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Dielectric testing techniques, in both time and frequency domains, are currently widely used by power utilities for assessment of the condition of transformer oil-paper insulation systems. However, it has been reported that results of these tests are highly influenced by the operating temperature during measurements. The distribution, migration and equilibrium of moisture between oil and paper in a complicated insulation system is highly temperature dependent. It requires adequate experience and proper understanding to interpret the dielectric response results in the presence of temperature variations and thermal instability. Proper analysis of the dielectric test result is only possible with an understanding of the physical behavior of the insulation system in response to temperature. A circuit model, which describes the dielectric behavior of the transformers main insulation system, has been investigated in this paper. The values of the parameters of the model have been identified from the dielectric tests. A correlation has been observed between the operating temperature and the equivalent model parameters that can be used as additional information for better interpretation of the dielectric test results. This paper thus reports a detailed study on the effects of temperature on dielectric measurements of a transformer under controlled laboratory conditions. Some results of practical on-site testing are also presented to demonstrate the possibility of errors that may be introduced in dielectric test results analysis unless temperature effects are taken into consideration. [ABSTRACT FROM AUTHOR]

One of the issues faced by asset managers in the electric power industry is the condition and remaining life assessment of the high voltage (HV) assets. In contrast to other power equipment, transmission power cables are mainly subjected to corrective maintenance. To support the asset management of service aged transmission power cable circuits, this paper discusses an approach of integrated knowledge rules for condition-based maintenance based on laboratory investigations and field examples. There are very few recent publications on this subject in spite of aging power cable infrastructure; therefore, this paper aims at showing practical applications of condition-based maintenance of this important component of the transmission and distribution systems. [ABSTRACT FROM AUTHOR]

This paper provides the electrical equivalent circuits of high-resistance grounded (HRG) power systems other than the delta–wye-connected utility power supply transformer included in Part I of this paper. This paper also provides the HRG of a medium-voltage generator for connection to an industrial power system and to a utility power system, and this paper discusses a line–ground fault with fault resistance. Three-line diagrams of ungrounded power systems are also included to illustrate the HRG application and its effect on the ground fault current during the line–ground fault. The damage at the fault location is based on the assumption that the fault remains a line–ground fault until it is cleared by appropriate ground fault protection relays. The fault resistance and the fault current that have an effect on the damage at the fault location are included. This paper provides guidance to update the current edition of the IEEE STD. 142, with respect to HRG systems. [ABSTRACT FROM AUTHOR]

In interconnected power systems, operated by several system operators, the participating areas are strongly dependent on their neighbors. In order to identify the economically efficient generation dispatch in each area, a distributed multi-area optimal power flow (OPF) must be solved. Additionally, installation of an increasing number of HVDC lines to deal with increased power flows from renewable generation is expected to change the power system operation paradigm. The controllability introduced by the HVDC lines should be considered and incorporated in the OPF algorithm. In this paper we introduce a formulation for the distributed solution of the OPF problem in multi-area systems consisting of both HVAC and HVDC lines. We show the applicability of this formulation on two different operating schemes for HVDC grids and we compare their performance with a central solution for the mixed HVAC/HVDC grid. The proposed formulations are based on a linearized solution of the OPF problem. The only data to be exchanged between the areas pertains to the border nodes. [ABSTRACT FROM AUTHOR]

