On the basis of the relation among natural frequency of travelling wave, fault distance and reflect coefficient at the terminal of transmission line, a novel transmission line protection scheme is proposed in this study. The multiple signal classification method is employed to extract the dominant natural frequency through the spectrum analysis of fault travelling wave. Performance of the proposed transmission line protection algorithm is studied through detailed simulations carried out using the electromagnetic transient simulation software PSCAD/EMTDC. The method proposed in this study does not need identifying the surge arrival time. Therefore it is more robust compared with the traditional travelling-wave-based protection scheme. The effect of fault resistance on the proposed protection scheme is also discussed in this study. The simulation results have shown the proposed method is valid and can distinguish internal faults from external faults correctly.

The main aim of this study is to estimate long-duration voltage variations considering uncertainties associated with stochastic fluctuations in the output power of the wind distributed generation (DG) and system load. In the proposed methodology the uncertainties were represented using the time series models: Fourier analysis and auto-regressive moving average. These models were used in the quasi-sequential Monte Carlo simulation method to generate the system operation scenarios. The Monte Carlo simulation method was also used to model failures in the DG. The proposed methodology to estimate long-duration voltage variations was tested in a test system with 33 buses. The results showed that the insertion of wind DG in the system has a significant impact on the voltage profile. Furthermore, it was demonstrated that failures in DG and fluctuations in the load and wind speed caused large variations on the nodal voltages.

In this study, a non-linear excitation controller using inverse filtering is proposed to damp inter-area oscillations. The proposed controller is based on determining generator flux value for the next sampling time which is obtained by maximising reduction rate of kinetic energy of the system after the fault. The desired flux for the next time interval is obtained using wide-area measurements and the equivalent area rotor angles and velocities are predicted using a non-linear Kalman filter. A supplementary control input for the excitation system, using inverse filtering approach, to track the desired flux is implemented. The inverse filtering approach ensures that the non-linearity introduced because of saturation is well compensated. The efficacy of the proposed controller with and without communication time delay is evaluated on different IEEE benchmark systems including Kundur's two area, Western System Coordinating Council three-area and 16-machine, 68-bus test systems.

In this study, the role of self-validated computing for solving the energy hub-scheduling problem in the presence of multiple and heterogeneous sources of data uncertainties is explored and a new solution paradigm based on affine arithmetic is conceptualised. The benefits deriving from the application of this methodology are analysed in details, and several numerical results are presented and discussed.

This study proposes a new forecasting method for short-term spot prices in the Nordic power market. It proposes a Cuckoo search Levenberg–Marquardt (CSLM)-trained, CSLM feed-forward neural network (CSLM-FFNN) for the solving process that combines the improved Levenberg Marquardt and Cuckoo search algorithms. The proposed model considers actual power generation and system load as input sets to facilitate the efficient use of both transmission and power generation resources by direct market participants. During the training, the proposed CSLM-FFNN model generalises the relationship between the area prices and the system price for the same period. The model can be updated to track online the variation trend of the electricity price and to maintain accuracy because of the rapid training speed in CSLM learning algorithm. The developed model is tested with publicly available data acquired from the Nord Pool, and the model's performance is compared with state-of-the-art artificial neural networks and time-series models. Besides, the proposed approach is applied to forecast market-clearing price in the Spanish electricity market, to further assess the validity of the approach. The results show that the proposed CSLM-FFNN exhibits superior performance than other methods in terms of forecasting accuracy and training efficiency.

It is very helpful for power system operation to assess and forecast the uncertainty of the load forecasting. The improved credibility assessment index of the short-term load forecasting results is presented to assess the uncertainty in this study. The forecasting method for credibility of short-term load forecasting is also proposed by adopting genetic algorithm-based back propagation neural network. In the case study, it is proved that the improved credibility assessment can evaluate the short-term load forecasting results and the forecasting methods. Meanwhile, the credibility forecasting can contribute to optimise reserve capacity in power system scheduling.

In this study, reliability and economic-driven capacitor allocation problem in electrical distribution system is investigated for a definite planning horizon considering several technical and economic aspects. Also, the system reliability modelling is performed based on a new approach, which is considering values of reactive component of currents flowing through branches of the feeder and applying different feeder's failure rate models. The aim of this study is minimising total cost of the system including system power loss cost, system risk cost, investment cost and maintenance cost. Herein, in order to achieve practical outcomes, inflation and interest rates as the economic factors considered in the planning, and yearly load growth, hourly and daily varying load, and customers’ load types are applied in the modelling, and also load model-based power flow is run rather than simple power flow. In this study, it is demonstrated that considering unreal model for the system load types or ignoring dependence of system reliability on the reactive component of current can significantly affect the results of the capacitor placement problem and also it can impose extra cost to the local distribution company.

