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This paper proposes a new and fast wavelet network based method for estimating the risk of failure caused by lightning overvoltages in arrester protected networks. First, failure risks obtained by simulations are used as the training data for training the wavelet network. The trained wavelet network is then used for accurate and fast estimating of the lightning-related risk of failure of power system apparatus for all possible conditions. The accuracy of the proposed method has been tested and verified under various conditions in the 230 kV network of Sistan–Baluchestan. Performance of the new method has also been compared with several existing methods under same conditions, and the test results show better accuracy of the proposed method. The proposed method not only does not have the restriction of conventional methods, but also it does not have the limitations associated with traditional neural networks based algorithms such as convergence to local optimum points, over-fit and/or under-fit problems. The main contribution of the paper is an accurate (due to proper selection of the training data set based on the k-fold cross validation technique and using wavelet network for estimation), fast (mean calculation time for the network risk of failure computation is 54 s) and simple wavelet network-based algorithm (as compared to the conventional algorithms) for estimating the lightning-related risk of failure of power system apparatus.

In this paper a novel approach regarding the optimal penetration of Distributed Generation (DG) in Distribution Networks (DNs) towards loss minimization is proposed. More specific, a Local Particle Swarm Optimization (PSO) variant algorithm is developed in order to define the optimal active and reactive power generation and/or consumption requirements for the optimal number and location of nodes that yield loss minimization. Thus, the proposed approach provides the optimal number, siting and sizing of DGs altogether. In addition, based on the optimal power requirements of the resulted nodes, a combination of potential DG types to be installed is recommended. The proposed objective function in this paper is also innovative since it embeds the constraint of reverse power flow to the slack bus by the formation of a new penalty term. The proposed methodology is applied to 30 and 33 bus systems. The results indicate the optimal number, locations, and capacity of DG units, which were calculated simultaneously. Finally, the impact of the predefined amount of permissible reverse power flow to the optimal solution is also examined through two scenarios: the first considers zero reverse power flow and the second unlimited reverse power flow.

This paper presents a new approach using swarm intelligence algorithm called Fireworks Algorithm applied to determine Unit Commitment and generation cost (UC) by considering prohibited operating zones. Inspired by the swarm behaviour of fireworks, an algorithm based on the explosion (search) process and the mechanisms of keeping the diversity of sparks has been developed to minimize the total generation cost over a given scheduled time period and to give the most cost-effective combination of generating units to meet forecasted load and reserve requirements, while adhering to generator and transmission constraints. The primary focus is to achieve better optimization while incorporating a large and often complicated set of constraints like generation limits, meeting the load demand, spinning reserves, minimum up/down time and including more realistic constraints, such as considering the restricted/prohibited operating zones of a generator. The generating units have certain ranges where operation is restricted based upon physical limitations of machine components or instability, e.g., due to steam valve or vibration in shaft bearings. Therefore, prohibited operating zones as a prominent constraint must be considered. In this paper the incorporating of complicated constraints of an optimization problem into the objective function is not considered by neglecting the penalty term. Numerical simulations have been carried out on 10 – unit 24 – hour system.

Resistance is an important element in power flow calculation. The accuracy of active power loss calculation depends upon resistance of that branch. Although resistance is a function of temperature rise for pure conductor, conventional power studies neglect temperature effect totally. To calculate exact losses in branch, it is necessary to consider temperature rise in calculation. In a deregulated electricity structure, optimal power flow has been an important tool to assess the economic operation of electricity market. So, the accuracy of optimal power flow is greatly influenced by temperature effect. This paper presents implementation of an efficient gbest-guided artificial bee colony algorithm to solve optimal power flow as well as temperature dependent optimal power flow. This method is tested on IEEE 30 bus system and IEEE 57 bus test system for statistical analysis of gbest-guided artificial bee colony algorithm. This paper also presents the temperature dependent optimal power flow on IEEE 30 bus test system. Effect of temperature rise is also analysed on IEEE 30 bus system, 2383 bus winter peak Polish system and 2736 bus summer peak Polish system.

This paper explores stability issues for integration of distributed generation (DG) resources to the power grid by power electronic converters. Application of power converters in power distribution systems is becoming more and more common. Stability study of this kind of systems is crucial because of the potential for negative impedance instability of interfacing converters. In addition, in a power distribution system, a converter can lead to local instabilities when interacting with other dynamic subsystems. In this paper, to investigate the stability of system, the impedance-based small-signal model of each of the subsystem is respectively achieved and then an active control technique is proposed to stabilize the system. The proposed method depends on reshaping the input impedance of the interfaced converter by injection of an active stabilization signal at the control loop of the converter. MATLAB/Simulink simulations are conducted to demonstrate the effectiveness of the proposed control technique during various operating conditions.

Identifying location and operation of DGs are vital in effective performance of autonomous MGs. This paper gives a novel optimization method for finding the optimal operation and location of DGs. The optimal operation is obtained via setting DGs economic droop parameters which operate based on droop control. A multi-objective function is developed to provide a new problem formulation for finding the optimal operation of DG units. The objectives include the fuel consumption cost, voltage stability index and the total voltage variation of MG. A hybrid optimization algorithm is proposed to solve the problem by combing the harmony algorithm (HS) and mutation and crossover operators of the genetic algorithm (GA). To find the best solution of non-dominated results a fuzzy method is employed. The performance of the paper approach is compared with other optimization and non-optimization methods in MG with 33 and 69 buses using MATLAB. The results support a good performance for the paper approach.