Search for a reliable and efficient insulation diagnostic tool has always been the interest of power utilities. Today a large number of methods are available that can be used for insulation condition monitoring. These methods include both traditional and newer techniques. However due to complex aging process of oil paper insulation under the influence of different types of stresses, insulation condition assessment is generally performed by experts after carefully evaluating different measurement data. Furthermore, measurement data are influenced by various factors (like conductive aging byproducts, furanic compounds, paper and oil-moisture) in addition to measurement error (if any). This makes prediction of insulation condition based on single type of measurement rather difficult. This paper presents an Expert System designed to perform insulation diagnosis. The Expert System considers measurement data obtained using both traditional and newer techniques in order to come to a definitive conclusion. The Expert System extracts insulation condition sensitive information from data obtained using different techniques and then uses these to devise an optimized insulation model. This optimized model is used to predict papermoisture content and other insulation condition sensitive parameters. Since these values are predicted using optimized model, they are not dependent on a single type of measurement and hence are less likely to be affected by error of any specific measurement. The performance of the developed Expert System is first tested on a laboratory sample and then on several real life power transformers belonging to NTPC Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes an optimization approach for day-ahead reactive power planning to improve voltage security in transmission networks. The problem is formulated as a voltage-secure multi-period optimal reactive power dispatch (MP-ORPD) problem. The optimization approach searches for optimal set-points of dynamic and static reactive power (var) resources. Specifically, the output includes set-points for switching shunts, transformer taps, and voltage magnitudes at the regulated buses. The primary goal is to maximize the dynamic reactive power reserve of the system, by minimizing the reactive power supplied by synchronous generators. As the size of the MP-ORPD problem increases significantly with increasing number of contingencies and time periods, efficiency is crucial for practical applications. In this paper, a decomposition technique based on consensus and alternating optimization, where integer variable targets are obtained via MILP, is used to partition the MP-ORPD problem into a set of subproblems, which can be solved in parallel to reduce the computation time. The proposed MP-ORPD problem and its solution algorithm are integrated into the EPRI-VCA software. The results of various power networks of large electric utilities in the Eastern interconnection demonstrate the effectiveness of the proposed algorithm in providing preventive control schedules. [ABSTRACT FROM AUTHOR]

The need for economic, reliable, and effective delivery of electric power has lead to the search for fast, efficient, and effective methods for diagnosing the insulation of high-voltage (HV) equipment in the power industries. The recent dielectric techniques that have been carefully considered by major industries for transformer insulation condition assessment are the recovery voltage method (RVM) and the polarization and depolarization current (PDC) measurement. However, due to the complexity of the transformer insulation structure and various degradation mechanisms under multiple stresses, insulation condition assessment is usually performed by experts with special knowledge and experience. In this paper, an expert system (ES) is developed, which imitates the performance of a human expert, to make the complicated insulation condition assessment procedure accessible to plant maintenance engineers. The structure of the ES is described in detail including knowledge base, inference engine, and human-computer interface. Examples of the application of the ES are also presented to confirm that the system can provide accurate insulation diagnosis. [ABSTRACT FROM AUTHOR]

The lack of information regarding the systemic behavior of new software and hardware before introducing them for controlling and operating power networks consists of a major challenge for power distribution utilities towards a smart grid implementation. In this context, this paper describes an innovative and cost-effective test platform for advanced distribution automation (ADA) functionalities. The platform integrates a steady-state power system simulator, intelligent electronic devices, smart meters, communication infrastructure, and typical operation systems, using a cyber-physical system approach. The development of such platform originated a novel smart grid emulator, aiming at the execution of systemic tests and validation of ADA functionalities in a controlled environment, allowing systemic analysis rarely found in hardware-in-the-loop (HIL) testbeds. Through such an approach, it is possible to predict and solve typical issues that would be typically noticed only in field implementation. The study case presents tests of a specific algorithm for downed conductor location, considering the environment that the power distribution utility would have through the deployment of a smart grid infrastructure. The paper also discusses the robustness of the event-driven synchronization as an interface technique for HIL and software-in-the-loop environment, which is responsible for integrating operation systems, field equipment, and the power system simulator. [ABSTRACT FROM AUTHOR]

Concerns about the cybersecurity and resilience of power systems have heightened in electric utilities and regulatory agencies over the past decade mainly because of the unpredictable target, location and scale of cyberattacks and the potential severity of consequences. The cybersecurity of pilot protection is paramount in bulk power systems considering their prevalence and the crucial role they play in protecting critical assets and preventing large system disturbances and major blackouts. This paper investigates the resilience of pilot protection using a co-simulation platform based on OPAL-RT simulator and Riverbed Modeler. It is demonstrated that software-defined networking for operational technology (OT SDN) significantly improves the resilience of pilot protection to false data injection (FDI) attacks compared to traditional networks. Moreover, the resilience of OT SDN based pilot protection to denial of service (DoS) attack against the SDN controller is investigated both in the proactive and reactive modes of operation. The simulation results verified the resilience of OT SDN controller in OT SDN based pilot protection to DoS attacks in the proactive mode of operation. [ABSTRACT FROM AUTHOR]

