Aiming at the mutual influence of hydraulic, mechanical, and electrical factors in a hydropower station, a detailed mathematical model for the governing system of a hydro-turbine generator unit was presented here. An object-oriented approach was used to write the computational program in Matlab/Simulink platform, and then it was verified by the prototype tests. The parameters of the governing system were optimised by the experimental test and this model, and evaluated by using the amplitude frequency characteristic method under no-load frequency control mode, load frequency control mode, and load opening control mode. The characteristics of the waveform of the transient process and the influence degree of hydraulic, mechanical, and electrical factors were obtained. The computational results of the transient process show that the load rejection as an electrical disturbance leads to the water hammer, and the water-level fluctuation in the surge chamber becomes one of the reasons of the low-frequency oscillations in the power grid, especially under the load frequency control mode.

False data injection attacks can pose serious threats to the operation and control of power grid. The smarter the power grid gets, the more vulnerable it becomes to cyber-attacks. Various detection methods of cyber-attacks have been proposed in the literature in recent past. However, to completely alleviate the possibility of cyber-threats, the compromised meters must be identified and secured. In this study, the authors are presenting an artificial intelligence (AI)-based identification method to correctly single out the malicious meters. The proposed AI-based method successfully identifies the compromised meters by anticipating the correct measurements in the event of the cyber-attack. New York Independent System Operator load data is mapped with the IEEE 14-bus system to validate the proposed method. The efficiency of the proposed method is compared for artificial neural network and extreme learning machine-based AI techniques. It is observed that both the techniques identify the corrupted meters with high accuracy.

The majority of faults in power distribution system are caused by natural degradation of feeders. In addition, travelling waves will be generated during degradation of feeders. This study proposes a method based on travelling waves to identify sub-health condition, which represents the degradation of feeder before the feeder fails into a permanent fault. In the method, traveling waves in the power distribution system are monitored in real time. Then, the location of travelling wave source is determined by the polarity of travelling waves, which is extracted using wavelet transform. Finally, the degradation of feeder is identified when all the other possibilities to generate travelling waves are ruled out using the characteristics of power-frequency voltages and currents accompanied with travelling waves. Simulation results have verified that the proposed method is feasible and effective.

In order to reduce the damages of transmission line icing, an effective ice accretion forecasting can be used to guide the de-icing work. The ice accretion on transmission lines varies slowly over time, and the icing data series is characteristic of timing sequence and autocorrelation. Time-series analysis is suitable for analysing the similar data series, and fireworks algorithm (FA) is used to determine the autoregressive order and the moving average order of time-series analysis. Then a short-term ice accretion forecasting for transmission lines with modified time-series analysis by FA is built. The ice accretion experiments were done in artificial icing laboratory. The results show that the modified time-series analysis model by the FA has higher accuracy than another five models, whose relative errors are <1.3% and closer to the experimental data. Field applications also show that the modified time-series analysis model has higher accuracy than the traditional one for the short-term ice accretion forecasting, whose average error rates are separately 2.6723 and 5.2654%.

Renewable energy sources (RESs) are actively connected with the grid, and thus the requirement for transmission network expansion planning has increased. When RESs are added to the grid as independent power plants under a deregulated power system structure, an independent system operator managing the transmission system should evaluate the impact of RES penetration. The system operator should restrict the capacity of the RES to be installed or perform transmission network expansion planning if necessary. This study proposes risk assessment (RA) based on an exponential risk level (RL) model to evaluate the negative effects of RES penetration and introduces a method of applying RA in scenario-based transmission network expansion planning. The index of RL reduction via a scenario is formulated as an economic efficiency indicator for reducing the RL, based on the result of RA. A case study is performed on an actual power system in South Korea. For two cases based on the penetration of RESs, transmission network expansion planning considering the proposed RA is performed for several scenarios, and then, the best scenario for each case is selected.

