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The paper proposes a technique for the on-line estimation of Thevenin equivalent (TE) which only needs the present phasor measurements. The technique is based on the wide-area measurements including voltage and current phasors of the system loads and synchronous generators, so that it can simultaneously estimate TE of the system seen from the interested buses. The technique has two main steps. In the first step, the conventional impedance matrix $\bar Z_{\rm bus}$ is modified to be suitable for TE estimation. In the second step, a correction coefficient based on the sensitivity theory calculated by using two consecutive phasor measurements is applied to correct the diagonal terms of the $\bar Z_{\rm bus}$ matrix. Simulation results carried on the IEEE 39-bus and 118-bus test systems show that the proposed technique can accurately estimate the TE for both generation and consumption buses under any load-increase scenario. The comparison scenarios verify the superiority of the proposed technique over others.

Prolonged voltage level reduction caused by the fault induced delayed voltage recovery (FIDVR) event may lead to a decrease in distance relays security. Therefore, some distance relays are prone to mal-operation under severely prolonged depressed-voltage conditions, and their security should be considered in the FIDVR event studies. The present paper investigates the possible operation of distance relay during the FIDVR event and proposes an auxiliary protection algorithm to effectively prevent its mal-operation during short-term dynamic voltage transient. The proposed algorithm estimates the critical time and voltage level at which the impedance trajectory arrives in Zone 3 of the critical relays using the rate of change of the impedance trajectory, relay margin index, and time-variant NERC/WECC severity indices. Then, the critical voltage is compared with the expected voltage level at the estimated critical time calculated by piecewise cubic spline interpolation (PCSI) method and three consecutive voltage phasors to decide about the block of relays which entering the impedance trajectory to their Zone 3 is probable during the FIDVR event. The efficacy of the proposed method is demonstrated by simulating some short-term voltage transient scenarios on the IEEE 39-bus test system

Demand response modelling have paved an important role in smart grid at a greater perspective. DR analysis exhibits the analysis of scheduling of appliances for an optimal strategy at the user’s side with an effective pricing scheme. In this proposed work, the entire model is done in three different steps. The first step develops strategy patterns for the users considering integration of renewable energy and effective demand response analysis is done. The second step in the process exhibits the learning process of the consumers using Robust Adversarial Reinforcement Learning for privacy process among the users. The third step develops optimal strategy plan for the users for maintaining privacy among the users. Considering the uncertainties of the user’s behavioral patterns, typical pricing schemes are involved with integration of renewable energy at the user’ side so that an optimal strategy is obtained. The optimal strategy for scheduling the appliances solving privacy issues and considering renewable energy at user’ side is done using Robust Adversarial Reinforcement learning and Gradient Based Nikaido-Isoda Function which gives an optimal accuracy. The results of the proposed work exhibit optimal strategy plan for the users developing proper learning paradigm. The effectiveness of the proposed work with mathematical modelling are validated using real time data and shows the demand response strategy plan with proper learning access model. The results obtained among the set of strategy develops 80 % of the patterns created with the learning paradigm moves with optimal DR scheduling patterns. This work embarks the best learning DR pattern created for the future set of consumers following the strategy so privacy among the users can be maintained effectively.

Transient behaviour of high‐voltage direct current transmission lines under direct current faults can be easily affected by many factors, namely, fault location, fault resistance and transmission line length. In order to design a suitable protective scheme, the impact of these factors should be thoroughly investigated. An impedance‐based analysis is more suitable in evaluating high‐voltage direct current system behaviour during direct current line faults, and consequently, in comparison to similar harmonic current or voltage‐based schemes, a characteristic harmonic impedance‐based protection is more capable in fault detection. Therefore, this paper presents a novel pilot protection method for line‐commutated converter based high‐voltage direct current transmission lines, which relies on continuous monitoring of characteristic harmonic impedances. The proposed method can accurately calculate location of faults along the line, and estimate additional valuable information, such as fault resistance. The validity of the proposed method is evaluated by a wide range of fault scenarios using the CIGRE high‐voltage direct current benchmark model, simulated in PSCAD/EMTDC and codes written in MATLAB software environments. It will be shown that the proposed protection method sounds promising, and can serve as an excellent backup option in the case of primary protection malfunction.