Preventive diagnosis and maintenance of transformers have become more and more popular in recent times in order to improve the reliability of electric power systems. Dielectric testing techniques such as return voltage measurement (RVM) and polarization-depolarization current (PDC) measurement are being investigated as potential tools for condition assessment of transformer insulation. A better understanding and analysis of the dielectric test results are only possible with a clear understanding of the physical behavior of the insulation system in response to moisture and aging. A circuit model, which describes the dielectric behavior of the transformer's main insulation system, has been parameterized in this paper. The values of the parameters of the model have been identified from the dielectric tests. A correlation has been developed between the physical condition of the insulation and the equivalent model parameters that enable a clear and transparent interpretation of the dielectric test results. [ABSTRACT FROM AUTHOR]

Transformers are the most expensive element of a power system, and so transformer monitoring systems are becoming more important as loads increase. Under heavy loading conditions, the hot-spot temperature of a transformer is the most critical parameter to determine the limit of loading. Therefore, to make an accurate estimation of hot-spot temperature and maintain the reliability of a power system, dynamic thermal models or methods must be employed. Due to the complexity of thermal phenomena, the methods presented so far needs to be improved to reduce computational errors. This is particularly the case for variable loading conditions and power utilities are still in need of good techniques. This paper describes two methods to determine temperature in single-phase, oil-immersed transformers. The first method calculates average windings temperature (AWT) using the voltage and current from primary and secondary windings. The second method, which uses data from the first method, determines the hot-spot temperature of the transformer. The methods have been investigated by experiments on a 30 kVA single-phase transformer and verified the results using COMSOL ™ software. Our methods have proven more accurate than the IEEE Annex G method. [ABSTRACT FROM AUTHOR]

Urban power grids are facing many operational and expansion challenges to meet further demand growth and increased reliability requirements. Advanced transmission technologies have been considered by the electric utilities to effectively increase the utilization of existing infrastructure and operational flexibility. The focus of this paper is on VSC-HVDC technologies for urban power grid enhancement and modernization. First, a potential technical scheme is proposed for converting an existing AC circuit to DC operation, which could boost the power transfer capability of the critical transmission corridor and increase network operational flexibility. Second, this paper proposes three operation modes for the VSC-HVDC interties in urban power grids corresponding to normal, emergency and island operating conditions, respectively. An integrated, adaptive emergency control strategy (AEC) is proposed that can enable adaptive power flow responses of the VSC-HVDC intertie under varying system operating conditions and critical contingencies. The flexibility and effectiveness of the proposed operational principles of urban VSC-HVDC intertie and the corresponding control strategies are verified in PSCAD/EMTDC using a realistic urban power grid in China. [ABSTRACT FROM AUTHOR]

This paper presents a new non-deterministic approach for multiyear distribution network reinforcement planning (DNRP) considering the uncertainty sources pertaining to loads, electricity prices, investment costs, and operation costs. Accordingly, the underlying idea of the information-gap decision theory (IGDT) is used to obtain a robust solution protected against different realizations of each uncertain variable lying in its robust region. The proposed model is capable of adjusting the robustness of the optimal solution in terms of a specific parameter designated as the budget of uncertainty. As the uncertain loads, investment and operation costs competitively tend to maximize their robust regions for a particular value of the budget of uncertainty, the normalized normal constraint (NNC) method as a proficient multi-objective optimization method is exploited in this paper to solve the proposed multiobjective IGDT-based DNRP (IGDT-DNRP) model. Mainly, the NNC method presents a set of Pareto optimal solutions rather than a single optimal solution. Accordingly, a posteriori out-of-sample analysis is introduced in this paper to find the best solution among the set of Pareto optimal solutions. The proposed IGDT-DNRP model is implemented on the IEEE 33-bus distribution network under different circumstances. Simulation results illustrate the effectiveness of the proposed nondeterministic approach. [ABSTRACT FROM AUTHOR]