Wind power is a rich, widespread and renewable energy, it is also one of the vitally important alternative energies. Wind power belongs to the renewable energy without pollution, and the power generation by wind can reduce harmful gas released from conventional power generation process with mineral fuel, and then decrease the development of greenhouse effect and acid rain. The wind power has been greatly developed in the global scope with maturing wind power techniques, and will maintain persistent growing. The development and utilization of renewable energy resources is the future development direction. In this paper, taking full account of the fluctuation and unpredictability of wind power, one will put forward two types of fault factor features extraction schemes, fault feature I: Factor coefficients and fault feature II: Factor scores, on the basis of these two schemes, one can realize accurate and reliable fault identification. The research in this paper has direct and practical significance for promoting the large-scale exploitation and utilization of wind energy. And the proposed fault factor features extraction schemes will contribute to the future construction of smart grid.

The hourly wind speed, solar insolation and load power have probabilistic characteristics. However, among them, there are multiple stochastic correlations that are difficult to be modeled using traditional methods. This paper presents a stochastic correlation modeling method using the pair-copula function to capture the multiple stochastic correlations among wind speed, solar insolation and load power. This paper also presents the procedure for generating a synthetic set of stochastic correlated data based on pair-copula function. The proposed modeling method and data generating procedure are incorporated into microgrid reliability and economic evaluation using sequential Monte Carlo simulation. A test on IEEE-RBTS shows the effectiveness of the pair-copula function based reliability and economic assessment method.

Presence of large number of single-phase, customer-owned, distributed energy resources that are installed randomly in any phase of Low Voltage (LV) distribution feeders, may lead the generation, in a particular phase, to exceed its load demand. This may result in reverse power flow in that phase towards the upstream network while in the other phases, power flows from the upstream network to the LV feeder. To avoid such problems, this paper proposes the use of Distribution Static Compensators (DSTATCOM) to circulate the reverse flowing power from one phase to the other phases. In this paper, the installation of DSTATCOMs is considered in the medium voltage feeders. The DSTATCOM can be connected in either wye or delta, both of these connections are explored here. Different control strategies are developed for each connection. The main objective of the DSTATCOM is to provide a path for the power, to circulate among the phases, through its DC link. The DSTATCOM controller is further developed to balance its upstream powers and to supply the load reactive power demand. The proposed configurations and the developed control methods for the DSTATCOM are numerically validated through extensive computer simulation studies in PSCAD/EMTDC.

This paper deals with the efficiency of a coordinated system of surge protective devices (SPD), which is indicated by the IEC standard 62305 as typical protection measure for electrical and electronic apparatus against surges due to lightning. For practical applications, the probability of a given SPD system to reduce the risk of failure of apparatus is a key point for its proper selection and installation. The paper aims to give the rationale for the evaluation of such probability and shows application examples of different types of SPD systems in the case of direct lightning stroke to the structure (source of damage S1).

Distributed generation (DG) has an overall positive impact on Microgrids. These DGs are usually located close to the load centers which lead to some benefits such as; system power loss and energy cost reduction; voltage profile and stability improvement; environmental friendliness, postponement system upgrading and reliability enhancement. In this paper, a novel combined method based on Genetic Algorithm (GA) and Intelligent Water Drops (IWD) is proposed to find location and capacity of DG in Microgrids for optimizing some objective functions. The objectives are minimizing network power losses, improving voltage regulation and increasing the voltage stability within the framework of system operation and security constraints in Microgrids. In this paper, DG units are modeled as generators that are able to inject just active power to network. The Intelligent Water Drops (IWD) algorithm is a new swarm-based optimization algorithm inspired by observing natural water drops that flow in rivers. A detailed performance analysis is carried out on 69-bus and 33-bus Microgrids to demonstrate the effectiveness of the proposed methodology.

The aim of this paper is to minimize the total cost of the system by incorporating wind power and plug-in-electric vehicles (PEVs) along with demand response (DR) program. The methodologies have proposed in contrast with the conventional algorithm in which the transmission line investment cost has been minimized without considering the dynamism of the deregulated environment. Moreover, the transmission network planning enhances the competitiveness of the power market, where more market players can participate. In this situation, the network planner has an important role in assessing the needs for transmission investments. Now-a-days practice of the network planner is to utilize more renewable power resources, PEVs and implementation of different electricity price tariffs. To achieve more benefits of PEVs and wind energy, their optimal utilization is a major concern. This paper proposes a mathematical model for solving the combined effect of PEVs and wind power integration with incentive-based DR program on static transmission network expansion planning (STNEP) problem. To solve this non-linear and non-convex problem, a nature-inspired optimization algorithm named gbest-guided artificial bee colony algorithm (GABC) is applied due to its robustness. The algorithm’s performance is evaluated through modified IEEE 24-bus, Brazilian 46-bus and Colombian 93-bus system. The test results indicate that the combined effect of DR, PEVs and wind has reduced the total system cost significantly.

Electric power systems are complex and commonly run near their operational limits. Power systems are basically designed based on the ( N − 1) criterion. In these systems, total or partial blackouts are unavoidable. Cascading failures following an initial event is recognized as the main mechanism for power system blackouts. Undesirable activation of zone 3 of distance relays due to their local function has been identified as one of the major causes for propagation of cascading failures. In this paper, in order to mitigate the risk of power system blackouts, a novel approach is proposed for recognizing the critical line outages with the highest contribution in cascading failure and preventing their undesirable outage by blocking zone 3 of their distance relay. In this paper, based on the statistical activation of distance relays, a deterministic–probabilistic approach is developed for identifying the critical lines with the highest contribution in blackouts due to activation of zone 3 of their distance relays. In order to avoid interference of relay blocking with the main protection duty of distance relays, the proposed approach recognizes the minimum critical lines with the highest contribution in cascading failure for blocking zone 3 of their distance relays. The proposed approach is demonstrated on the New England 39-bus system and detailed simulation studies carried out to examine the validity and effectiveness of the proposed approach.