In this study, the three-phase four-wire shunt active power filter (ShAPF) dealing with non-ideal point of common coupling (PCC) voltages will be presented. The instantaneous power theory is applied to design the ShAPF controller which shows reliable performances. An adaptive notch filter (ANF) is proposed to process those unbalanced and/or distorted PCC voltage. The power balance among utility, load and ShAPF while applying ANF is clarified by an in-depth explanation. The simulation results prove that the ANF can successfully facilitate the ShAPF in terms of compensating unbalanced/distorted current of loads under a non-ideal PCC voltage circumstance.

Fault location estimation in series compensated transmission lines is quite difficult because a non-linear current dependent circuit appears between the substation and fault point. In particular, the faults which occur at different locations at the same time in different phases known as multi-location faults has not been addressed by researchers. Other types of fault that may occur in transmission lines are transforming faults where one type of fault transforms to another type fault after some time. In this study, a fault location estimation scheme using artificial neural network (ANN) is presented for multi-location faults, transforming faults as well as for commonly occurring shunt faults in thyristor controlled series capacitor (TCSC) compensated transmission line. DB-4 wavelet is used for pre-processing of the three-phase current and voltage signals. The shunt capacitance of the line is considered based on distributed parameter line model. Feasibility of the ANN-based fault location algorithm is tested under a wide variation of parameters, such as fault type, location, fault resistance and fault inception angle. Fault location errors are within 0.001–1% range.

In this study, a transmission line model described in the q–s domain (spatial frequency–temporal frequency) is applied to obtain transient voltage and current profiles along field-excited multiconductor lines (also known as illuminated lines). The incident field excitation is incorporated into the model by means of Taylor's formulation, in which such field is included by means of series voltage and shunt current sources distributed along the line. For the case of lines excited by an indirect lightning stroke, the corresponding field is computed according to the formulae proposed by Master and Uman. The inverse numerical Laplace transform is applied successively (twice) to obtain the results in the z–t domain, corresponding to the voltage and current profiles along the illuminated line. An initial validation of the model consists of two examples, in which simple analytical expressions are introduced for the voltage and current sources (separately) along the line in order to provide comparisons with alternative transients programme/electromagnetic transients programme. Then, three test cases corresponding to lightning strokes at different locations near the line are considered. Power system computer-aided design/electromagnetic transient design and control is used in this section for validation purposes.

Voltage source converters (VSCs) are widely used in microgrids to interface the renewable resources with the electrical network. In autonomous microgrids with the dc distribution network, the optimal dc voltage reference for the one VSC that operates in the voltage regulator mode and the optimal reference power settings of the remaining VSCs working in the power dispatcher mode have to be pre-determined. Emulating the utility grid, these settings and control modes are commonly selected such that the dc voltage is maintained within desired margins, typically ±10% around the rated value. In this study, the objective function is minimisation of the converter and distribution line losses. All the operational modes and limits of VSCs have been taken into account. Genetic algorithm has been utilised in solving the optimisation problem. Owing to limited available power from renewables, reducing the converter and distribution system losses will enhance the survivability of the microgrid and ease the cooling requirements, resulting in a more compact system. A model of a 20-bus microgrid with the dc distribution network is employed to verify the effectiveness of the presented optimisation algorithm.

This study presents a novel method for robust transmission network expansion planning (RTNEP) considering intermittent renewable energy generation and loads. The investment cost of transmission line and operating cost are considered as the objective function of the planning. This study proposes to select the suitable scenarios to make the robust expansion plan for all possible scenarios based on intermittent renewable energy generation and loads data in a year. Meta-heuristic algorithm called adaptive tabu search (ATS) is employed in the proposed RTNEP. ATS iterates between the main problem, which minimises the investment cost and operation cost and the subproblem, which minimises the total power generation of conventional generators and curtailments of renewable energy generation and loads. This study uses AC load flow based on Newton–Raphson method and non-linear programming (NLP) based on interior point method for solving the main problem and the subproblem, respectively. IEEE Reliability Test System 79 (RTS 79) is used for testing the proposed method. The results show that the proposed expansion plan is more robust than the solutions from other research works.