Recently, the development of the electric power industry has led to an increase in the fault current when a fault occurs. It is important to reduce the fault current, since fault currents exceeding the capacity of protective devices can result in large blackouts. In order to reduce the fault current, there is a method to separate the bus line of main substation. However, this method has the disadvantage of complicating the power system. Another method is to install a superconducting fault current limiter (SFCL). The SFCL has the advantage that the fault current can be quickly limited within 1/4 cycle immediately after the fault occurrence without affecting the power system since its impedance is zero in a normal time. However, the application of SFCL affects the operation of the over-current relay (OCR) due to the reduced fault current such as trip time delay. The trip time delay of OCR was reported to be suppressed by using SFCL's voltage component in previous studies. In this paper, the impedance compensation method was suggested to exclude the effect of SFCL on OCR. To prevent OCR from the influence of SFCL, the component that can exclude the impedance of SFCL was considered to be added to the characteristic formula of OCR. In addition, the effect of correcting this characteristic equation was analyzed by constructing a power distribution system using PSCAD / EMTDC. [ABSTRACT FROM AUTHOR]

In this paper, a self-adaptive protection system is proposed for adjusting the time dial (TD) of reclosers found in electrical power distribution systems (EPDSs). The self-adjustment is carried out in both phase and ground protection. The methodology considers the fuses along the feeder to obtain the fuse-saving philosophy. This feature allows less interference on the protection system already implemented by the electrical power distribution utilities. This methodology also allows using other frameworks, such as the estimation of the fault distance. The software used for computer modeling and simulation was PSCAD™/EMTDC™. The flexibility provided by the method, which allows the incorporation of new logic and changes in decision-making, resulted in an adaptive method with a good performance against different locations, types, and fault impedance. It also resulted in better coordination between the protection devices (PDs). The results compared with well-coordinated conventional protection have shown significant performance gain with the adaptive system. [ABSTRACT FROM AUTHOR]

High resistance grounding (HRG) is a well-proven technology for improving electric reliability for many industrial and utility facilities such as used in petrochemical, automotive, and generating plants. Many such facilities require the increased reliability for production and operational reasons. This paper will discuss the improved personnel safety aspects of using HRG on low-voltage systems. In particular, this paper will discuss the following: 1) the probability of the three common faults occurring within an industrial plant, namely, three-phase, phase-to-phase, and ground faults; 2) how the probability of a ground fault can be used to improve electrical safety with HRG; 3) the impact of a ground fault on a system and the speed at which the ground fault on a solidly grounded system may propagate into a multiphase fault; 4) the risk reduction of a ground fault on an HRG system propagating into a multiphase fault; 5) the potential reduction in serious and fatal arc blast injuries through the use of an HRG system; and 6) potential single-pole breaker clearing issues when a second ground fault occurs on a second phase. This paper will include comments from recent testing, which was conducted at the KEMA Laboratories and presented in a recent IEEE Industry Applications Society Petroleum and Chemical Industry Committee paper in September 2014. [ABSTRACT FROM AUTHOR]

In this paper, classification of mental task-root brain–computer interfaces (BCIs) is being investigated. The mental tasks are dominant area of investigations in BCI, which utmost interest as these system can be augmented life of people having severe disabilities. The performance of BCI model primarily depends on the construction of features from brain, electroencephalography (EEG), signal, and the size of feature vector, which are obtained through multiple channels. The availability of training samples to features are minimal for mental task classification. The feature selection is used to increase the ratio for the mental task classification by getting rid of irrelevant and superfluous features. This paper suggests an approach to augment the performance of a learning algorithm for the mental task classification on the utility of power spectral density (PSD) using feature selection. This paper also deals a comparative analysis of multivariate and univariate feature selection for mental task classification. After applying the above stated method, the findings demonstrate substantial improvements in the performance of learning model for mental task classification. Moreover, the efficacy of the proposed approach is endorsed by carrying out a robust ranking algorithm and Friedman’s statistical test for finding the best combinations and compare various combinations of PSD and feature selection methods. [ABSTRACT FROM AUTHOR]

Voltage sag insurance (VSI) is an effective measure to reduce the voltage sag loss and risk for enterprises with insufficient mitigation confidence or economic ability. However, due to the lack of understanding of voltage sag risk (VSR), it is difficult for power utilities to identify the enterprises with VSI demands, and it is also unable to realize differentiated premium according to different enterprises' situations. To solve the above problems, this paper proposes an improved voltage sag premium model based on VSR. Firstly, the VSR factors are analyzed, such as the hazard, the vulnerability, the exposure. The process immune time is introduced to describe the vulnerability. Based on the traditional consideration of only the ability of users to resist voltage sag, the ability of users to recover from voltage sag is further considered. Then, the risk evaluation model of voltage sag is established. The evaluation results can help power utilities to judge whether enterprises have the demand of VSI. Finally, the improved premium model of VSI based on VSR is constructed to ensure the differentiation and rationalization of the premium. The correctness and rationality of this method are proved by ten manufacturing enterprises in China by analyzing the VSR and comparing the premium before and after the improvement. [ABSTRACT FROM AUTHOR]