State of health (SOH) and remaining useful life (RUL) are two major key parameters which plays a major role in battery management system. In recent years, various machine learning approaches have been proposed to estimate SOH and RUL effectively for establishing the battery conditions. In the proposed work establishes an effective method to predict the battery aging process with accurate battery health estimation with real time simulations and hardware approach. This paper effectively exhibits a process to estimate SOH and RUL of a Li-Ion 18650 cell which are based on various factors like state of charge, discharge voltage transfers characteristics, internal resistance and capacity. To identify an optimal SOH and RUL machine learning based estimation approach, various battery’s statistical models are developed and implemented on a standalone hardware platform. The experimental results in this real time application shows that SOH is predicted by deep neural network approach which are found to be within the accepted error rate of ±5% and long short time memory neural network model estimates a battery’s RUL effectively with an accuracy of ±10 cycles. This approach exhibits various machine learning models in an realistic hardware platform which establishes optimal battery life.

In this paper, the significance of cross-tied link between the solar photovoltaic (PV) modules in an array during partial shading conditions (PSCs) is introduced. In order to conduct a detailed analysis, twenty numbers of 20W PV modules ( $4\times 5$ ) are arranged in a series-parallel (SP) configuration. The change in the pre-arranged SP configured PV array is implemented using a cross-link matrix switch between parallels based on shadow patterns. The switch matrix based modified PV array configuration is called Adaptive-cross-tied (A-CT) configuration. An embedded system based adaptive switch matrix (ASM) controller is developed to control the cross-linking connections between the PV modules under the PSCs to improve global maximum power. In addition, a performance analysis is carried out and compared all PV modules arranged in conventional SP and A-CT configurations. Moreover, realistic shadow test cases are under consideration to characterize current-voltage (I-V) and power-voltage (P-V) characteristics. The output power of the PV array decreases as well as the P-V curves show multiple power maxima points., such as the local maximum power point (LMPP) and the global maximum power point (GMPP). LMPP and GMPP locations, mismatch loss (ML), enhanced fill factor (FF), decreased power loss (PL) and performance ratio (PR) are indicators of performance during experimental and MATLAB/Simulink studies.

Frequency-based relays, commonly used for islanding detection of synchronous distributed generation (SDG), may either have large non-detection zones (NDZs) or wrongly operate for non-islanding disturbances unless they are efficiently adjusted. Trial and error simulation-based methods, employing application region (AR) and/or power imbalance AR (PIAR), are presented in the literature to adjust these relays for quick islanding detection without false trips. However, the associated settings are not optimal and finding them is time-consuming. In this study, an approach utilising particle swarm optimisation algorithm is proposed to adjust a rate of change of frequency (ROCOF) relay, one of the most effective relays in SDG islanding detection. The proposed approach needs a set of analytical formulas for determining the ROCOF relay performance curve and NDZ as well as AR and PIAR. These formulas are developed to be employed in the relay adjustment. By applying the developed analytical formulas to the optimisation-based approach, the ROCOF relay is adjusted fast and systematically. It is shown that while the performance of the relay adjusted by the proposed approach is close to the one with setting obtained by corresponding trial and error-based method, the latter is much more time-consuming than the former.

This paper proposes a novel, unknown input functional observer based optimal load frequency control approach for real-world complex nonlinear power systems. In the proposed control approach, the control signal applied to each power plant is directly estimated via the well-designed functional observer. The proposed functional dynamic estimator is able to handle parametric and nonparametric uncertainties, control loop and sensor faults, unknown inputs, and cyber-attacks. The observer for each power plant is decoupled from the other plants resulting in a more feasible implementation, reducing the complexity of the estimator and improving the reliability of the proposed control system. The applicability of the proposed method is shown on IEEE 39 bus-system divided into three control areas. The effectiveness of the proposed control scheme is verified by comparing results with well-known control schemes. Tolerance of the proposed technique to unknown inputs, uncertainties, and possible cyber-attacks is verified by several simulation scenarios.