Due to nonlinear and discrete variables and constraints, optimal reactive power dispatch (ORPD) is a complex optimization problem in power systems. In this paper, the purpose is to solve multi objective ORPD (MO-ORPD) problem considering bus voltage limits, the limits of branches power flow, generators voltages, transformers tap changers and the amount of compensation on weak buses. The objectives of this paper are real power losses and voltage deviations from their corresponding nominal values, which are conflicting objectives. Because of the stochastic behavior of loads, the MO-ORPD problem requires a probabilistic approach. Hence, in this paper, a two-point estimate method (TPEM) is proposed to model the load uncertainty in MO-ORPD problem. Moreover, the proposed method is compared with some other methods such as deterministic approaches and Monte Carlo simulations (MCS). The obtained results approve the efficiency of the proposed methodology. The proposed models are implemented and solved using GAMS optimization package and verified using IEEE 14-bus and IEEE 30-bus standard test systems.

This paper proposes a simple, passive, voltage-balancing scheme for induction generators directly interfaced with single-phase utility grids. The proposed scheme employs two capacitors for balancing the stator voltage and is insensitive to the machine’s slip. The paper presents the mathematical analysis and an algorithm for the calculation of the two capacitances. Further, the effectiveness of the proposed scheme is demonstrated through the simulation studies in the PSCAD/EMTDC software environment.

Feeder incident information is quite useful for evaluating the quality of the electricity distribution system. The improving scheme can be taken based on this information as well. In this paper, an adequate way for gathering this information was developed and the related messages from SCADA historical event log were analyzed by a novel methodology. For correctly and rapidly analyzing the collected messages purpose, this paper developed a time-driven and event-driven approach in order to express the exact feeder incident affairs. The feeder fault information can be fetched precisely and efficiently according to the result of this paper. Furthermore, the outage duration of the fault feeder, excluding the load transferring condition, was computed as well. For the sake of cyber security purpose, this paper developed a low cost and secured file transfer mechanism for transferring the event log from the SCADA system to an intranet web server. Corresponding to the web-based application software based on the result of this paper was consequently developed and installed on the sever of information management department of Taiwan Power Company (Taipower) for all SCADA control centers, and the software is running successfully.

In recent years, Smart Grid technologies such as Advanced Metering, Pervasive Control, Automation and Distribution Management have created numerous control and optimization opportunities and challenges for smart distribution networks. Availability of Co-Gen loads and/or Electric Vehicles (EVs) enable these technologies to inject reactive power into the grid by changing their inverter’s operating mode without considerable impact on their active power operation. This feature has created considerable opportunity for distribution network planners to explore if EVs could be used in the distribution network as reliable VAR suppliers. It may be possible for network operators to employ some EVs as VAR suppliers for future distribution grids. This paper proposes an innovative Smart Grid-based Volt-VAR Optimization (VVO) engine, capable of minimizing system power loss cost as well as the operating cost of switched Capacitor Banks, while optimizing the system voltage using an improved Genetic Algorithm (GA) with two levels of mutation and two levels of crossover. The paper studies the impact of EVs with different charging and penetration levels on VVO in different operating scenarios. Furthermore, the paper demonstrates how a typical VVO engine could benefit from V2G’s reactive power support. In order to assess V2G impacts on VVO and test the applicability of the proposed VVO, revised IEEE-123 Node Test Feeder in presence of various load types is used as case study.

The purpose of this work is informing the scientific community and vendors of a certain type of instrument transducers for protection and control applications in industrial electric installations. Such transducers can increase the accuracy and decrease the size of the measuring system for all service conditions at any industrial facilities. The work contains circuit diagrams of negative sequence current transducers offered by the author and obtaining primary currents from Rogowski coils. The statistical data based on the field tests of the discussed equipment is also presented in the paper. The algorithm for calculation of parameter values for negative sequence current transducers is discussed. The paper may be of interest for investigators and engineers engaged in research, design and commissioning of protection and control equipment, current instrument and measurement devices used in industrial applications, and also for undergraduate and postgraduate students in electrical engineering.

This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people’s living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be risk averse. In this paper, mathematical models are developed to incorporate the risk aversion into the generation expansion planning problems. We use the conditional-value-at-risk and maximum regret as risk measures and the results shows that the investment plans are affected when the risk is considered.

This paper introduces an approach based on stochastic data envelopment analysis (SDEA) for performance assessment of electricity distribution units. A new approach is applied for assessment of Iranian distribution units from 2001 to 2011 in this paper. There are usually incomplete and stochastic data or lack of data with respect to electricity distribution companies. Due to lack of information about some parameters, theory of probability is imported to the model. Different Iranian distribution units are considered as decision making units (DMUs). Network length, transport capacity and the number of employees are chosen as inputs while number of customers and total electricity sales are chosen as stochastic outputs. Then, the best electricity distributions units are selected with respect to efficiency scores in stochastic environment. Also, SDEA model is performed for each input, separately to identify the most important input indicators by comparing the results of associated efficiencies with SDEA model. The empirical results show that network length is the most important and influential input factor in this particular case study. To the best of our knowledge this is the first paper that examines stochastic outputs for assessment of electricity distribution units by SDEA in Iran.

Power grids are vulnerable to cascading failures, as shown by previous blackouts or major system disturbances. Line outages due to overload are often the main contributors to the cascading failures leading to these undesired situations. Indeed, the more a line is overloaded, the larger is its sagging, and hence the probability that it will be tripped. It is necessary to quantify in a realistic way the probability of trip as a function of the load in order to compute a good estimation of the frequency of dangerous cascading outages. Several models were proposed for this purpose, but none of them is backed up by empirical evidence or detailed analysis. This paper studies factors that could affect the probability of trip as a function of load, and it computes this probability for two different test systems using a temperature simulation based methodology, called dynamic PRA level-I analysis. This paper then compares existing modelings of this probability to these results. This comparison shows that all modelings used in the literature are not always convenient. We finally propose a simple model that can be adopted in probabilistic risk assessment of cascading failures.