This study presents a new method for allocation of network losses to distributed generations (DGs) and consumers connected to radial distribution networks in context of liberalised electricity market. The study intends to deal with three aspects, namely, issue of non-linear relation between power flow and losses, change in network losses because of voltage variation and contribution of DG to the network loss. The proposed method is a branch-oriented approach based on tracing the real and reactive power of DGs and loads. It establishes a direct relationship between sending and receiving node voltages and apparent power available at the receiving node of a branch. It allocates the losses without any assumptions and approximations by employing backward sweep network reduction technique. The proposed method is simple and effective; and requires only the power flow solution to allocate the losses to DGs and loads. Pro rata method, which is based on the power rating of generators and consumers, is revisited and modified according to branch oriented approach. To show the effectiveness of the proposed method, it has been tested on two test networks, that is, 28- and 33-node test networks. The obtained results are presented, discussed and compared with other published methods.

In recent years new FACTS devices based on voltage-source converters (VSCs) have been investigated. Unified interphase power controller (UIPC) is one of these novel FACTS controllers and the other one is VSC-based interphase power controller (VSC-based IPC).The purpose of this study is to investigate and compare the performance of distance relays on transmission lines in the presence of VSC-based IPC and UIPC, while working in power flow control mode. Simulation results show that the distance relay sees the higher apparent impedance in the presence of proposed FACTS devices. Detailed simulations for different faults types and locations are evaluated. Moreover, the impact of the FACTS device location on the apparent impedance seen by the relay is discussed.

Torsional damping controllers, such as supplementary excitation damping controllers (SEDCs), are widely used to stabilise subsynchronous resonance (SSR) induced by torsional interactions (TIs) between turbo-generators and series-compensated power systems. However, because of the changeable operating situations of a power system, it is a great challenge to design them to guarantee torsional stability under all possible operating conditions. This study proposes a global optimal control-design procedure for tuning SEDCs to accommodate the variation of system conditions. Considering TI is a small-signal stability issue, the non-linear power system is converted into a family of linear parameter varying models and the parameter-tuning task for multiple SEDCs is formulated into a multi-model constrained non-linear optimisation problem. A global optimisation procedure based on genetic algorithm and simulated annealing is designed to efficiently solve this problem and obtain a set of robust or several sets of gain-scheduling SEDCs. The proposed method is applied to a multi-machine series-compensated power system. The results of both eigenvalue analysis and time-domain simulation have fully demonstrated the effectiveness of the optimised SEDCs in stabilising SSR under all possible operating conditions.

The cross-border trading in an interconnected multi-area power system (MAPS) has significantly increased in recent years. In this situation, the coordination of electricity markets in MAPS is very imperative. In this study, in the presence of multiple markets in an MAPS structure, it is assumed that there is a single market in each area, and the participation of external players in each market is possible. A market-based mechanism for power exchange management is designed by a proposed central coordinator entity. In this mechanism, two main roles are considered for the coordinator, namely, the determination of the external network equivalents for each area, and the management of power exchange in an iterative decision-making process to maintain system security. The designed mechanism uses the proposed power exchange management factors matrix. Then, a market process is run for the management of external player's exchanges. The numerical results for a small-scale (15-bus) test system as well as the IEEE RTS-96 system are presented to demonstrate the effectiveness of the proposed mechanism.

The power system networks can be adversely affected by indirect coupling with the cloud-to-ground lightning return stroke. In most computations of lightning-induced voltages on overhead transmission lines, the overhead transmission lines are considered as straight lines and the return stroke channel is assumed to be a straight and a vertical channel. However, in reality, the line is not straight and is not parallel to the ground level because of the sag produced by its weight. In addition, the lightning channel is most often inclined. This study studies the effect of conductors’ sag as well as the inclination angle of the lightning channel on the lightning-induced voltage on the three-phase power lines because of inclined lightning channel. This study has been evolved, formulated and applied on Egyptian 500 kV three-phase transmission line. Moreover, the effect of the ground conductivity on induced overvoltages in case of sagged transmission lines is considered. It can be observed that, taking into account the effects of the ground conductivity, the presence of the ground wire and the sag of the transmission lines reduce the values of the calculated induced voltages.

The study presents an advanced Bayesian technique to carry out availability analyses of photovoltaic inverters (PVI) in presence of uncertain reliability data. In order to take proper into account the above uncertainty, PVI hazard rate and repair rate are considered as random variables characterised by proper log-normal and/or Gamma distributions. These assumptions are adequately motivated by well-known and established physical and mathematical considerations. In this manner the photovoltaic availability uncertainty can be expressed as a function of the component uncertain data. Afterwards, thanks to the tailored Bayesian technique the authors demonstrate how, even in presence of scarce data, an efficient updating of the system performance can be accomplished during the PVI operating life. The methodology is really useful in view of an optimal allocation of the components’ reliabilities at the design stage and to establish the actual expected payback of the whole photovoltaic system. Extensive numerical simulations confirm the effectiveness and the validity of the developed Bayesian technique by also verifying its inherent robustness and efficiency through a rigorous analysis.