High distributed generation (DG) penetration can lead to significant changes in the operation of high voltage transmission systems. In this paper, a methodology is proposed, which can optimally allocate synchronous DG (SDG) units to sub-transmission substations based on defining an SDG planning model for maximizing the profit of regional transmission system operators under the conditions existing in the Iranian system by taking into account their relevant costs and revenues. The constraints include the network and the DG capacity constraints. The formulated problem is executed by a heuristic approach comprising three main parts. The algorithm starts with determining the maximum DG capacity at each bus by short-circuit studies in order to satisfy short-circuit-level constraints. In the second part, the SDG planning problem is tackled by the Tabu search algorithm. The final stage is to investigate the constraints of protection blinding and false tripping for the solution of the second part. The proposed model, in different scenarios, was put to test in Isfahan Regional Electricity Company network in Iran. According to the results, significant profit related to the transmission and sub-transmission systems was achieved by the proposed model.

This paper aims at providing a novel techno-economic flexibility index to quantify the relative flexibility of different conventional generation technologies. The proposed measure takes into account a comprehensive set of technical flexibility characteristics of generation units including minimum stable generation level, operating range, minimum up/down times, and ramp up/down capability. The impact of various technical parameters on the flexibility restriction is determined based on the additional costs imposed to the system operator in order to satisfy that constraint. Afterward, the calculated flexibility index is incorporated into day-ahead market clearing procedure as a new objective function beside operation cost using a multiobjective decision-making approach. Simulation results show that the need of different flexibility levels changes the optimal generation dispatch and results in different operation costs. Furthermore, the impact of two emerging flexible options, i.e., bulk energy storages and a typical demand response program in the flexibility contribution of other generation technologies is also investigated. The results reveal that the integration of emerging flexible options frequently changes the flexibility share of conventional units and can provide the required flexibility level at a lower cost.

The ability of riding through the grid disturbances can increase the integration of microgrids into the distribution system. Consequently, a grid-connected microgrid should provide ancillary services such as low voltage ride-through (LVRT) capability and reactive power support to sustain the power system operations during abnormal grid conditions. The objective of this paper is to propose an LVRT scheme that improves the power quality of the entire microgrid. The developed method is implemented as the controller of the interface voltage-sourced converter (VSC) of a distributed energy resource and consists of primary and secondary control levels. The former includes the cascaded voltage and current control loops and the droop controller, while the latter controls the reactive power injection during the balanced/unbalanced voltage sags/swells. The proposed scheme is developed based on the independent control of each phase and does not require calculation of symmetrical components. Moreover, it can be employed in the VSC control systems with various reference frames and is effective for droop-based grid-connected microgrids with both single-phase and three-phase four-wire configurations. The proposed strategy is implemented using the hierarchical control system and preserves the plug and play capability. Several case studies are presented to verify the effectiveness of the proposed strategy.

The high penetration of renewable energy sources in modern power systems introduces opportunities and challenges to power system operators. The frequency, which is a global variable in power systems, is being affected due to the increase of the renewable energy shares. This paper suggests dynamic models of power systems for assessing the frequency response due to different types of disturbances and uncertainties from renewable energy sources. The introduced model is built based on the sub-transient model of synchronous generating units. Likewise, a simplified system frequency response model is presented, in which the demand-side participation in providing ancillary services is considered. Different types of power systems are considered to verify the introduced models. The results show the effectiveness of the presented models in evaluating the impact of different parameters on power system frequency response. The impacts of increasing the renewable energy shares and its uncertainties are also investigated.

