Residential rooftop-mounted solar photovoltaic (PV) panels are being installed at an increasing rate, both in New Zealand and globally. There have been concerns over possible issues such as overvoltage and overcurrent. These PV systems are mostly connected at low voltage (LV). This study presents a case study of simulating the entire LV network from a single utility, comprising 10,558 11 kV–415 V transformers and their associated distribution feeders. These results are also presented by network type. Various solar PV penetration levels are added to the model and the power-flow results are presented. From these results, possible maximum limits of solar PV penetration are investigated and measures to alleviate overvoltage problems are simulated. The effect of using PV inverters with voltage regulation is simulated. Results show that some minor overvoltage problems can be expected in the future, particularly in urban areas. However, in most cases the overvoltage would not be much higher than the statutory limit of 1.06 p.u.

Due to the uncontrollability of renewable energy resources, micro-grids (MGs) often have to exchange excessive or insufficient power with the utility grid in traditional non-cooperative mode. In contrast, power transaction considering direct energy trading between MGs has been considered as a promising method to improve economic efficiency. Specifically, MGs with complementary power surplus or shortage have an incentive to cooperate with each other and perform direct trading due to lower costs and power losses. In this study, the authors focus on comprehensive economic power transaction of the multiple MGs network with multi-agent system. A three-stage algorithm based on coalitional game strategy is proposed consisting of request exchange stage, merge-and-split stage and cooperative transaction stage. The developed algorithm enables MGs to form coalitions, where each MG can exchange power directly by paying a transmission fee. With local power transaction, MGs can minimise their expenditures comprising the generation costs, transmission costs, power losses and load shedding compensation; hence, ensure the cost efficiency of the whole MGs network. Moreover, the implementation of load shedding is discussed and its benefit is demonstrated. Simulation results show that the proposed cooperative scheme significantly reduces the total cost of MGs compared with the non-cooperative method.

This study proposes an approach to optimally allocate multiple types of flexible AC transmission system (FACTS) devices in market-based power systems with wind generation. The main objective is to maximise profit by minimising device investment cost, and the system's operating cost considering both normal conditions and possible contingencies. The proposed method accurately evaluates the long-term costs and benefits gained by FACTS devices (FDs) installation to solve a large-scale optimisation problem. The objective implies maximising social welfare as well as minimising compensations paid for generation re-scheduling and load shedding. Many technical operation constraints and uncertainties are included in problem formulation. The overall problem is solved using both particle swarm optimisations for attaining optimal FDs allocation as main problem and optimal power flow as sub-optimisation problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

A joint active and reactive power reserve market is presented in this study. Reactive and active powers are closely related through some issues such as load flow equations, network line current limitations and synchronous generator capability curve. The proposed solution deals with simultaneously determining of optimal capacities of active and reactive power reserve after administration and settlement of active and reactive power markets separately. Three following objectives would be met in the proposed joint market while satisfying constraints of network and producing units in all contingencies: i Minimising cost of required simultaneous active and reactive power at each contingency. ii Minimising unsupplied energy due to lack of active power at each contingency. iii Minimising unsupplied energy due to insufficiency of reactive power. IEEE 24 bus RTS system is used for evaluation of the proposed market and results have been compared with those from traditional separate active power reserve markets.

A DC microgrid (DC-MG) provides an effective mean to integrate various sources, energy storage units and loads at a common dc-side. The droop-based, in the context of a decentralised control, has been widely used for the control of the DC-MG. However, the conventional droop control cannot achieve both accurate current sharing and desired voltage regulation. This study proposes a new adaptive control method for DC-MG applications which satisfies both accurate current sharing and acceptable voltage regulation depending on the loading condition. At light load conditions where the output currents of the DG units are well below the maximum limits, the accuracy of the current sharing process is not an issue. As the load increases, the output currents of the DG units increase and under heavy load conditions accurate current sharing is necessary. The proposed control method increases the equivalent droop gains as the load level increases and achieves accurate current sharing. This study evaluates the performance and stability of the proposed method based on a linearised model and verifies the results by digital time-domain simulation and hardware-based experiments.

