is established that the ampacity of the 110 kV cable line can be increased up to 26.7%.

This study proposes a novel fast learning optimiser (FLO) for real-time optimal energy management (OEM) of a grid-connected microgrid. To reduce the optimisation difficulty, the non-convex real-time OEM is decomposed into a two-layer optimisation. The non-convex top-layer optimisation is responsible to determine the direction of tie-line power, and the heat energy outputs of combined heat and power units. Then bottom-layer optimisation is strictly convex with the rest controllable variables, which is solved by the classical interior point method. The model-free Q-learning is employed for knowledge learning and decision making in the top-layer optimisation, thus the feedback reward from the bottom-layer optimisation can effectively realise a coordination between them. The real-coded associative memory is presented for a more efficient optimisation of continuous controllable variables. In order to dramatically reduce the execution time, the knowledge transfer is adopted for approximating the optimal knowledge matrices of a real-time new task by abstracting the optimal knowledge matrices of the predictive source tasks. Simulation results demonstrates that the proposed FLO can rapidly search a high-quality optimum of real-time OEM, in which the computation rate is about 2.75–29.23 times faster than that of eight classical heuristic algorithms.

This paper deals with the short-term forecasting of electrical energy demands at the local level, incorporating advanced metering infrastructure (AMI), or ‘smart meter’ data. It provides a study of the effects of aggregation on electrical energy demand modelling and multi-nodal demand forecasting. This paper then presents a detailed assessment of the variables which affect electrical energy demand, and how these effects vary at different levels of demand aggregation. Finally, this study outlines an approach for incorporating AMI data in short-term forecasting at the local level, in order to improve forecasting accuracy for applications in distributed energy systems, microgrids and transactive energy. The analysis presented in this study is carried out using large AMI data sets comprised of recorded demand and local weather data from test sites in two European countries.

This work presents a probabilistic sequential framework for short-term operation of distribution companies (DisCos) participating in the day-ahead (DA) and real-time (RT) markets. In the proposed framework, the DisCo's operating decisions are sequentially optimised; first, in a DA operation stage, and then in RT. The DA decisions are driven by the DisCo's profit maximisation, while the DisCo aims to minimise the actions required to accommodate deviations from forecasted quantities (i.e. the DA decisions) in the RT operation stage. This sequential approach considers realistic voltage-sensitive loads and full ac power flow equations to represent the realistic network's active and reactive power injections. In addition, the operation of stationary batteries and the demand elasticity under time-varying retail prices are explicitly modelled. The two resulting models are large-scale highly non-linear non-convex mathematical problems with continuous and discrete variables. A pseudo-dynamic tabu-search-based solution algorithm is used as an alternative to conventional optimisation solvers in order to tackle the problem in an effective manner, without linearisations. Numerical results from 69- and 135-bus distribution systems illustrate the performance and the scalability of the proposed approach.

A study of the AC link with flexible transmission distance and half wavelength properties as an option for bulk power transmission over very long distances is presented. This alternative has been studied for many years, however, the present document introduces new insight and explanations about how the use of adequate optimisation methods of tower design and tuning procedures permits that AC transmission lines with half-wavelength properties present enhanced performance that could be comparable with high-voltage DC transmission systems. Issues highlighted in this work are: improvement of right of way size, flexible distance, adequate voltage-reactive power regulation and the competitive system efficiency. Competitiveness of this AC link based on half-wavelength properties is proved when old problems are eliminated.

The high penetration of renewable energy requires flexible transmission of electrical energy over long distances. Onshore high-voltage DC (HVDC) interconnectors based on overhead transmission lines have already reached an advanced planning stage. These interconnectors could be extended to multi-terminal grids in the second step for higher transmission redundancy and flexibility. Fast and selective protection concepts for fault handling are required to ensure high reliability and continuous operation of these systems. Modular multi-level converters with submodules in half-bridge topology and solid-state HVDC-circuit breakers (SSCB) provide fault clearing within several microseconds to prevent converter blocking. Within this publication, a selective protection concept for SSCB and multi-terminal HVDC systems based on the overhead transmission is developed and analysed. It is based on a combination of local voltage and current signals and does not require communication between grid nodes. Additional series reactors for limiting rising fault currents are not required. Subsequent simulations for validating the protection concept and identifying its limits are carried out in power systems computer-aided design™/electro-magnetic transient design and control™ for an exemplary HVDC system. The combination of overcurrent protection with additional excitation signals enables selective fault clearing for all types of line fault scenarios.