In the event of a power system disturbance, it is important that the decision to implement under frequency load shedding is based on both the minimum frequency and the magnitude of the disturbance. In this paper, we propose the use of higher order polynomial curve fitting to estimate the minimum frequency. If the prediction shows that the minimum frequency threshold will be violated, the magnitude of the total disturbance is estimated using the swing equation. In addition, the minimum amount of load that must be shed to restore the frequency just above the minimum value can also be directly calculated. Simulations are carried out for the considered Taiwan power system and the results prove the efficiency of the proposed technique.

Power systems that are known as the most complex systems encounter different types of disturbances and emergence events. To operate such systems in a stable mode, several control protection techniques are in need. Frequency plays a vital role in power systems and needs to be properly maintained in a permissible level. To this end, under-frequency load-shedding (UFLS) techniques are used to intercept the frequency decline when a system encounters a severe disturbance. In this paper, a novel, wide-area measurement system (WAMS)-based optimal UFLS technique is proposed. The system frequency response (SFR) model is identified online based on the real-time measurements collected by phasor measurement units (PMUs). Then, the SFR model is used to design a new optimal multi-stage UFLS scheme. Imperialist competitive algorithm (ICA), which is a powerful evolutionary computing method, is then adopted for solving the suggested multi-stage UFLS optimization problem. The applicability of the proposed method is shown on a practical test system. The effectiveness of the proposed optimal multi-stage UFLS scheme is verified by several simulation and comparison scenarios.

The rapid growth of rooftop photovoltaic (PV) arrays installed in residential houses leads to serious voltage quality problems in low voltage distribution networks (LVDNs). In this paper, a combined method using the battery energy management of plug-in electric vehicles (PEVs) and the active power curtailment (APC) of PV arrays is proposed to regulate voltage in LVDNs with high penetration level of PV resources. A distributed control strategy composed of two consensus algorithms is used to reach an effective utilization of limited storage capacity of PEV battery considering its power/capacity and state of charge (SoC). A consensus control algorithm is also developed to fairly share the required power curtailment among PVs during overvoltage periods. The main objective is to mitigate the voltage rise due to the reverse power flow and to compensate the voltage drop resulting from the peak load. Overall, the proposed algorithm contributes to a coordinated charging/discharging control of PEVs battery which provides a maximum utilization of available storage capacity throughout the network. In addition, the coordinated operation minimizes the required active power which is going to be curtailed from PV arrays. The effectiveness of the proposed control scheme is investigated on a typical three-phase four-wire LVDN in presence of PV resources and PEVs.

The increasing share of uncertain wind generation has changed traditional operation scheduling of power systems. The challenges of this additional variability raise the need for an operational flexibility in providing both energy and reserve. One key solution is an effective incorporation of plug-in electric vehicles (PEVs) into the power system operation process. To this end, this paper proposes a two-stage stochastic programming market-clearing model considering the network constraints to achieve the optimal scheduling of conventional units as well as PEV parking lots (PLs) in providing both energy and reserve services. Different from existing works, the paper pays more attention to the uncertain characterization of PLs takes into account the arrival/departure time of PEVs to/from the PL, the initial state of charge (SOC) of PEVs, and their battery capacity through a set of scenarios in addition to wind generation scenarios. The results reveal that although the cost saving as a consequence of incorporating PL to the grid is below 1% of total system cost, however, flexible interactions of PL in the energy and reserve markets can promote the integration of wind power more than 13.5%.

Power systems are the most complex systems that have been created by men in history. To operate such systems in a stable mode, several control loops are needed. Voltage frequency plays a vital role in power systems which need to be properly controlled. To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems. Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance. Likewise, the power exchanges between different control areas are controlled by LFC approaches. In recent decades, many control approaches have been suggested for LFC in power systems. This paper presents a comprehensive literature survey on the topic of LFC. In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems. Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups. The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC.