Circuit breaker (CB) is a component providing significant electrical protection for power transmission and distribution systems. Hence, an effective condition monitoring system for the CBs is of imminent importance. This study presents a fuzzy-probabilistic-based condition assessment algorithm to assess the CB operation performance by monitoring its trip/close coil current (C.C.), and suggests a simple yet effective condition assessment tool. The C.C. patterns are acquired by measurements carried out on 60 CBs (72.5 kV, SF₆) under faulty and normal conditions. To intelligently assess the CB's operating state (i.e. normal, alarm and emergency), in terms of its reliability, the optimum C.C. features with minimum interdependence were obtained. Furthermore, a fuzzy-probabilistic method is proposed based on the results of the statistical analyses of the features. The feasibility and applicability of the proposed method in CB condition assessment is verified against the experimental measured data.

Circuit breakers (CBs) play a crucial role in power system reliability. Most CB failures observed in the field are related to operating mechanism. One of the useful approaches to effectively diagnose the mechanism failures of CBs is based on the trip coil current signatures. Using the simulation tool MapleSim, this study proposes a simulation model of CB trip mechanism to identify the CB failures and their causes. The impacts of intentional abnormalities on the trip coil current taken from the field testing of trip mechanism are scrutinised. The intentional abnormalities include trip coil operating voltage, trip coil circuit resistance, and shaft gap. To validate the effectiveness of the proposed MapleSim simulation model, the work made the trip coil current comparison between computer simulation and field testing. In this study, the field testing data are gathered from 23 kV gas insulated switchgear with good and various faulty conditions. The simulation-based findings in this study provide a useful and valuable insight into the CB trip mechanism failures, offering more diagnostic advice to maintenance personnel. The proposed results are of great interest in CB diagnosis.

Many methods have been proposed to determine the optimal location and capacities of distributed generation (DG) units to reach the lowest value for system losses. In this study, the combination of analytical and genetic algorithm methods is used for optimal allocation of multiple DGs in a distribution network to minimise the system losses. This combination guarantees the convergence accuracy and speed in multiple DG units allocation. In this study, the DGs active power, power factor, and location are simultaneously considered during distribution network losses minimisation. The utility will dictate only the maximum DG power generation if the DG is installed by DG owner. However, both of the size and the location of DG will be determined by the utility if the DG is installed by it. The proposed method is applied to 33-bus and 69-bus test distribution systems. Simulation results show that the proposed method results in lower losses compared with the other methods.

This study proposes a novel scheme using mathematical morphology to effectively discriminate between the internal fault and inrush currents of power transformers. The proposed scheme consists of two parts. The first part is based on morphological gradient (MG), for discrimination of currents occurring without considering the current transformer (CT) saturation. The second one uses a symmetrical criterion involving MG to identify internal fault current under CT saturation. To demonstrate its compatibility and efficiency, the scheme is verified employing the data simulated using PSCAD/EMTDC and data collected from laboratory experiment, respectively. The simulation and experimental results indicate that the proposed scheme can improve the accuracy of inrush current identification, even under certain extreme conditions.

Reactive power markets have received special attention in recent years due to the importance of reactive power for maintaining network stability and freeing up the capacity of transmission lines. Hence, this study tries to improve this market and encourage fair competence in reactive electrical power generation through improving the unit pricing process. On the other hand, simultaneous active and reactive power markets are implemented by this study in order to account for energy market and reactive power market interactions. A new structure for paying lost opportunity costs to reactive power producers is presented here which is aimed for improving this market. Additionally, considering local nature of reactive power, the new method of holding simultaneous market using regional reactive power is proposed and pertaining results are compared with separate, non-local market. Finally, the effect of increments in prices proposed by effective units in reactive power market on implementation costs have been compared with separate and simultaneous markets, in order to investigate efficiency of active and reactive simultaneous markets.