This paper presents a fast model-agnosticmethod for recovering noisy Phasor Measurement Unit (PMU) data streams with missing entries. The measurements are first transformed into a Page matrix, and the original signals are reconstructed using low-rank matrix estimation based on optimal singular value thresholding. Two variations of the recovery algorithm are shown- a) an offline block-processing method for imputing past measurements, and b) an online method for predicting future measurements. Information within a PMU channel (temporal correlation) as well as from different PMU channels in a network (spatial correlation) are utilized to recover degraded data. The proposed method is fast and needs no explicit knowledge of the underlying system model or measurement noise distribution. The performance of the recovery algorithms is illustrated using simulated measurements from the IEEE 39-bus test system as well as real measurements from an anonymized U.S. electric utility. Extensive numeric tests show that the original signals can be accurately recovered in the presence of additive noise, consecutive data drop, as well as simultaneous data erasures across multiple PMU channels. [ABSTRACT FROM AUTHOR]

Stray voltages have always been a concern to utility companies and customers. But methods to troubleshoot and monitor nonroutine stray voltage problems are very limited. This paper presents a passive, measurement-based method to identify the contributors to the common cause of stray voltages, the neutral-to-earth voltage (NEV) rise at the service entrance point. The paper shows that the NEV can be decoupled into two components: those related to the customer under investigation and those outside the customer facility. A method to quantify the relative contributions of the two components is proposed. A new concept called current return ratio is introduced to facilitate the decoupling and to quantify the grounding conditions of the system. This paper presents the background, circuit model, concept, and theory of the proposed method. [ABSTRACT FROM AUTHOR]

Overall electric energy conservation and improvement in electrical energy efficiency has been a topic of interest to the electric power industry for long time, since 40% of total primary energy used is in the form of electricity. There are many facets to the energy conservation and/or energy efficiency techniques. Energy conservation by voltage reduction popularly called “CVR” has recently gained some momentum, in particular, to reduce the peak demand. This is also an integral part of the discussion in the future smarter grid technology. This paper addresses the pros and cons of the CVR application including a thorough literature search, practical applications, and a quantifiable measure of its actual amount of energy saving from utilities and the cost associated with it. It is expected that this paper will serve as a foundation to all practicing engineers addressing the issue of CVR. [ABSTRACT FROM AUTHOR]

Planned and unplanned outages on distribution networks may cause major economic loss to customers and can result in substantial reparation payments by utilities. This paper analyzes the use of a battery energy storage system (BESS) to partially or completely avoid these outages. The analysis is conducted with a multiday high-demand scenario where the load demand at peak times exceeds the current capacity of the line. This would result in an outage unless the current from the substation can be reduced. Three basic scenarios representative of different degrees of sophistication of feeder automation were studied, i.e., a conventional feeder controlled by one or more reclosing breakers; a modern distribution feeder equipped with a limited number of remote-controlled breakers that will disconnect nonvital loads belonging to residential, commercial, and industrial customers; and a modern distribution feeder equipped with numerous remote-controlled breakers that will selectively disconnect commercial, industrial, and residential loads based on their degree of criticality. This paper concluded that the total or partial avoidance of outages by way of BESS usage is feasible; however, the use of “smart grid” control technology can provide more benefit than BESSs in the scenarios studied. [ABSTRACT FROM AUTHOR]

Current transformers (CTs) are extensively used for the measurement of electrical energy, and hence they play a crucial role in the revenue generation for power distribution utilities. The novelty of this paper is that it presents artificial neural network (ANN) application for the ratio and phase angle error corrections of CTs in the presence of harmonic distortions. In this paper, the behaviors of silicon iron alloy and nanocrystalline alloy CTs are examined by the means of a number of experimental tests under the sinusoidal and distorted waveform conditions. The relation between the nature of CTs secondary current waveforms (CTSwf) with their metrological properties, connected burdens, and nature of load currents (linear or nonlinear) is established. The training data are obtained by the nature of CTSwf in terms of amplitude errors, time shifts, and deviations caused by different harmonic contents between input and output quantities. The ANN is trained for various operating conditions. The implementation of the error correction system and data acquisition is done using dSPACE 1104 software. The experimental results illustrate that the proposed technique can be used for error compensation in case of sinusoidal and the distorted waveform composed of fundamental and many harmonics. [ABSTRACT FROM AUTHOR]