The voltage rise problem in low voltage (LV) distribution networks with high penetration of photovoltaic (PV) resources is one of the most important challenges in the development of these renewable resources since it may prevent the maximum PV penetration considering the reliability and security issues of distribution networks. In this paper, the battery energy storage (BES) systems are used in order to solve the voltage rise during the peak PV generation as well as the voltage drop while meeting the peak load. A coordinated control strategy is proposed to regulate the charge/discharge of BESs using a combination of the local droop based control method and a distributed control scheme which ensures the voltages of feeder remain within allowed limits. Therefore, two different consensus algorithms are used: The first algorithm determines the BESs participation in voltage regulation in terms of their installed capacity whereas the second one modifies the BESs performance in terms of their state of charge (SoC) to prevent the excessive saturation or depletion of batteries. The proposed controller enables the effective use of storage capacity in different conditions. Finally, the simulation results based upon real data of a radial distribution feeder validate the effectiveness of this approach.

One of the major challenges in protection of the inverter-interfaced islanded microgrids is their limited fault current level. This degrades the performance of traditional overcurrent protection schemes. This paper proposes a fault detection strategy based on monitoring the transient response of the inverter current waveform using a transient monitoring function. To enhance the ability of the proposed fault detection scheme, an auxiliary control system is employed in addition to the main control system of the inverter. The proposed scheme can also differentiate asymmetrical and symmetrical fault conditions from normal load switching events and is effective for various inverter topologies (i.e., three/four-leg), main current limiting strategies, and all reference frames of the multi-loop control system. The merits of the proposed fault detection scheme are demonstrated through several time-domain simulation case studies using the CIGRE benchmark low voltage microgrid network.

There has been a considerable importance for the islanding detection due to the growing integration of distributed generations (DGs) in the modern power grids. This paper proposes a novel active islanding detection scheme for synchronous DGs, considering two additional compensators and a positive feedback for each of active and reactive power control loops. The added blocks are designed using the small gain theorem and stability margins definition considering characteristics of open loop transfer functions of synchronous DG control loops. Islanding can be detected using the proposed method even where there is an exact match between generation and local load without sacrificing power quality. In addition, the performance of the proposed method can be retained even with high penetration of motor loads. The proposed scheme improves the stability and power quality of the grid, when the synchronous DG is subjected to the grid-connected disturbances. Furthermore, this method augments the stability margins of the system in the grid-connected conditions to enhance the disturbances ride-through capability of the system and reduce the negative impact of the active methods on the power quality. Simultaneous advantages of the proposed scheme are demonstrated by modeling a test system in MATLAB software and time-domain simulation achieved by PSCAD.

With high penetration of distributed energy resources (DER), fault management strategy is of great importance for the distribution network operation. The objective of this paper is to propose a current and voltage limiting strategy to enhance fault ride-through (FRT) capability of inverter-based islanded microgrids (MGs) in which the effects of inverter control system and inverter topology (four/three-wire) are considered. A threephase voltage-sourced inverter (VSI) with multi-loop control system implemented in synchronous, stationary, and natural reference frames is employed in this study for both four- and three-wire configurations. The proposed strategy provides high voltage and current quality during overcurrent conditions, which is necessary for sensitive loads. Several time-domain simulation studies are conducted to investigate the FRT capability of the proposed strategy against both asymmetrical and symmetrical faults. Moreover, the proposed method is tested on the CIGRE benchmark microgrid to demonstrate the effectiveness of the proposed limiting strategy.

SUMMARY An important requirement for interconnecting distributed generation is anti-islanding protection. This paper uses the capabilities of two methods, application region (AR) and power imbalance AR, to efficiently adjust frequency-based relays. The proposed method gives a proper simple and nonexpensive solution to the synchronous distributed generation islanding detection problem. It employs the common protection devices: frequency or rate of change of frequency relays. These relays are adjusted in order to satisfy the anti-islanding protection and safe and abnormal frequency variation requirements and also to discriminate between islanding and nonislanding disturbances. The procedure is applied to a real system, which is a portion of the Isfahan Regional Electric Network in Iran, to show the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.