This study presents an integrated approach for reliability planning and risk estimation in active distribution systems. By incorporating the use of accurate reliability equivalents for different medium voltage/low voltage networks and load subsectors, a probabilistic methodology is proposed to capture both power quality and reliability aspects in power system planning, which potentially avoids the underestimation of system's performance at bulk supply points. A ‘time to restore supply’ concept, based on security of supply legislation, is introduced to quantify the effect of different network functionalities such as the use of backup supply or automatic/manual reconfiguration schemes. The range of annual reliability indices reported by 14 network operators in the UK is also used for the validation of reliability results, which allows estimating the risk of interruption times above the regulator-imposed limits. Accordingly, conventional reliability assessment procedures are extended in this study by analysing a meshed urban distribution network through the application of a time-sequential Monte Carlo simulation. The proposed methodology also acknowledges the use of time-varying fault probabilities and empirical load profiles for a more realistic estimation of customer interruptions. A decision-making approach is shown by assessing the impact of several network actions on the accuracy of reliability performance results.

The Publisher is retracting this article, 'Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation', IET Generation, Transmission and Distribution, 2016, 10, (1), p. 107-114, DOI: 10.1049/iet-gtd.2015.0473. The paper has been retracted due to an overlap with a previously published paper by the authors, entitled “Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program,” Energy Conversion and Management, October 2015, 103, (1), pp. 1008-1018.

As a consequence of privatisation and deregulation of the electric power market, there is a marked increase of scheduled power that flows in the transmission line and also the spontaneous power exchanges leading to complex power transmission congestion problems. The proper placement of interline power flow controller (IPFC) can improve the transmission line congestion problem to a great extent. This study proposes a method for optimal placement of IPFC based on disparity line utilisation factor (DLUF) and firefly algorithm (FA)-based optimal tuning for a multi-objective function to control the congestion in transmission lines. DLUF determines the difference between the percentages mega voltage ampere (MVA) utilisation of each line connected to the same bus. The IPFC is placed in the lines with maximum DLUF. This method has been implemented on an IEEE 30-bus system and the results have been presented and analysed. Optimal tuning of IPFC at the proposed location is carried out using FA for a multi-objective function consisting of active power loss, total voltage deviations, security margin and capacity of the installed IPFC. The tuning of IPFC is also carried out using genetic algorithm. The results obtained have been compared with that of FA for different loading conditions.

An efficient power flow solution is highly important for power system analyses. Traditionally, LU decomposition-based direct method is dominant in solving linear systems in the power flow analysis. However, with the increasing scale and complexity, direct methods may suffer scalability issues, especially under parallel implementation. Therefore, iterative methods such as Conjugate Gradient (CG) are gaining more attention for their scalability and feasibility for parallelisation. To efficiently apply an iterative solver like CG, a preconditioner is usually required. A polynomial-based Chebyshev preconditioner is discussed in this work. An essential parameter in Chebyshev preconditioning is the maximum eigenvalue of the linear system. However, direct calculation of the eigenvalues is too time-consuming to be practical. Therefore, this work proposes a method to estimate the largest eigenvalue to save the time spent on eigenvalue calculation. Thus, Chebyshev preconditioning will be practical to use in power system analyses. This work first proves that the eigenvalues of power system applications range within (0, 2] after a normalisation step, then demonstrates the eigenvalue estimation accuracy, and finally presents the performance improvement. The test shows an average 98.92% runtime saving for the Chebyshev preconditioner, and a 40.99% runtime saving for precondition and iterative solving process.

The smart grid implementation requires real time monitoring and visualisation of the power system networks. This study presents a multi-agent-based multi-area power system dynamic state estimator (MPDSE), suitable for the network that can be divided into sub-areas. In this approach, the sub-areas run MPDSE using field measurements from the remote terminal units (RTUs), as well as from the phasor measurement units (PMUs). The MPDSE is executed for the sub-areas independently and in parallel to save the overall execution time. Software agents are utilised to exchange the information and run the MPDSE for the RTU and the PMU measurements separately, and, then, integrate their results to estimate the final states of a sub-area. The central coordinator consolidates the state estimates of all the sub-areas. The MPDSE is solved by using three approaches based on extended Kalman filter (), unscented Kalman filter, and cubature Kalman filter, and their relative performances are obtained with the help of the simulation results on two test systems.