Distributed generation has many potential benefits including use of renewable resources, increased customer participation, and decreased losses. However, as the penetration of distributed renewable energy sources increases, the technical challenges of integrating these resources into the power system increase as well. One such challenge is the rapid variation of voltages along distribution feeders in response to photovoltaic (PV) output fluctuations, and the reactive power capability of PV inverters can be used to address this challenge. A method of achieving optimal expected performance with respect to a figure of merit of interest to the distribution system operator while maintaining appropriate system voltage magnitudes and considering the uncertainty of PV power injections is proposed. The method utilises reactive power injection both to improve system performance and to compensate for variations in active power injection. It requires infrequent communication between the distribution system operator and the PV inverters and bases its decisions on short-term forecasts, formulating voltage magnitude requirements as chance constraints. The proposed method is validated using the IEEE 123-node radial distribution test feeder and shown to improve the distribution system performance (with respect to existing methods) and maintain suitable voltages.

In recent years, high penetration of distributed generations based on wind energy, solar energy and so on in the existing power system network has been noticed. However, due to their stochastic behaviour, operations under autonomous mode as well as in grid-connected mode are not an easy task. This has forced the power utilities to re-define frequency regulation criteria to enhance the overall system stability and reliability. In line with the same, dynamic performance analysis of load frequency control (LFC) of an autonomous hybrid power system model (HPSM) consisting of tidal power plant (TPP) and diesel power plant is explored in this study. A concept of deloaded TPP is adopted in the studied HPSM to utilise the available reserve power for the frequency support. Apart from this, the studied model also incorporates frequency regulation through inertia and damping control and supplementary control strategies. These control strategies are realised through conventional controllers whose gain values are optimised using quasi-oppositional harmony search algorithm (QOHSA) for the optimal dynamic performance of LFC. The efficacy of the proposed QOHSA is corroborated by comparing the results with those yielded by few other existing state-of-the-art algorithms.

The synchronisation is a critical process in power system. When closing a circuit breaker (CB) between two energised parts of the power system, match voltages on both CB sides before closing must be verified. Non-synchronising conditions will result in a power system disturbance and equipment damage. The voltage magnitude, frequency and phase angle differences across the breaker must be closely monitored. In this study, the author suggests a synchro-check relay based on correlation concept. The correlation is considered a proper statistical method for estimating the similarity between electrical signals. The three-phase voltages and currents, measured from the two sub-systems, are used in the proposed technique to check match voltages during normal operation conditions. The synchroniser can operate online and function in automatic mode for electrical networks with different voltage levels. In addition, it can be used to supervise CB closing for avoiding an incorrect operation. Two parts of a 19.57 kV/500 kV power system with real parameters are simulated using alternative transients program (ATP) software and MATLAB package to examine the suggested algorithm under different operating conditions. The simulation results show that the proposed approach is relatively simple, reliable, efficient and very promising in applications to generation plants and substation automation systems.

Maintenance and repair of circuit breakers (CBs) due to their protective role in the power systems is the centre of attention and assessing their condition is tremendously important. The interruption chamber of the CBs including main contacts is highly subjected to erosion over time due to friction, and excessive heat produced by an arc during the interruption of the currents. This study presents a new high-frequency (HF) non-intrusive diagnostic technique for the deterioration of contacts used in high-voltage CBs. The most striking result to emerge from the investigations is that the resonance frequency highly relies on the condition of contacts. The proposed approach is implemented in Computer Simulation Technology Studio Suite software and compared with the measured data obtained through the static resistance measurement. In addition, a HF model based on the transmission line theory has been developed for the interruption chamber of CBs. The comparison of the obtained results via a novel HF-based approach with the experimental data validates the feasibility and accuracy of this approach in analysing the ablation of contacts used in the interruption chamber of CBs.

Charging stations are the basic infrastructure for accommodating the energy needs of electric vehicles (EVs). Companies are expected to invest in these charging stations by installing them at locations with a dense concentration of vehicles, such as parking places, commercial centres, and workplaces. In order for investors in EV charging stations to maximise their profits and mitigate the impact on the power grid, these stations would benefit from coupling with an energy storage system (ESS). ESS would be used to arbitrage energy and to balance out the time-variant and uncertain EV energy demand. This study proposes a framework to optimise the offering/bidding strategy of an ensemble of charging stations coupled with ESS in the day-ahead electricity market. The proposed framework accounts for degradation of the ESS, robust scheduling against price uncertainty, as well as stochastic energy demand from EVs. The results show the viability of the proposed framework in providing cost savings to an ensemble of EV charging stations.