This study proposes a model for the analysis of earthing grid designs in multilayer soils with finite heterogeneities (in horizontal and vertical directions) based on the current simulation method (CSM). Case studies on some proposed IEEE grid design examples show significant accuracy levels when compared with the results obtained by the IEEE experimental and infinite series methods. A practical design problem which consists of a horizontal variation of resistivity in the top layer has been solved by the above CSM. Studies show that results provided by the CSM algorithm can be optimised further by increasing the number of current sources. The main objective of this study is to show that this computer-based simulation process can be a substitute to the experimental and other methods leading to less investment of man power and time for the design and analysis of earthing grids.

A new stochastic framework is proposed for distribution system restoration (DSR) problem. In this framework, dynamic programming (DP) is used to solve DSR problem for a distribution system that accommodates various technologies of distributed generation units and storage systems. Time and sequence of distribution feeders which should be energised after a blackout are chosen as stages of DP algorithm. In addition, uncertainties associated with the power received from transmission network in the period of system restoration are modelled as some probabilistic scenarios. The complexity of attained optimisation problem is reduced using some state reduction techniques. These techniques enable DP algorithm to reach near-optimal solution as well as computationally efficient calculation procedure. The proposed restoration framework is applied on a real-world test system and the results prove its effectiveness and practicality.

Aside from conventional generation units, heat ventilation and air-conditioning (HVAC) loads, thanks to their inherent thermal capacity storage, are reasonable alternatives to mitigate short-term variability impacts in power systems with high renewable energy sources (RES). Accordingly, HVAC loads are integrated into a multi-stage multi-resolution robust unit commitment considering non-deterministic variability-oriented reserves to address operational flexibility requirement in power systems. Since common two-stage robust optimisations are over-conservative, non-causal and in general NP-hard, a non-conservative extended affinely adjustable robust optimisation approach is proposed to provide causality, enhance computational tractability and improve optimality in a multi-stage robust decision-making framework. In addition, since existing hourly resolution scheduling is unable to track fast and frequent variations in RES, the proposed framework is multi-resolution including both hourly and sub-hourly resolutions. Moreover, unlike conventional deterministic flexible ramp reserve procurement, a robust variability-oriented reserve scheduling is presented to determine adequate while economic and technically deliverable flexible ramp reserves from both generation and demand sides. The effectiveness of the proposed model is illustrated on the IEEE 24-bus reliability test system.

The arc temperature profile in an interrupter, which determines the extinguishing characteristic of an SF₆ circuit breaker (CB), is of interest to designers and developers. In this investigation, optical fibres and spectrograph were employed to measure the arc temperature profiles in a 252 kV SF₆ CB during short current interrupting. The temperature profiles of the upstream, throat, and downstream of the nozzle have been measured. The optical fibres can transfer the arc light from the measuring points in the nozzle to the spectrograph. Moreover, the spectral line intensities of copper (Cu) 510.5, Cu 515.3, and Cu 521.8 nm were obtained by the spectrograph. The condition in CB can be treated as a local thermal equilibrium system, and the temperature profiles can be calculated by two-line method and Abel inverse method. The arc temperature profiles of the interrupter under 15–50 kA root mean square current have been analysed through the method established in this investigation.

Large-scale wind power integration will inevitably affect the dispatch of conventional resources, which could result in transmission line overload. Thyristor-controlled series capacitors (TCSCs) can be therefore installed in the transmission lines to change their series impedance so as to increase the loadability of the power system and reduce transmission losses. To address the highly uncertain characteristic of wind power output, a stochastic optimisation-based optimal TCSC planning model is proposed here. This model minimises the expected value of power loss cost and the investment cost of TCSC considering the probability of different scenarios, which are developed by using the classical copula theory, where the temporal interdependence between wind and load is taken into account. Mathematically, this optimal TCSC placement problem is formulated as a two-stage non-linear programme. Then the linearisation methods are adopted to transform the model to a mix-integer linear programme. Comprehensive case studies are carried out on the modified IEEE 57-bus test system, which demonstrates the effectiveness and efficiency of the proposed model.