This study presents a new resistive capacitor switching transient limiter (RCSTL) for mitigating power capacitor switching transients. The RCSTL is composed of three limiting resistors, a three-phase full bridge diode rectifier, a thyristor and a three-phase coupling transformer. The limiting resistors are connected in series with the capacitor bank and the thyristor is installed at the DC side of the diode rectifier. During the capacitor bank energising, the thyristor remains off and hence, the secondary side of the coupling transformer acts as open circuit. Consequently, high impedance including the transformer's magnetic reactance in parallel with the limiting resistors is inserted in series with the capacitor bank. Under such circumstance, the limiting resistors restrain the capacitor switching transients. In the steady-state, the control system triggers the thyristor and the coupling transformer acts as short circuit. As a result, the limiting resistors are bypassed by the coupling transformer and thus, the RCSTL has no significant effect on the circuit. Analytical analysis is performed to describe different operation modes of the proposed RCSTL. A single stage of a three-phase wye-connected capacitor bank with 25 kVAR is energised and the performance of the proposed limiter is investigated. Both the simulation and experimental results confirm the effectiveness of the RCSTL.

Many existing short-circuit calculation (SCC) methods may encounter the issue of divergence in solving distribution systems with distributed generators (DGs) and ZIP (constant power, constant current, and constant impedance) loads. To address this problem, this study presents a robust homotopy-enhanced numerical SCC method for general distribution networks with non-linear loads. Numerical studies reveal that the difference of SCC results between ZIP loads and constant impedance loads can be as large as 37.9% for the IEEE 8500-node test system, highlighting the importance of load modelling in calculating short-circuit currents. To demonstrate its robustness and effectiveness, the proposed method is evaluated on the IEEE 13-bus network and the IEEE 8500-node test system. The evaluation results are very promising. One distinguished feature of the proposed method is that it can assist several existing SSC methods to solve the short-circuit equations of distribution networks with DGs and ZIP loads.

DC optimal power flow (DCOPF) has been widely used in modern power system operation and planning. With the consideration of the stochastic renewable resources integration, an adjustable robust DCOPF is studied in this work in combination with generator participation factors to obtain an optimal solution that can immunise against all realisations of the renewable resource output variability. However, the robust optimisation may lead to an extreme conservative optimal solution compared to the traditional deterministic optimisation. Therefore, the price of robustness is taken into account which provides a tradeoff between the robust optimal solution and the traditional optimal solution for decision makers. According to the duality theory, the robust DCOPF is transformed into a convex quadratic program, which has a large number of linear constraints. In order to efficiently solve the robust DCOPF for applications in large-scale power systems, an inactive constraints reduction technique is introduced to identify the inactive security constraints before solving the proposed model, which greatly improves the computational performance. Numerical results on the IEEE 14-bus, 118-bus and other six large Polish test systems validate the effectiveness of the proposed method.

This study proposes three macroscopic indices to evaluate the quality of AC/DC hybrid power grid structures, which are the corridor strength index, the voltage support strength index and the frequency support strength index. The corridor strength index includes the ratio of the AC corridor strength to the DC corridor strength and the strength of the AC corridor to resist the sudden power transferred from the DC corridor. The multi-infeed effective short-circuit ratio is used as the voltage support strength index to evaluate the voltage support ability for the DC converter stations. The frequency bias factor is adopted as the frequency support strength index to measure the frequency support ability of the power grids. These three macroscopic indices can reflect some important qualities of the AC/DC hybrid power grid structures and provide an effective tool for quantitative assessments of the AC/DC hybrid power grid structures. Application of the three indices in China Southern Power Grid is presented, which proves the validity of the three indices.