Vulnerable transmission lines are weaknesses in the power system security, which are easy to induce cascading failures and blackouts. To identify the vulnerable transmission lines with the increasing complexity of the interconnected power grid, the authors propose a vulnerable transmission line identification method using the depth of the K-shell (Ks) decomposition under power transfer (named the DKsPS method), which fully considers the dynamic characteristics of the power transfer and transmission capability after the power grid fault. This method establishes a correlation network based on the correlation matrix of transmission lines under the N − 1 check and then identifies the vulnerable transmission lines by using the modified Ks decomposition. Numerical simulations on both the IEEE-39 bus system and the Northeast China power grid verify the validity and accuracy of the DKsPS method.

The modern power system operation is faced with numerous challenges related to the power quality improvements such as identification and classification of power distribution network (PDN) faults. The recent advances in the area of signal processing allow the development of new algorithms and methods which can be used for fault identification and classification in PDN. This study presents a comparison of two approaches for identification and classification of high-impedance faults (HIFs) in medium-voltage PDN. The first approach is based on the voltage phase difference algorithm, whereas the second approach is based on the combination of discrete wavelet transform and artificial neural networks algorithm. The proposed algorithms are tested on models of a real distribution network, which represents a typical PDN currently used in Bosnia and Herzegovina. It was demonstrated that the proposed methods are capable to accurately detect and classify HIF in PDN. This study makes a contribution to the existing body of knowledge by developing, testing and comparing two methods for HIF classification and identification, whose application represents an improvement when compared with the capability of the existing protection devices.

This study presents the fuzzy logic integrator gain-tuned improved second-order generalized integrator (GI) for a double-stage grid-interfaced photovoltaic (PV) system. The proposed system includes the functionalities of feeding active power to the grid, power factor correction, grid currents balancing and system isolation under grid side faults. Moreover, the smooth system operation is ensured under weak distribution grids where grid voltage is subject to huge diversions. Furthermore, automatic protection scheme for the system under grid-side faults is also established with the proposed algorithm for increased reliability. The fuzzy-tuned GI provides advantages of efficient and effective extraction of load current fundamental component under steady-state and dynamic grid conditions. The non-linear frequency error variation is compensated here using fuzzy logic-based self-tuning integrator gain of the controller. The controller is improved to mitigate the possible DC component in the load current. The neutral current in the loads is nullified by using a four wire system. The adaptive DC bus voltage helps to minimize the switching losses and prevents unexpected tripping of the PV inverter. The system is experimentally verified using a prototype built in the laboratory.

As there are different types of energy storage systems (ESS), it is important to have a tool that determines the best alternative to be installed in the distribution systems. This study presents a methodology for optimal determination of size, type and site of ESS in distribution systems with distributed generation (DG). The methodology uses a genetic algorithm and a power flow calculated by the Electric Power Research Institute software OPENDSS. For the optimal ESS charge and discharge management uses a non-linear optimisation model that has as objective an energy cost and loss reduction. In addition, the methodology makes an energy management of the system by limiting the reverse flow with a load shifting process and a cost penalty. Solar and wind power are considered as DG modelled in Homer. Then, a genetic algorithm is used to select the size, type and site of the ESS, considering different lifecycles and costs. This methodology is tested in the IEEE 123 nodes system simulated and adapted in the OPENDSS and the formulation is implemented in MATLAB via COM interface. Finally, results of the methodology are presented and discussed.

This study presents particularly an innovative technique to enhance charging dynamics in transformer's oil using multi-nanoparticles (NPs). A charging dynamic process in power transformer oils is the main way to slow down the streamer propagation and upping dielectric strength. In addition, transformer oil's based suspension multi-NPs (dielectric, conductive, and semi-conductive) have substantial levels of deposited electrons higher than suspension traditional nanofluids. An experimental work has been done to verify the importance of using multi-NPs for slowing down positive streamer propagation in transformer oils against using individual NP techniques or traditional transformer oils.