Frequency Response Analysis is a well-known technique for the diagnosis of power transformers. Currently, this technique is under research for its application in rotary electrical machines. This paper presents significant results on the application of Frequency Response Analysis to fault detection in field winding of synchronous machines with static excitation. First, the influence of the rotor position on the frequency response is evaluated. Secondly, some relevant test results are shown regarding ground fault and inter-turn fault detection in field windings at standstill condition. The influence of the fault resistance value is also taken into account. This paper also studies the applicability of Frequency Response Analysis in fault detection in field windings while rotating. This represents an important feature because some defects only appear with the machine rated speed. Several laboratory test results show the applicability of this fault detection technique in field windings at full speed with no excitation current.

This paper investigates the role of integration of distributed storage with high penetration of variable renewable sources in power systems. The paper analyzes the impact of such integrations on the security, emission reduction, and the economic operation of electric power systems. The paper also identifies strategies for a larger penetration of variable generation resources without compromising the power system security. Mixed integer linear programing (MILP) is applied for the optimization of the day-ahead hourly security-constrained unit commitment. The assimilation of EVs (both as a provider and a utilizer of energy), renewable energy sources, and smart grid is regarded as a novel, low-cost, and low-emission solution to the existing challenges of electric power systems including the means of storing large quantities of energy considering variable renewable energy sources and large carbon footprints of conventional thermal units. Numerical studies are conducted in this paper to showcase the potential impacts of EV fleets as battery storage for peak load shaving, minimizing power grid operation costs and hourly wind curtailments, and optimizing the environmental impacts based on hourly commitment and dispatch of thermal generating units.

This paper presents a model for maintenance scheduling (MS) of generators using combined simulated annealing and binary particle swarm optimization (CSABPSO) based stochastic approach. The objective function of this paper is to reduce the loss of load probability (LOLP) for a power system. The hybrid algorithm combines BPSO with simulated annealing behavior. The CSABPSO algorithm takes both of the advantages, good solution quality of SA and fast searching ability of BPSO. As stochastic optimization algorithms are sensitive to their parameters, proper weight update procedure for parameters selection is introduced in this paper to improve solution quality. Weight update operators are introduced in the BPSO in order to obtain the diversified solutions in the search space. In this paper the impacts of transmission constrained MS is considered. Moreover, the CSABPSO based economic dispatch (ED) and load flow have been decomposed as a sub-problem in the maintenance model that results to a more practical transmission constrained maintenance schedule. A case study for IEEE reliability test system (RTS) is used for detailed analysis and further results are presented for roy billinton test system (RBTS) which shows the proposed algorithm can accomplish a significant levelization in the reliability indices over the planning horizon and demonstrates the usefulness of the proposed approach. The simulation results obtained by proposed algorithm indicate transmission line constraint influence on establishment of optimal MS. The CSABPSO could have higher efficiency, better quality than the other compared algorithms.

Microgrids comprising multiple distributed resources are being increasingly considered for integration into electricity networks. Considering the multiplicity of the distributed resources in a single location and distributed nature of such single entities, it is impractical to represent them as detailed models in power system simulations. Hence, it will be attractive for electricity utilities to employ simplified models of microgrids in dynamic studies. This paper proposes a method for representing grid-tied microgrids as simplified generator or load units in such studies. For this purpose, the paper takes an approach in investigating the applicability of modal analysis as a tool for model equivalencing of grid-tied microgrids with inverter and non-inverter interfaced distributed generators. Validity of the reduced order dynamic equivalents is tested under different operating conditions: power export and import modes, with different load types and fault conditions. Scalability of the model equivalencing approach is demonstrated using a case study developed based on the IEEE 13-Bus test feeder. Furthermore, the model equivalencing is applied on microgrids in a multi-microgrid environment to validate the methodology. The dynamic model equivalent of the microgrid can be represented as a current source at the point of common coupling while retaining all imperative dynamic characteristics. The proposed methodology is also applicable to distribution network clusters comprising distributed generators.

This paper presents the application of well known recursive least square (RLS) harmonic estimation technique and its elimination with improved current control technique based shunt active power filter (SAPF) in a distorted power network. The estimation of amplitude and phase angle of fundamental and harmonics is performed using RLS algorithm, known for their simplicity of computation, accuracy and good convergence properties. The estimates are updated recursively as samples of the harmonic signals are received. In order to eliminate harmonics produced by the nonlinear load connected in the distribution network, a three-phase SAPF with modified current control technique is employed. In this paper, based on the analysis and modeling of SAPF with closed-loop control, a feed forward compensation path of load current and a new pulse width modulation (PWM) control scheme is proposed to improve the dynamic performance of the SAPF. In this case the amplitude and phase angle of the converter AC voltage should be adjusted using PWM, thus producing either leading or lagging reactive power. Harmonic contented in the signal is estimated at the point of common coupling (PCC) with and without SAPF. The comparative results of amplitude and phase angle of fundamental and selected harmonics are determined considering installation of SAPF in the distribution network. The system is studied using MATLAB environment to justify the effectiveness of proposed control technique in comparison to the other techniques discussed in the recent literature.

This paper describes an approach using an adaptive neuro-fuzzy inference system (ANFIS) for the assessment of online critical clearing time (CCT). The ANFIS can integrate neural networks and fuzzy logic principles, and has a potential to combine the advantages of both in a single framework. In this paper, the ANFIS is applied for the prediction of CCT by varying load levels and fault locations in buses and transmission lines. The IEEE 39-bus system and 9-bus western system coordinating council are tested and implemented in this study. All machines of the IEEE 39-bus system are considered as the classical model without considering any generator’s exciters. While three machines in the 9-bus western system coordinating council are considered as detailed models, forth-order differential equation is described for all machines by considering the excitation system controller. CCT values obtained by the time domain simulation method using step-by-step calculation are used as the benchmark. The power world version 17 is used for transient simulation, and the ANFIS is implemented using MATLAB version 2014B. The results obtained from the ANFIS approach are quite satisfied with high accurate solutions and much lower computation time. Finally, the graphical user interface in MATLAB is applied for the online CCT estimation of two test power systems by using appropriate ANFIS models obtained from simulations.