Summary Industrial microgrids (IMGs) consist of factories with distributed energy resources (DERs) and electric loads that heavily rely on combined heat and power (CHP) systems. The new generations of IMGs are expected to also include renewable DERs and plug-in electric vehicles (PEVs) with different power ratings and charging characteristics. This paper proposes a profit-based security constrained unit commitment (PB-SCUC) formulation for IMGs with PEV charging and renewable DERs that includes both microgrid security and factories constraints as well as the PEV charging requirements. PB-SCUC will utilize the generators waste heat to fulfill thermal requirements and also consider the status of renewable DERs to decrease the overall cost of IMG. To demonstrate the effectiveness of PB-SCUC, detailed simulation results are presented and analyzed for an IMG consisting of 12 factories and 6 types of PEVs without/with photovoltaic generations operating in grid-connected and stand-alone modes. Copyright © 2014 John Wiley & Sons, Ltd.

In the event of a generator loss or disturbance, the power system frequency declines quickly and overall system stability is at risk. During these scenarios, under frequency load shedding is triggered to restore the power system frequency. The main stage of modern adaptive under frequency load shedding techniques is disturbance estimation. However, the swing equation is widely used in disturbance estimation but has some critical estimation errors. In this paper, instead of using the swing equation we proposed the use of a disturbance observer to estimate the curtailed power. By making use of wide area measurements, a system frequency response model, which is a representative of the whole power system, can be realized in real time. Using different power system states of the developed model, a disturbance observer can be designed as well. The main advantage of the disturbance observer is that it can accurately estimate the disturbance magnitude and its location in a very short time. Further investigations show that by using the disturbance observer disturbances, which occur at the same time or at different times in different areas regardless of the magnitude or size, accurate estimations can be made. To ascertain the efficiency of the proposed scheme, simulations are done for a four-area power system using Matlab/Simulink.

Power systems are the most complex systems and have great importance in modern life. They have direct impacts on the modernization, economic, political and social aspects. To operate such systems in a stable mode, several control and protection techniques are required. However, modern systems are equipped with several protection schemes with the aim of avoiding the unpredicted events and power outages, power systems are still encountering emergency and mal-operation situations. The most severe emergencies put the whole or at least a part of the system in danger. If the emergency is not well managed, the power system is likely to have cascading failures that might lead to a blackout. Due to the consequences, many countries around the world have research and expert teams who work to avoid blackouts on their systems. In this paper, a comprehensive review on the major blackouts and cascading events that have occurred in the last decade are introduced. A particular focus is given on the US power system outages and their causes since it is one of the leading power producers in the world and it is also due to the ready availability of data for the past events. The paper also highlights the root causes of different blackouts around the globe. Furthermore, blackout and cascading analysis methods and the consequences of blackouts are surveyed. Moreover, the challenges in the existing protective schemes and research gaps in the topic of power system blackout and cascading events are marked out. Research directions and issues to be considered in future power system blackout studies are also proposed.

Ever since energy sustainability is an emergent concern, Plug-in Electric Vehicles (PEVs) significantly affect the approaching smart grids. Indeed, Demand Response (DR) brings a positive effect on the uncertainties of renewable energy sources, improving market efficiency and enhancing system reliability. This paper proposes a multi-stage stochastic model of a PEV aggregation agent to participate in day-ahead and intraday electricity markets. The stochastic model reflects several uncertainties such as the behaviour of PEV owners, electricity market prices, and activated quantity of reserve by the system operator. For this purpose, appropriate scenarios are utilized to realize the uncertain feature of the problem. Furthermore, in the proposed model, the PEV aggregation agents can update their bids/offers by taking part in the intraday market. To this end, these aggregation agents take part in Demand Response eXchange (DRX) markets designed in the intraday session by employing DR resources. The numerical results show that DR provides a perfect opportunity for PEV aggregation agents to increase the profit. In addition, the results reveal that the PEV aggregation agent not only can increase its profit by participating in the DRX market, but also can become an important player in the mentioned market.