In developed area, there is not only dense electric power grid, but also dense gas pipelines. In this situation, the DC current injected into the earth through the grounding electrodes of a high-voltage DC system would aggravate the corrosion and even destroy the protection devices of the pipelines. In this study, a numerical approach is put forward to simulate the potential distribution in gas pipeline, which is regarded as long grounding system with insulating coating on the grounding conductor. The main cathodic protection methods for the pipeline are also modelled. The approach is validated by the experiment on a reduced-scale model. With this approach, the effectiveness of the measures to reduce the electrode potential distribution along the pipelines is analysed.

The ion-flow environment is an important corona design factor of HVDC transmission lines. The space charges generated by corona form a typical convection-dominated ion-flow field. For this special transport phenomenon, however, standard Galerkin FEM always presents serious deficiencies. In this study, a new approach is used to solve ion-flow field based on Petrov–Galerkin method derived from the theory of fluid computation. A high-order stabilisation technique is used to overcome the non-physical oscillations in the presence of highly convective effects. This algorithm is equivalent to the proper modification of weight function according to the direction and magnitude of local drift velocity. It reflects the characteristic of information propagation in flow problem. The establishment procedure of weak form and matrix gives a further explanation on the deficiency of Galerkin method. Moreover, to guarantee convergence of the iteration for this fully-coupled non-linear problem, a relaxation method is introduced in the iterative loop. Calculations with the Petrov–Galerkin least square method are in good agreement with analytical solution and experiment values of ground-level values and corona losses. Results show that the proposed stabilisation technique is able to preclude the numerical spurious oscillation and has a higher-order accuracy than the fully-upwind treatment.

One of the common causes of cross-linked polyethylene (XLPE) insulation ageing and finally cable failure is the presence of a cavity within cable insulation. Gas filled cavities can be initiated in XLPE cables during its manufacturing, installing and operating conditions. Once the size of the cavity reaches the critical limit, noticeable partial discharge (PD) activity develops. Therefore, the size of the cavity is one of the important factors that considered when investigating the PD activity in power cable. This work studies the effect of cavity size on PD behaviour within insulation layer of an 18/30 kV XLPE cable specimen; the changing in an artificial spherical cavity depths and diameters is investigated in the laboratory. In addition, 2D model geometry of a cable insulation having an artificial cavity is also developed using COMSOL software and MATLAB program to simulate the PD measurements from the laboratory experiments to imitate the conditions found during measurements, hence interpreting the obtained experimental results and determining the significant parameters influencing PD activity; hence, more a fuller understanding of PD phenomena within a cavity. The results show good coincidence between experimental and simulated data, in terms of PD magnitude and PD inception voltage.

The droop control strategy has been widely used in the microgrid. Though the real power sharing is accurate, the performance of reactive power sharing is not good due to the lack of global information. A new control strategy that employs an adaptive virtual impedance is proposed to improve the reactive power sharing accuracy without communication. In the proposed controller, reactive power sharing is realised through the adaptive virtual impedance, whose coefficient is set to the square of the reactive power sharing ratio. Only inductive virtual impedance is adopted by using the absolute value of the reactive power. The proposed controller only uses local information. Its reactive power sharing accuracy and the virtual impedance design principle are analysed and explained. Small signal stability of an inverter equipped with the proposed controller is analysed. It has been shown that the reactive power sharing error of the proposed controller could be reduced by less about 50% compared to conventional droop control. Real-time simulation results are submitted to verify the effectiveness.

Losses on low-voltage networks are often substantial. For example, in the UK they have been estimated as being 4% of the energy supplied by low-voltage networks. However, the breakdown of the losses to individual conductors and their split over time are poorly understood as generally only the peak demands and average loads over several months have been recorded. The introduction of domestic smart meters has the potential to change this. How domestic smart meter readings can be used to estimate the actual losses is analysed. In particular, the accuracy of using 30 min readings compared with 1 min readings, and how this accuracy could be improved, were investigated. This was achieved by assigning the data recorded by 100 smart meters with a time resolution of 1 min to three test networks. Smart meter data from three sources were used in the investigation. It was found that 30 min resolution data underestimated the losses by between 9 and 24%. By fitting an appropriate model to the data, it was possible to reduce the inaccuracy by ∼50%. Having a smart meter time resolution of 10 min rather than 30 gave little improvement to the accuracy.