In this study a new index is proposed for power system islanding prediction. The total energy absorbed by coherent synchronous generators during unplanned islanding conditions is formulated as an islanding predictor. Decision tree (DT) algorithm is utilised to extract the information gain of the proposed predictor over the input training samples. A comprehensive list of input scenarios, including island and non-island conditions is constructed. The rotor angles of synchronous generators are estimated by phasor measurements at generators’ terminals and used for calculating the predictor over the input samples. The results of DT algorithm are rearranged as a set of if–then rules for practical applications. The proposed method is implemented in the 10-machine 39-bus New-England test system.

This study proposes a novel recurrent multi-objective differential evolution (RMODE) algorithm to solve the constrained reactive power management (RPM) problem, which is a non-linear, multi-objective optimisation problem. Minimisation of total active power loss and improvement of voltage profile are considered as the objectives of the RPM problem. For RPM, generator bus voltage magnitudes, transformer tap settings and reactive power of capacitor/reactor are taken as the decision variables. In the proposed RMODE algorithm, the multi-objective differential evolution (MODE) algorithm has been applied repeatedly using the available Pareto-optimal solutions and re-initialising the remaining population. Thus, for each next cycle of the RMODE, the better values of best compromise solution have been obtained. Effectiveness of the proposed RMODE algorithm has been demonstrated for RPM in the standard IEEE-30 bus system and a practical 75-bus Indian system. Compared with multi-objective particle swarm optimisation (PSO), genetic algorithm toolbox for multi-objective optimisation, MODE and reported results using modified differential evolution and classical PSO, the proposed approach seems to be a promising alternative approach for solving RPM problem in practical power system.

To obtain the optimal trade-off between economy and reliability, this study presents a fuzzy chance constrained programming (CCP) approach to the day-ahead scheduling of virtual power plant (VPP). In this model, uncertain factors in VPP are characterised by fuzzy parameters, and reserve requirements are formulated as fuzzy chance constraints. Considering that economy and risk of VPP are sensitive to different confidence levels (CLs), it is important to select a proper CL for the operator. Different from a pre-given CL in most literatures, this study proposes a method to determine the optimal CL, hoping to provide references for the operator in optimisations involving CCP. A synthetic satisfaction function is introduced, which depicts the satisfaction degree of VPP under different probabilities. Meanwhile, the satisfaction function reflects VPP's distinct attitudes toward risk and profit. A matrix real-coded genetic algorithm combined with Monte Carlo simulation is used to solve this model. To reduce computation burden, the fuzzy chance constraint is converted into its crisp equivalent by utilising credibility theory. Numerical tests are performed in a VPP system, and the best CL is determined through comparing VPP's satisfaction degree under different cases, which prove the validity of the proposed model.

This study proposes a discrete Fourier transform (DFT)-based parametric identification method by using a difference sequence between two sets of frequency data. An autocorrelation function of the frequency difference sequence can be represented as a linear combination of exponentially decaying sinusoidal functions, whose natural frequencies and damping ratios are equal to those of interarea modes. These modal parameters are calculated from the Laplace transform coefficients of the autocorrelation function. The coefficients are estimated by curve-fitting the DFT values of the autocorrelation function. The proposed method is compared with the modified extended Yule Walker method through simulations on signal-to-noise ratio. Finally, the feasibility of the proposed method is shown by identifying real power systems from frequency data of the frequency monitoring network system.

This study is a review of traditional and non-traditional electric power theories. Along with the standard IEEE 1459-2010, other definitions like the currents’ physical components theory, p–q, p–q–r theories are briefly described with the accent on analysis of a priori unknown electric systems. The mathematical definitions were implemented and tested on real measured data, which facilitates the uncovering of some advantages and disadvantages. In the conclusion some of the pros and cons of the undermentioned theories are discussed.