Considering six common types of substation automation systems (SASs), this paper not only performs a quantitative reliability evaluation of different automated industrial substations, but also assesses the impacts of various automated substations on the distribution system reliability. The technique is based on the event-tree methodology, reliability block diagram approach, and the concept-of-expectation method. The proposed approach is applied to the eight basic industrial substation configurations, and quantitative assessment of reliability benefits from the utilization of substation automation is conducted through a range of studies. The results show the value of using a systematic quantitative approach for investigating the effects of automation systems on substation reliability. The main contributions of this paper are: 1) to give explicit formulas for reliability evaluations of the automated industrial substation with arbitrary time duration of the automatic switching operation; 2) to prove the SAS with a faster automatic switching operation has a higher degree of improvement in the substation reliability indices; 3) to provide an effective tool for ranking the most reliable industrial substation configurations in the presence of various SASs; and 4) to quantitatively evaluate the effects of the automated substation with various SASs on distribution reliability indices.

Due to the fact that repair plays a vital role in the reliability modeling, this paper investigates the effects of component repair on the availability, reliability, and component importance analyses of various four substation automation systems (SASs). For this purpose, some explicit expressions are derived for the steady-state availability, mean time to failure, mean time to first failure (MTTF1), and repair rate regarding a repairable SAS. Then, some numerical results are presented and are accompanied by detailed descriptions of how much increase in the reliability and availability indices of SASs can take place with component repair. Besides, for the repairable model, the results obtained demonstrate the most reliable SAS in comparison with the others. Then, different sensitivity analyses have been carried out for the repairable and the nonrepairable SAS. Finally, some suitable measures of importance are selected and used, thereby knowing which components of a repairable SAS are the most important and how much they can improve the system performance. The results calculated by importance measures can be informative to guide the designers when trying to enhance the performance of a repairable SAS.

A new method based on runs test is proposed to distinguish the inrush currents from the internal faults in power transformers, which is derived from the inherent differences between these waveforms. First, two statistical hypotheses that represent these differences are defined. Then by testing these hypotheses using runs test and by comparing the outputs of the hypotheses, a criterion to identify the internal fault is obtained. A total of 200 experimental cases are used to test the performance of the technique. In all of the tests, the proposed method accurately distinguished between fault and inrush currents without any errors. Also the suitable performance of the method is demonstrated by simulation of different faults and switching conditions on a power transformer. For this purpose, a small part of Iran power system involving a power transformer and the transmission lines on both sides of the transformer has been considered. To include effective factors on differential current components, the elements of this power system have been precisely modeled in PSCAD/EMTDC. Copyright © 2010 John Wiley & Sons, Ltd.

In this paper, by defining and solving an optimization problem, amount of distributed generators (DGs) and reactive power sources (RSs) in selected buses of a distribution system are computed to make up a given total of distributed generation for minimizing losses, line loadings, and total required reactive power capacity. The formulated problem is a combinatorial problem, therefore Tabu search algorithm is applied for solving the optimization problem. Results of solving the optimization problem for a radial 33-bus distribution system and a meshed 6-bus system are presented. When using less amount of reactive capacity, regarding tap positions of voltage regulators as control variables has considerable role in loss reduction and improvement of voltage profile. In the case of meshed systems, including line loadings in the cost function can significantly change results of solving the optimization problem such as amount of the required reactive capacity and how to assign DGs and RSs to the selected buses. Copyright © 2006 John Wiley & Sons, Ltd.