Energy needs increases day by day in those areas of the world where the electrical distribution lines are not available. This situation limits the industrial and economic development of these areas as well as the establishment of the population, so that it facilitates the exodus and the uprooting of people. At the moment the electrical energy supply in remote areas is based on solutions with generator sets, consuming great amounts of fuel with a great environmental damage. The technological development of renewable energies and the new concepts for their management, make possible proposing off-grid generation solutions for providing great amount of energy with high quality and reliability. Along this paper, a smart-grid configuration is proposed which is developed with products of proved reliability and which uses renewable energies as main generation source. This configuration allows having “standard” grid services anywhere, without the need of connection to the traditional grid. Environmental, economic and operation benefits of using these technologies against traditional solutions are also presented in this paper. This proposed solution allows the economical development and exploitation of areas where due to the lack of energy or to the energy cost it has not been possible until now.

Purpose In recent years, most organizations have been dealing with many economic, environmental and social problems. Iran’s Electricity Distribution Network (EDN) with different supply stages involving generation, transmission, and distribution is a good case of a complex system engaging in sustainable activities; they must incorporate environmental and social concerns into traditional economic objectives. Assessing the sustainability of EDNs is complicate because it involves a variety of inputs, outputs and inter-related inputs/outputs at any stage of the network for which the importance of each stage may vary. Methodology This paper proposes a new network data envelopment analysis (NDEA) model for assessing the sustainability of EDNs and their components. The proposed method has the following characteristics: All generation, transmission, and distribution stages, as well as the overall performance of the network, are evaluated in a unified framework; Undesirable outputs, re-work, and external inputs are considered in the model; Different weights for stages, determined by decision-makers, have been implemented to cause different effects on the network performance; The strengths and weaknesses of EDNs’ components are identified; The effect of each dimension of sustainability on the performance of EDNs’ components is investigated. Finding The result of this study indicates that the Gharb EDN with an efficiency score of 0.8487 has the best performance and Mazandaran EDN with an efficiency score of 0.4667 has the worst performance. Based on the results, the paper proposes how to reduce inefficiencies in each stage of the network.

This paper proposes a comprehensive framework for generation and transmission planning of renewable dominated power systems, which is formulated as a stochastic multiobjective problem. In this regard, a Normalized Normal Constraint (NNC) solution approach is proposed to solve the introduced stochastic multiobjective generation and transmission planning (GTP) problem. The NNC is utilized in this paper as a relation between different objective functions with different dimensions to find the optimal weighting factors of these objectives. The NNC is applied for solving the GTP problem with objective functions including the investment and operation costs along with the transmission losses, while considering the cost of unserved energy, as well as the uncertainty of load and Renewable Energy Resources (RERs). A fuzzy-based decision making framework is utilized to select the best solution among the optimal non-dominated solution points. A scenario-based approach is used to model the uncertainties. The Garver 6-bus and IEEE 118-bus test systems are utilized to perform the numerical analysis. The simulation results validate the performance and importance of the proposed model, as well as the effectiveness of the NNC to find the evenly distributed Pareto solutions of the multiobjective problems.

The decentralised infrastructure of the Danish thermal and electricity infrastructure has improved security, efficiency and reliability in energy transmission and consumption in each of the systems. To further improve this trend, this paper investigates the concept of decentralised coupling of electrified thermal and transportation system in low voltage residential network to identify their operational flexibility. In this paper, diagnosis based on actual data from the energy distributors and surveys is used to understand and improve the flexibility of an integrated energy system. The main contribution is a set up model with an autonomous control system that can assess the potential flexibility from thermal units (eg heat pumps and storages) and electric vehicles (EV) charging systems, in the low voltage distribution network as a multi-energy system. Each thermal system and EV charging has its respective individual controller. The proposed control technique manages to successfully operate and control the thermal units and EVs charging system within the recommended operating limits of grid voltage, and by sharing flexibility within the specific network integrated with multi-carrier energy systems. It has the capability of sensing local key control parameters like node voltage, state of charge of EV, temperature and level of hot water in the storage tank. These control parameters allow scheduling, re-scheduling, and decision making on the operation of individual thermal and EV charging-unit with operational priorities. This enhances the sharing of flexibility for proper coordination, control, and management of thermal and EV charging systems in low voltage (LV) distribution networks with mutual technical benefits. From the results of the steady-state analysis of power system, the application of the proposed control architecture is found to be effective to manage grid congestions and local voltage control, satisfying the thermal energy requirements of the customer as well as charging needs of EV.

The paper looks through the fault location algorithm of multi-terminal direct-current (MTDC) hybrid transmission systems based on line-commutated converter (LCC) and modular multi-level converter (MMC). Generally, it has two issues which required to be addressed: (1) the travelling wave (TW) fault location algorithm suitable for the multi-terminal transmission system; and (2) the method of acquiring or processing the TW signal. In this paper, a novel TW fault location algorithm suitable for the LCC-MMC-HVDC hybrid transmission system is researched based on the Hilbert-Huang transform (HHT). Firstly, the TW propagation process characteristic of hybrid LCC-MMC-MTDC transmission system is studied. Secondly, a novel TW fault location algorithm based on HHT is proposed. Eventually, a typical ± 400 kV LCC-MMC-MTDC hybrid transmission system is established via PSCAD/EMTDC software for the case study to investigate the accuracy of the proposed algorithm. Afterwards, its robustness against fault location issue, fault resistance issue and fault type issue is also confirmed.