Microgrid (MG) contains large scales of flexible components, so the traditional distribution network equivalent method is not applicable in MG equivalent research. In this study, a novel MG model structure considering the influence of control strategy on the external characteristics of MG is presented, in order to make measurement-based modelling approach more suitable for equivalent research of MG. The proposed model is a non-mechanism model which can restore the dynamic characteristics of MG better, and the parameters identification of the model is solved by improved immune algorithm. Finally, through the fault validation way the effectiveness of the model is demonstrated.

This study presents a new approach based on a binary fish swarm algorithm (BFSA) and dynamic economic dispatch (DED) method for generation companies (GENCOs) profit (PF)-based unit commitment (PBUC) problem considering power and reserve generations simultaneously in a day-ahead competitive electricity markets. BFSA is used to decide the units on/off status, whereas the optimum dispatch solution is determined using DED method with modified unit generation limits because of ramp rate constraints over the complete scheduled time horizon. To avoid the search to get trapped at a local optimal solution, swap move-based local search and cyclic re-initialisation operators are embedded in BFSA. Moreover, two strategies for selling power and reserve are considered in problem formulation and implementation phase. Its effectiveness is validated on 10 and 100 thermal units in a day-ahead electricity market in terms of GENCOs PF and computation time. The results obtained for PBUC problem with BFSA method have been compared with those obtained with priority list, dynamic programming, Lagrange relaxation, genetic algorithm and binary artificial bee colony algorithm, and BFSA has been found effective to achieve quality solutions in reasonable computation time.

This study proposes a unified power flow controller-based oscillation damping controller for use with a permanent magnet synchronous generator-based offshore power farm. A novel intelligent damping controller (NIDC) was used to increase the stability of power control and improves the performance, where the proposed NIDC consists of the adaptive critic network, the functional link-based Elman neural network (FLENN), the genetic ant colony optimisation algorithm (GACO) and proportional–integral-derivative (PID) linear damping controller. The PID damping controller analyses complex eigenvalues based on the theory of modern control. The node connecting weights of the FLENN and critic network are trained online. A GACO approach is developed to adjust the learning rates and thus improve the learning ability. The proposed NIDC can achieve better damping characteristics, and the internal power fluctuations can also be effectively alleviated.

Subsynchronous resonance (SSR) has three categories, namely induction generator effect, torsional interaction and torque amplification. Bypass damping filter (BDF) was generally considered particularly effective for the induction generator effect. In this study, it is shown that BDF is also an effective countermeasure for torsional interaction and transient torque amplification. In addition, it can help reduce transient overvoltage of the series capacitor in a series compensated system. The parameter tuning method for BDF is proposed, based on electrical damping analysis and criterion for torsional stability. The SSR damping effectiveness of BDF in a series compensated system is verified by electrical damping analysis, torsional mode analysis and time-domain simulation.

In many countries, it is common for medium voltage (MV) and low voltage (LV) to share the same pole and power line corridor, and this has been a general practice for decades. The MV line and the LV line separation distance may be short under some situations; therefore the mutual coupling may become substantial, which can have a significant impact on network voltages. In the literature, such coupling effect is generally ignored, and there is a lack of a detailed model of the coupled MV and LV lines for incorporation into load flow programs. This study develops a model for unbalanced distribution lines considering the mutual coupling between different voltage levels. Then the established model is utilised in a current injection load flow program to analyse the MV/LV coupling impacts on distribution system voltage.

This study deals with power quality improvement in a diesel generator (DG) set-based standalone supply system feeding three-phase four-wire(3P4W) loads. The proposed system consists of a diesel engine, three-phase wound field synchronous generator, a four-leg voltage source converter (VSC) and3P4W loads. The four-leg VSC with a capacitor connected on its DC link is used for neutral current compensation and unity power factor operation of the DG set. In addition, the VSC provides harmonics elimination and the load balancing. The voltage of the DG system is controlled by excitation control of the synchronous generator and the frequency is controlled by speed regulating system of the diesel engine. The speed of the engine is regulated by controlling the fuel injection of the diesel engine. An adaptive theory-based notch filter algorithm is used to extract fundamental component of the load currents for estimation of reference source currents.