Load current may become highly distorted in a weak power system network due to the presence of non-linear and dynamic loads. Harmonics get penetrated into the supply system too; thereby making it polluted and rich in harmonic content and causing a detrimental effect on the performance of other connected loads. In such cases, the conventional control algorithms fail to work effectively to mitigate power quality (PQ) issues. This study addresses solutions to PQ issues which get aggravated in the presence of distorted supply. This study proposes a multiple complex coefficient filter (MCCF)-second-order generalised integrator (SOGI)-based controller designed to effectively compensate for PQ problems associated with weak grid. A MCCF filter is designed to extract the fundamental components of grid voltage used further for grid synchronisation. The SOGI is designed to extract the fundamental active current magnitude of the load current and reduce PQ issues with the help of Distributed Static Compensator (DSTATCOM). Neutral current compensation is achieved with an appropriately designed zigzag transformer. Extensive simulation and hardware results realising dSPACE 1104 as Digital Signal Processor are considered in this study to show that the performance of the proposed control algorithm under PQ issues with distorted grid.

Optimal placement of switches can play a key role in providing resilience to power distribution systems against major faults caused by natural disasters. This study presents a resilience-based framework for optimal switch placement in distribution systems being consistent with the expansion plans of distributed generation units. At first, the impact of hurricanes on distribution system components is modelled using the geographic information system of distribution grid and the strength of components against extreme weather-related events. Then, a new resiliency index is proposed to assess the resilience of distribution grids. This index is involved in a mathematical model of the switch placement problem and the obtained formulation is modelled as a mixed integer linear programming optimisation problem. The presented framework is implemented on two test systems, i.e. an illustrative test system and Bus 4 of the Roy Billinton test system. The results prove the effectiveness of this approach to improving the resiliency of distribution systems.

Half-bridge modular multi-level converter-based multi-terminal HVDC (HB-MMC-MTDC) technology is increasingly adopted as a promising option in the power transmission and distribution fields. However, how to cut off DC fault currents safely and ensure the continuous operation of the healthy parts of the HB-MMC-MTDC system under DC faults presents a huge challenge. This study proposes a generalised protection strategy on the use of a new RL-fault current limiter (FCL) branch and hybrid DC circuit breakers (CBs), to deal with the bipolar DC faults for a given HB-MMC-MTDC system. It contributes to cut off the DC fault current before triggering MMC blocking, without influencing the continuous operation of the healthy parts of MTDC system. The operation characteristics of hybrid DC CBs and the equivalent circuit for the DC fault current is introduced, and the mathematical model of the DC fault current with the new RL-FCL is discussed in detail. Theoretical and data analyses are performed to obtain the feasible parameters of the RL-FCL. Simulation tests of an HB-MMC-MTDC system with different topologies are performed in PSCAD/EMTDC to validate the effectiveness of the generalised protection strategy.

Aimed to clarify the correlation characteristics between the internal partial discharge (PD) in the negative direct current (DC) gas-insulated system (GIS) and gas pressure, and to establish an insulation fault diagnosis method based on decomposition component analysis, this study on PD decomposition of sulphur hexafluoride (SF₆) was conducted under different pressures on the basis of constructing a SF₆ decomposition experimental platform under DC PD. A stainless steel needle-plate electrode was used to simulate the insulation defects of metal protrusions in GIS. SOF₂, SO₂F₂, CO₂, SO₂, and CF₄ data generated from SF₆ decomposition were obtained under different pressures. The variation law of component concentration and effective characteristic ratio with pressure were analysed in detail. In addition, a mathematical formula for pressure and decomposition components was deduced according to gas micro-ionisation theory. The effective content and formation rate were defined to validate the relationship. Results show that the concentration of SF₆ decomposition components decreased gradually with increasing pressure with a strong regularity. Furthermore, the relationship between pressure and component concentration derived from the theory can explain the relationship between the effective content of SF₆ decomposition components and the effective formation rate and pressure variations.