By applying stepwise inertial control (SIC) on wind turbines (WTs), a secure system frequency response after large active power imbalances in the system can be achieved. In Part I of this paper (Ding et al., submitted for publication), a novel approach for determining when to terminate the SIC is presented. In this context, a new analytical expression for a fixed termination time (FTT) is derived. In order to optimally implement the FTT concept, both the parameters of the system frequency response (SFR) model and the incremental power during the SIC process must be known. This paper is providing answers to these questions and furthermore proposes an advanced application strategy for the FTT concept. The new strategy improves the frequency nadirs and prevents the WTs’ rotor speed from violating the lower permissible limit during the SIC process. Using the least squares algorithm, the unknown SFR model parameters are estimated from the frequency measured at the point of common coupling (PCC) of the wind farm. The incremental active power is determined considering the effect of the incremental power on the frequency nadirs and the releasable kinetic energy of the WTs. The performance of the proposed new application strategy is verified using a modified IEEE 39-bus test system.

In this paper, a comprehensive method is proposed to synergistically optimize the configuration and operation strategy of combined cooling, heating and power (CCHP) systems, considering configuration and strategy interact with each other. The mathematical model is established based on the energy flow and the energy balance relationship of CCHP system and traditional separate (SP) system with multi-objective evaluation criterion. The optimization based on an industrial park in Shanxi is carried out to find the optimal configuration and corresponding strategy. The results show that the optimized CCHP system outperforms the SP system in cost saving, energy consumption saving and CO2 emission reduction with the saving ratio of 17.37%, 33.72% and 55.76% respectively throughout the year. An analysis of the factors that affect the performance of CCHP systems is adopted in terms of: (1) price of electricity and gas; (2) the ratio of thermal load to waste heat; and (3) load rate of gas turbine. This paper may provide some new ideas for the optimization and performance improvement of CCHP systems.

Standalone dc microgrid faces a significant reliability risk due to continuous variation in power from renewable energy generation and the load demand. Usually, the output power from the renewable generators fluctuates with the weather conditions. The load is also varying all the time. This leads to a continuous risk of power mismatch in the system. Thus, a complementary generation or a storage system is required for maintaining the power balance in the system. This paper introduces a supervisory power management strategy (PMS) for a standalone dc microgrid with multiple distributed generations, load, and a battery energy storage system. The PMS is designed based on the model predictive control (MPC) approach. The complete mathematical model of the system has been developed, and it has been utilized in the MPC controller to solve an optimization problem with operating constraints. A forecasting technique is also incorporated in the proposed MPC to predict the environmental and load demand parameters. Simulation results illustrate the effectiveness of the presented MPC-based power management approach. Accordingly, the proposed approach effectively manages the power among the generators, load, and the battery and stabilizes the dc voltage. The paper also evaluates the effects of various prediction methods on the controller performance.

Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability.

This paper discusses the optimal distribution system operation in the presence of wind power by coordinating network reconfiguration and demand response method. Under the specific demand response program, the paper proposes an optimal control method of coordinating thermostatically controlled load (TCL) and battery energy storage (BES). The TCL of the demand response can be controlled in the premise of not hurting customer comfort. The risk of exceeding thermal customer comfort limit is measured by conditional value-at-risk (CVaR) index. Under the requirement of timely wind power balancing, the hourly reconfiguration plan is adopted. Because of the stochastic characteristics of wind power, this is a risk-constrained optimization problem with the objective of minimizing operation cost. Due to the time interdependence of wind power, a Markov Decision Process (MDP) formulation in combination with dynamic programming is adopted to solve the multi-stage stochastic optimization problem. The results show that coordinating reconfiguration and demand response method could significantly contribute to compensating for the forecast error of wind power, therefore, bringing considerable economic savings on operation cost in real-time electricity market.

High penetration of renewable energy sources (RES) in distributed Microgrid (MG) systems provides significant economic and environmental benefits. Nevertheless, the intermittent nature of RESs is the greatest challenge in the efficient utilisation of these resources. Using Battery Energy Storage Systems (BESS) in MGs is proposed as an effective solution to mitigate the fluctuations of RESs power generation. However, BESSs are expensive components with a short lifetime and therefore, they should be optimally sized according to the characteristics and requirements of MGs. This paper proposes a BESS sizing approach to determine the capacity and power rating of the BESS in a Grid-Connected MG, taking economic and technical criteria as well as the uncertainty of dispatchable generators (DG) and RESs into consideration. The technical requirements include the degree of reliability, BESS degradation, and operating constraints of the DGs. On the other hand, the cost factors associated with the utility grid including peak cost, valley cost, and Time of Use tariff (TOU) are taken into account. In this paper, a multi-objective mixed-integer quadratic model is developed to include the aforementioned parameters in the BESS capacity optimisation algorithm. Inspecting the impact of the considered parameters on the optimal size of the BESS and total cost of the MG, four case scenarios are studied. The first two scenarios evaluate the effect of the BESS depreciation, whereas the third and fourth scenarios investigate the impact of grid volatility (GV) and reliability indices on the optimal solution. The obtained results from the case studies verify the effectiveness of the proposed BESS sizing method.

Model-based predictive control, or MPC, is a popular technique widely used in three-phase two-level power converters (VSC), in applications such as motor and generator control. One of the main drawbacks of implementing MPC is the high computation time requirements while evaluating the effects of the six available vectors on the cost function. The computing time becomes unacceptable when the number of vectors is very high, as in modular multilevel converters (MMC), making it impossible to run the MPC algorithm in microcontrollers (MCUs) within reasonable cycle times. This paper proposes a fast method capable of finding the reference voltage vector among a large number of available multilevel voltage vectors, in a single step, which greatly reduces the computation time and makes it possible to use MPC in regular MCUs. Unlike other MPCs, after calculating the reference vector, the proposed method discards the duration times obtained by the MPC and the reference vector is modulated using an SVM. MPC has been little developed for MMC and is normally intended to improve the internal operation of the converter. In contrast, this paper presents a fast MPC, designed to control the active and reactive powers exchanged by a grid-connected MMC, providing a fast dynamic response, low current THD and constant switching frequency. In addition, the implementation is compatible with other known MMC vector control algorithms and can even be used with other multilevel converters.