This study introduces a new model for line-commutated converter high-voltage direct current (LCC-HVDC) systems based upon the concept of extended-frequency dynamic phasors (DPs). The proposed model is able to represent LCC-HVDC converters during normal as well as abnormal operating modes such as system imbalances and commutation failure by automatically adjusting its parameters based upon converter terminal quantity measurements. The model offers a high level of accuracy with reduced computational burden, and is suitable as a replacement for conventional switch-based models of LCC in electromagnetic transient (EMT) simulation platforms. The proposed model is thoroughly evaluated against detailed EMT simulations of the CIGRE HVDC benchmark and the IEEE 12-bus systems with an embedded LCC-HVDC link. Simulation results confirm that the proposed DP-based model retains EMT-grade accuracy even at large simulations steps. Significant acceleration ratios reaching up to an order of magnitude are observed in the simulations using the proposed model compared with conventional EMT models.

One of the major issues in an interconnected power system is the low damping of inter-area oscillations which significantly reduces the power transfer capability. A speed deviation-based wide-area power system stabiliser (WAPSS) is known to be effective in damping inter-area modes which use feedback from remote locations. However, the involvement of wide-area signals gives rise to the problem of time delay, which may degrade the system performance. The delay in synchronised and non-synchronised feedback to WAPSS can have alternate performances. The effect of delays in such WAPSS with two types of feedback is studied and controllers are synthesised using the control with regional pole placement to ensure adequate dynamic performance. To show the effectiveness of the proposed approach, two power system models have been used for the simulations. It is shown that the controllers designed based on the non-synchronised signals are more robust to time-delay variations than the controllers using the synchronised signal.

A new generation of electric appliances with controllable reactive power creates an opportunity for operators in distribution systems to be used as a resource for reactive power support. On the other hand, implementing demand response (DR) programmes as an alternative resource to manage the active power demand may also affect the reactive power balance. Collaborative effect of reactive power support devices and the DR programme is investigated in order to control voltage problem in a distribution network. In the first step, distributed voltage (DV) control and DR methods are considered as individual control actions; then, the hybrid DV control with DR (DVDR) method is proposed to improve the voltage profile. The IEEE 33-bus distribution standard test system is chosen for validating the novel method, in which the optimum reactive power injection in the candidate buses and demand curtailment in each area are calculated. The proposed DVDR method can better mitigate the voltage problem and the results showed far desirable performance compared with using just DR or DV methods. The proposed method can also curtail less demand in comparison to the DR method.

Current differential protection is normally designed as the primary protection for the high-voltage transmission lines. However, for the transmission line that is connected with the large-scale inverter-interfaced generators (IIGs), the performance of the conventional current differential protection is significantly affected by the difference between the sequence components of the fault currents on both sides of this line. This may result in the mal-operation of protection relays. This study proposes a sequence-component-based current differential protection from a suitable fault model of IIGs under positive-sequence control strategy. A differential coefficient is introduced to overcome the low sensitivity and poor reliability of the conventional differential protection. The proposed scheme discriminates the internal faults accurately from the external faults and the normal operating conditions. Additionally, the robustness analysis shows that this scheme is immune to different fault resistances, fault locations, and system parameters. Simulation results in power systems computer-aided design/electro-magnetic transient design and control validate the effectiveness of the proposed sequence-component-based protection scheme.

This study presents a new analytical solution to solve the contracting capacity (CC) optimisation problem that several sets of the demand and energy rates are available in the market. The proposed method (PM) obtains the best option for the prices and the best CC. It is mathematically proved that the best CC is the maximum demand for a specific month of interest. Further, despite most existing methods such as linear programming, PM is able to obtain all optima. Some significant properties of and the influence of the input parameters on the optimal solution are discussed. Moreover, the errors on the forecasted maximum demand and the forecasted prices are separately analysed. Finally, the PM is performed on the data of various scenarios of a large real electrical user to highlight the effectiveness of this method.