Reliable detection of islanded operation is essential in distribution systems with large penetration of the distributed generation. Commonly-used protections present performance limitations in terms of sensitivity and stability. To overcome such limitations, this study proposes to enrich classical protections by adding a passive islanding detector based on a new method. It adopts a linear representation of the low voltage distribution system, referred to as Thevenin-like model. On the basis of the voltage and current measures at the detector installation point, two model parameters are estimated and are used to distinguish islanded from grid-connected operation. The proposed detector presents high sensitivity and reliability, does not require expert tuning, can be installed in different points of the distribution system and is economically viable. Numerical analysis and simulations, evidence the effectiveness of the proposed method.

Bayesian network (BN) is a strong framework for handling probabilistic events which have received limited attention in power system reliability assessment. By applying BN for bulk power system reliability assessment, additional capabilities are provided at modelling and analysis levels in comparison with conventional methods. This study proposes a methodology to apply BNs to composite power system (CPS) reliability modelling, reliability assessment and reliability-based analyses. A minimal cutset (MC)-based method is proposed to extract the BN structure. Moreover, BN parameters are defined based on logical relationships between components, MCs and system failure. In addition, some issues of BN application to large systems are investigated. A variety of reliability-based analyses, useful in different power system studies are introduced and discussed in details which are provided by applying BNs to CPS reliability. The computational efficiency of the presented method is demonstrated by comparing it with state enumeration and Monte Carlo simulation methods. The proposed methodology is implemented on Roy Billinton Test System to extract its BN model based on which analysis issues are considered. Finally, the proposed methodology is applied to the simple, but representative, system the IEEE-reliability test system to show its feasibility in larger systems.

In this study, a transient stability constrained-optimal power flow (TSC-OPF) model is proposed and applied to a real case in the currently interconnected Balearic Islands-Iberian Peninsula system. The TSC-OPF retains the dynamics of all generators in the islands with fourth degree transient synchronous generator models and includes a representation of a high-voltage direct current (HVDC) link on the inverter side. The proposed large-scale non-linear optimisation problem, programmed in GAMS and solved using the CONOPT tool, is used to assess the economic impact of the HVDC on the Balearic Islands generation cost under different circumstances, using TSC-OPF and traditional OPF on the dispatch. Different recovery patterns of the HVDC link after a severe fault in the transmission grid are evaluated from the viewpoint of the cost and stability of power generation.

The impedance parameters of overhead transmission lines are fundamental input data for various power system studies. The data are traditionally calculated based on the structure information of a line. This study proposes a method for estimating the parameters using fault records captured by digital relays. The fault records are the unsynchronised voltage and current waveforms recorded at both ends of a line. One of the main contributions of this work is the use of the wave propagation speed equation to simplify the problem and to improve the estimation accuracy. As a result, both the positive and zero sequence parameters can be estimated using simple algorithms in a decoupled solution process. Simulation results show that the proposed approach has good accuracy. Finally, the method was applied to estimate the impedance data of several actual transmission lines based on the fault record data provided by a utility company.

This study examines how environmental and socioeconomic criteria affect renewable energy resources (RES) distribution strategic plans regarding national energy policies. Four criteria are introduced with respective coefficients properly formulated to quantify their capacity. Moreover, these coefficients are properly normalised to combine the effect of each criterion under a uniform formulation. The base case scenario in this work considers an initially available capacity of RESs to be equally distributed among the candidate regions. Six scenarios about different prioritisation are examined. The results prove that different prioritisation criteria yield significant variations regarding the assigned regional RES capacity. The proposed algorithm defines optimisation only by terms of predefined prioritisation criteria; each solution could be considered optimal given that the respective installation strategic plan is subject to specific weighted criteria. The advantages of the proposed algorithm rely on its simplicity and expandability, since both coefficients formulation and resizing procedure are easily performed, as well as additional criteria could be easily incorporated in the resizing procedure. Thus, this algorithm could be considered as a multi-objective planning tool regarding long-term strategic plans for nationwide RES distribution.

Harmonics originated by non-linear elements connected to power systems cause unwanted harmful technical problems. In this study a novel probabilistic harmonic load flow based on a point estimate method has been proposed. The proposed method surpasses the previous point estimate methods (PEMs) when generalising the approach to multiple random variables with various probabilistic distributions. Addressing the results of the Monte Carlo simulation (MCS) method as reference, the fast PEM has been applied to a modified version of the IEEE 14 bus test system and the advantages of this new method are highlighted. The results reveal less computational burden and time compared with the MCS method while the accuracy remains at a high level.