The paper presents the concept of adaptive control in electrical power systems, based on programmed trajectory motion of synchronous generators. The feasibility of the method is tested in a range of simulation experiments. The key feature of the technique is the use of a simple reference model which defines the dynamics of the controlled parameters. As a result, the voltage vector angle, velocity and acceleration are delivered to the exact, rather than approximate, target values in a predictable, coordinated, robust and efficient manner. Compared to other adaptive methods, such as model predictive control, the technique makes a more efficient use of computational resources, which makes it particularly beneficial if implemented at lower levels of control system hierarchy. It also shows a promising level of robustness against disturbances during the control process. We envisage that the most relevant practical applications are the stabilization and synchronization of small to medium size synchronous machines connected to distribution grid, and management (corrective control and resynchronization) of islanded sub-systems, such as microgrids. Simulations also indicate relatively short control time and improved stability against perturbations. With a proper choice of reference model, the need for bi-polar control action does not arise and the target values are achieved by uni-polar action only. Both the stabilization and the synchronization tasks are accomplished by means of one control algorithm, which improves the quality of control, especially in post-emergency operating conditions. The time-domain modeling results reported in the paper were obtained from software-based simulators.

This and the companion paper present key methodological and modelling aspects, as well as key findings and conclusions from the large-scale technical study into long-term development of future electricity distribution networks in Great Britain (GB) undertaken on behalf of all distribution utilities in GB. The objective is to apply traditional and smart solutions for development of diverse distribution networks with increased penetration of low carbon technologies (LCTs) and to assess their impact on the entire GB transmission system. This paper presents the applied methodological framework through system planning methods and principles, key features of the whole suite of undertaken steady-state and dynamic studies, and describes traditional and smart solutions for network development. A brief description of forecast energy scenarios and projections of LCT uptakes are then given in the companion paper. Results of the considered studies are presented for four large-scale real-life distribution networks covering all voltage levels and the integrated GB transmission-distribution system. These results are the basis for generalized conclusions, which give the answers to the key issues raised by the GB industry at the project initiation.

A medium voltage (MV) faulted section location technique depending solely on unsynchronized low voltage (LV) measurements in distribution systems is introduced in this paper. The proposed method identifies the faulted MV feeder segment when an unsymmetrical MV fault occurs. It exploits parameters including voltage magnitude, angle and sequence components captured via distributed non-synchronized monitoring devices connected at secondary substations. In this study, the characterization of a system’s LV profile during MV faults was achieved throughout both software simulations and physical testing. The latter was conducted in the 11 kV and LV distribution network of the Power Networks Demonstration Centre (PNDC) of the University of Strathclyde. The tests were performed for both 11 kV radial and ring network configurations. Modelling and simulations implemented using the DigSILENT PowerFactory package, complemented the hardware level testing and provided the opportunity for further examinations, such as the impact of MV laterals connection, distributed energy resources on both MV and LV side as well as the presence of unbalanced loads. Finally, the paper evaluates the effectiveness of the proposed faulted section location technique under various physical and simulated fault scenarios, loss of communications and noise interference.

The paper presents a new approach for earth fault localization which is based on evaluation of phase to ground voltages recorded by voltage monitors installed at low-voltage side of distribution transformer station deployed under smart metering projects. The introduced method “Vdip” determines the probability of asymmetrical fault location based on comparison of the changes in negative sequence current recorded at the feeding medium voltage substation and changes in negative sequence voltages recorded at the LV sides of distribution transformers. The paper describes the nature of the method and presents its principle using simulation of a MV resonant earthed distribution network where short-term connection of an auxiliary resistor is used. The method was also evaluated in real resonant earthed 22 kV network, where totally 15 earth faults with fault resistance up to 1.2 kΩ were carried out. As the result of this field test, the location error of the Vdip method is presented.

This paper proposes a novel energy management system (EMS) for an isolated structure of networked microgrids (NMGs). The interconnected microgrids consist of the cyber-physical connections for information and power exchanges. A bi-level EMS is presented in which the outer-level EMS is aimed to exchange the required information and power between the interconnected microgrids, and the inner-level EMS is intended for energy scheduling of each on-fault microgrid in case of separation from other microgrids. This paper focuses on the operation of interconnected microgrids. A step-wise demand response program (DRP) is also considered in the energy management to attain the cost-effective operation. Furthermore, a new pricing model based on microgrid marginal pricing (MGMP) is introduced for the power exchanges between the interconnected microgrids. To cope with the uncertainties of the renewable energy sources and loads, some scenarios are generated using the scenario-based analysis. Also, a backward scenario reduction method is used to reduce the number of the scenarios. Besides, a mixed integer linear programming (MILP) is applied to the stochastic optimization problem of the NMGs. The proposed model is implemented on a test system with five NMGs. The simulation is run over a 24-hour scheduling time horizon. Both cases without and with demand response program (DRP) are compared in the numerical results. The results of the simulation demonstrate that using the proposed DRP in the energy management increases the performance of the generation units and decreases the total operational cost of the proposed NMGs. Also, the voltages of the buses converge to their rated values.