This work is devoted to modelling the AC breakdown voltage in long oil point–plane gaps with insulating barrier by design of experiments (DOE) method. The authors present an experimental study of a laboratory setup that they designed to carry out the influence of geometrical parameters (the position and diameter of the barrier and the distance between electrodes), involved in the process of breakdown. This study is based on the DOE method. However, this method allowed them to propose a mathematical model of the response and leads to reduce the number of laboratory tests.

This study presents a novel optimisation methodology, optimal placement of monitors (OPM_Power), for optimal device/monitor placement in distribution networks. OPM_Power is developed based on gradient search and particle swarm optimisation. The proposed method integrates network topology into search process via spanning trees and uses the historical experience for search guidance. The method is particularly suited for optimal placement problems in power systems. The application is illustrated on the problem of optimal monitor placement for estimation of voltage unbalance in a section of existing UK distribution network and in a generic distribution network. It is demonstrated that the proposed methodology outperforms generic integer optimisation algorithms which are widely used for optimal placement problems in the literature, for example genetic algorithms.

To improve the performance of the conventional distance protection scheme for compensated lines with high resistance faults, an adaptive distance protection scheme is proposed. This study presents an analytical approach for finding the possible impacts of shunt connected flexible AC transmission systems (FACTS) devices such as static synchronous compensator/static volt-ampere reactive (VAR) compensator (SVC) integrated with off-shore wind farm (WF) on distance relay characteristics. Analytical results are presented and verified on simulation platform compares under reach phenomena in presence of both FACTS devices and it is found that under reach is more severe for SVC connected system. Moreover, presence of SVC changes the line characteristic presented to relay even for bolted faults. It is also seen that type of coupling transformer has a considerable effect on apparent impedance. Furthermore, the reach setting of the relay is significantly affected as the relay end voltage and power fluctuates continuously (due to non-linear relationship with speed) when off-shore WFs are connected to power transmission systems. Thus, adaptive tripping characteristics for high resistance line-to-ground fault with shunt-FACTS devices considering appropriate operating conditions is a demanding concern and the same has been addressed in the proposed research work.

This study proposes a quick and effective algorithm for screening severe N − 2 contingency, thus avoiding exhausting analysis of all conceivable N − 2 contingencies. First, the index of overload contribution rate (OCR) is developed on the basis of distribution factor, which is discovered to be long-tailed distributed by statistics. Then, by fully exploiting the discovered feature, the so-called technique of combination of partitioned data sets (TCPDS) is designed and described. The core of the contingency screening algorithm is to apply the TCPDS to the OCR. Moreover, an index system is established to evaluate the proposed algorithm. Finally, the proposed algorithm is proved to be effective and efficient by the index system when applied to some practical power systems.

This study presents a novel algorithm for the optimum placement for underground cable in a concrete duct bank to maximise ampacity and also the lifetime of the cable and fluctuation in the input variables. Fluctuations in the operating temperature cable result from variations in factors such as the ambient temperature, the thermal resistivity of the soil and back fill, as well as the loading of the cable. Operating the cable near or above its thermal rating could have an adverse effect on the aging of the cable insulation subsequently reducing the lifetime of the cable. The algorithm reported in this study considers the factors mentioned above and computes the optimum cable placement in the duct bank by calculating simulated lifetimes for the cables. It makes use of an Arrhenius thermal model to calculate the lifetime of the cable as well as the vector immune system algorithm and interior point method to optimise the placement of the cables in the duct bank. The proposed method has been used in a test case to show how cable placement affects the lifetime of the cables in the duct bank.

The phasor measurement technology has made it possible the monitoring and control of wide-area power systems. In this study, a new genetic algorithm based method for optimal placement of phasor measurement units (PMUs) considering observability and security issues is proposed. The idea is to allocate the least number of PMUs while providing the most redundant set of measurements. This allocation philosophy ensures reliability in the state estimation process. Moreover, the allocation method also takes into account security issues, by preserving the system's observability in case of loss of PMUs. In particular, the loss of a single PMU [(n − 1) criterion] is considered. The proposed method was tested on IEEE standard test systems and the results are discussed and evaluated.