Summary Industrial parks are forming industrial microgrids (IMGs) with factories, distributed energy resources, electric loads, heat loads, and combined heat and power systems as well as renewable distributed energy resources and plug-in electric vehicles (PEVs). Generation scheduling (GS) in IMGs is affected by the stochastic behavior of electric and heat loads due to outages of production processes or production lines and the uncertainties in solar irradiance and combined heat and power systems. This paper presents a stochastic scenario-based GS framework to consider uncertainties in an IMG coordinated with PEV charging. Although the scenario-based methods are usually very time consuming, this paper shows that their applications in IMGs will not significantly increase the calculation time. The proposed formulation guaranties that occurrence of each condition of uncertainty will not affect the PEV activities. An IMG with 12 factories, photovoltaic generations, and 6 types of electric vehicles with different battery sizes is considered and simulated. The main contributions are (1) a new stochastic GS problem formulation to minimize the cost of IMGs while fully charging all PEVs within their requested periods considering the network security, factories, and PEV constraints; (2) changing the nonlinear constraints to linear forms suitable for scenario-based optimization; and (3) considering the stochastic behavior of electric loads without requiring any data about their internal process in each factory.

Summary Interconnection standards prevent islanding operation of distributed generations (DGs) to keep the safety and avoid the equipment failure. To meet this requirement for synchronous DGs (SDGs), the frequency-based relays are commonly used in the active distribution networks. This paper shows that in some conditions, a voltage relay has better islanding detection performance than a frequency relay regarding the SDG operating point, power factor of loads, and network characteristics. In this paper, a method is proposed for adjusting and evaluating a voltage relay based on application region and power imbalance application region to satisfy the islanding detection and safe and abnormal voltage variation criteria and to eliminate the false operation for the non-islanding disturbances including load shedding, load restoration, and 3-phase short-circuit fault, as far as possible. The relay false operation is studied for a combination of the control mode of SDG excitation system and the load type that leads to the highest possibility of relay false operation for the non-islanding disturbances. A number of dynamic simulation case studies are conducted to investigate the characteristics and capabilities of the proposed SDG anti-islanding protection scheme in both single- and multi-DG systems.

Proposed is a methodology to evaluate bus selection for synchronous machine-based distributed generators considering their first swing stability. The notion of trajectory sensitivity is used to define a stability index that ranks the distribution system buses subsequent to a set of credible contingencies. The proposed methodology is verified using a radial test feeder.

In this study, a novel voltage droop scheme for the parallel operation of voltage source converters (VSCs) in an islanded multibus microgrid is proposed. In this scheme, the voltage droop coefficient is defined as a function of respective VSC active and reactive power outputs. Thus, each VSCs voltage reference is adaptively drooped as a non-linear function of its active and reactive power outputs. This approach leads to reduction in the reactive power sharing dependence on real power control and system parameters such as mismatched connecting and line impedances. A multiobjective index is introduced for evaluating the scheme performance. The index is used as an objective function in an optimisation problem that is employed to obtain optimal parameters of the scheme. The detailed analysis shows that this scheme has a superior behaviour compared to the conventional voltage droop method, in view of the reactive power sharing and loads voltage control under all loading conditions. Simulation and experimental results show the good performance of the method for three paralleled VSCs in a multibus microgrid system.

The time-varying nature of electric arc furnace (EAF) gives rise to voltage fluctuations, which produce the effect known as flicker. The ability of a static VAr compensator (SVC), a widely used method for flicker reduction, is limited by delays in reactive power measurements and thyristor ignition. To improve the SVC performance in flicker compensation, a technique for the prediction of EAF reactive power for a half cycle ahead is presented. This technique is based on a new procedure for stochastic modelling of EAF reactive power at an SVC bus. This procedure uses huge field data, collected from eight arc furnaces, to determine the most suitable signal among several candidate signals in view of EAF reactive power prediction. In addition, appropriate orders of autoregressive moving average models are found for reactive power time series. For this purpose, various model adequacy checking methods and some other stochastic analysis methods have been applied on data records. The performance of the compensator in the case of employing predicted fundamental reactive power of an EAF is compared with that of the conventional method by using three new indices that have been defined based on concepts of flicker frequencies and the power spectral density.