Microgrids are emerging as an alternative mode of operation for distribution systems integrated with Distributed Energy Resources (DERs). With appropriate management and control of the DERs, a section of a distribution system can operate isolated from the main grid thereby enhancing the reliability and security of supply to consumers. However, the integration of DERs has raised many technical challenges including protection. The traditional distribution system protection cannot provide reliable protection to the microgrid in the isolated mode due to the limited short-circuit capacities of the converter-interfaced DERs. This paper proposes the application of a new voltage-based relay type for the protection of microgrids. The relay algorithm achieves its protection function through active power differential and sensitivity calculations based on voltage measurements within a specified protection zone. In the paper, the new relay type is modelled in Digsilent PowerFactory software and installed at the nodes of a microgrid test system. The performance of the relay type is investigated under variety of faults. The relay is shown to operate correctly and effectively to detect and identify faults in both radial and meshed microgrids integrated with inverter-interfaced DER technologies.

In order to maximize the utility of renewable energy resources, long-distance power transmission lines are essentially required. To accomplish this purpose, the voltage-source-converter (VSC) based high voltage direct current (HVDC) transmission is considered an attractive option. However, due to DC-link capacitors and their discharge currents, the VSC-HVDC based transmission networks are more vulnerable to short circuit faults. The direct current circuit-breakers (DCCBs) are considered a reliable option to protect the transmission line against short circuit faults. The DCCBs with increased voltage rating and fault-current interruption capability are still considered a gigantic problem. The capacity issues of DCCBs can be alleviated using some external circuits to reduce the intensity of fault-current. This paper introduces an external fault-current limiting circuit (FCLC), which is non-superconducting in nature, and it consists of power electronics-based bidirectional switches, current limiting inductor, and power dissipating resistor. This circuit is placed in series with a DCCB, to escalate the response time in the advent of fault, to restrict the maximum value of fault-current, and to reduce the stresses on energy absorption components in DCCB. The circuit is activated only when fault-current limitation operation is required, thereby, the proposed FCLC has zero power-loss in the nonoperational state, and has no influence on the steady-state performance of the system. Furthermore, regarding FCLC, the detailed working principle, parametric analysis, and rigorous evaluation of performance are accomplished in this paper. The theoretical concepts are validated using a three-terminal VSC-HVDC model and equivalent circuit analysis, in PSCAD/EMTDC simulation-based environment. The results of FCLC are compared with other solutions in the literature. The comparison of results concludes that the proposed FCLC own better characteristics, in terms of control features, fault clearing time, and power losses.

Considering the development trends of renewable energy technologies, it is easy to understand why the future direction of the development for the power system will require a significant change in an approach to system planning and modeling. This is particularly the case with a high amount of inverter based distributed energy resources that can introduce non-linearity and higher fault current contribution, especially during the transients. In that regard, it is important to develop a new and a more precise model of the inverter based distributed energy resources, focusing on the initial fault response of the inverter. The most important factors, influencing the initial inverter response to the grid faults are investigated within the paper. Based on the experimental verification of these factors on the advanced laboratory prototype for testing the grid integrated renewable energy sources, this paper proposes a novel and accurate model of the inverter based distributed energy resources under grid faults.

This paper deals with the coordinated control of DFIG wind turbine system and microturbine in a DC microgrid system feeding constant power load (CPL). The DFIG stator and rotor are connected to the DC grid through diode rectifier, buck converter, and frequency converter, respectively. The DFIG wind system depending on the load demand and wind speed operates in the power control mode or load following mode. In the power control mode, the DFIG wind system injects the available wind power to the grid and microturbine sets the DC bus voltage to its reference value. In the load following mode, the DFIG wind system regulates the DC bus voltage to a constant value, and the power injected by the microturbine decreases to a negligible value. Studies show that in the load following mode and under high penetration of CPLs, the study system may become unstable. Hence, this paper, first, develops control structures for the DFIG wind system in the DC microgrid at both operation modes, and then control structure of the DFIG wind system is modified to efficiently stabilize the system under high CPL penetration. Next, performance and stability of the system are examined analytically and by time domain simulations.

The penetration of high-level wind power has significantly made the power system's operation complicated. The random power variation of the wind farms may deteriorate the power system's transient stability degree since it alters the operating state of the power system. In this paper, based on trajectory sensitivity and Extended Equal Area Criterion (EEAC) method, a new preventive control approach is proposed to optimally balance the wind power variation by rescheduling synchronous generators while maintaining the transient stability for credible contingencies. The whole problem is formulated to a programming problem with linear stabilization constraints. The proposed method is validated on the New-England 10-machine 39-bus system by using commercial simulation software Transient Security Assessment Tool (TSAT), and both single- and multiple-contingency cases are tested. Simulation results verify its satisfactory performance on control effectiveness, computational efficiency, transparency, and accuracy. Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) The work in this paper was supported in part by Ministry of Education (MOE), Republic of Singapore, under grant AcRF TIER 1 2019-T1-001-069 (RG75/19), and in part by National Research Foundation (NRF) of Singapore under project NRF2018-SR2001-018. Y. Xu’s work is supported by Nanyang Assistant Professorship from Nanyang Technological University, Singapore.

In this paper, we study an important variant of integrated unit commitment problem and gas network in which uncertain renewable energy resources, gas and electricity storage, the capability of line-pack of the gas network (gas stored in the pipeline), and Power to Gas (PtG) are taken into account. The motivation of this paper is to enhance the security of power generation and optimize both electrical and gas network operational cost. Uncertainty of renewable sources in a power system will inevitably increase the power system’s dependence on traditional gas power plants. As a result, the uncertainty of renewable sources is transferred to the gas network such that the fluctuations of the gas flow would increase. Gas and electricity storage, the capability of line-pack of gas network and the use of PtG technologies help us to manage the effect of renewable sources on electricity and gas network. Here, we formulate a mixed integer non-linear optimization model to present the integrated unit commitment problem. Given the complexity of the underlying problem, we explore the problem structure and propose a novel reformulation consisting of efficient decomposition and convexification techniques. Compared to existing methods whose quality are sensitive to initial solutions, the proposed model is more flexible and offers significant improvements in solution quality and efficiency. The proposed model is tested on a modified IEEE 24-Bus test system and Belgian 20-node gas system.