The resonant grounding is one of the possible methods of the system neutral grounding for the medium voltage distribution. IEEE standards do define this grounding configuration, but important advantages and drawbacks of the resonant grounding might not be fully known, due to its rather uncommon application in North America. On the other hand, resonant grounding in Europe is imposed by the increased requirements for power quality, especially for medium-voltage (MV) industrial users, imposed to electric utilities by regulatory authorities, with the purpose to protect the interests of users and consumers. Level of the continuity of the service, magnitude and phase of ground-fault currents, magnitude of touch voltages, all depend on how the neutral is connected to ground. In this paper, the authors will discuss electrical safety features of the resonant ground, and analyze issues when a substation, originally operated with different methods of system neutral grounding, is reconfigured with a resonant ground. In particular, a conservative approach for preserving safety during high-voltage (HV)-MV substations’ reconfiguration is herein proposed; the cases of the substation reconfiguration from resonant grounding to isolated-from-ground and vice versa shall be analyzed. Finally, the analysis of the impact of the use of Petersen coil on the global grounding systems will be provided. [ABSTRACT FROM AUTHOR]

This paper describes a selective high-resistance grounding (HRG) system for a large industrial facility with two in-plant generators in cogeneration mode and two utility transformers. In a five-step coordination using sensitive ground fault nondirectional and directional relays, ground faults throughout the distribution system are cleared with a maximum pickup setting of 6 A, and time delay of 0.25 s. A major consideration for HRG systems is that the stray capacitance charging current of the system should be small (10–15 A) to prevent ground fault damage. If the fault is left in place for some duration for a single-line-to-ground fault, insulation stresses occur due to higher line-to-ground voltages on two unfaulted phases. This paper demonstrates that with selective HRG, both these concerns are mitigated. A selective HRG is a bridge between the classical concepts of HRG and low-resistance grounding. The modern advancements in ground sensors and protective relaying can selectively clear low levels of ground fault currents, which make selective HRG a reality. [ABSTRACT FROM AUTHOR]

Risk of blackouts is more than expected and must be considered in the power system studies. The interest of this paper is to minimize the blackouts risk during minimizing the costs in probabilistic transmission expansion planning (TEP). In this paper, a long-term reliability analysis, which was developed by self-organized criticality theory, is used in a multi-objective optimization to include risk of blackouts in TEP. The objective functions are costs and expected energy not supplied. Also, a new formulation for calculating transmission operating cost as a part of cost function is proposed. The problem is solved by a multi-objective particle swarm optimization to find an optimal Pareto set from which the decision-maker can choose the most desirable one, regarding existing budget. The proposed method is applied to the IEEE 118-bus test system to investigate its applicability and scalability. The results are compared with security-constrained TEP, which uses famous deterministic criterion known as N-1. The proposed approach produces more efficient plans for suppressing cascading blackouts with less network investment. Moreover, the results provide motivation for considering the risk of cascading blackouts in TEP, which afford substantial saving to society. [ABSTRACT FROM AUTHOR]

Solar energy and bioenergy are two leading renewable forms of energy in the move toward a near-zero-emission electric power industry. Concentrated solar power units coupled with thermal storage and biomass power plant offer dispatchable electricity, raising their ever-growing role in future renewable-dominated networks. This paper proposes a day-ahead and intraday dispatch model for maximizing the profit of an Integrated Biomass-Concentrated Solar (IBCS) system considering the synergies arising from their coupled operation. To sensibly capture uncertainty and decision sequence of real-life electricity markets, a two-stage stochastic structure is proposed, while the solar-related uncertainty is involved using Information Gap Decision Theory (IGDT). The model is complemented with a novel multi-objective architecture based on the compound of IGDT and Conditional Value-at-Risk (CVaR), which allows handling risk exposure to both stochastic and IGDT inputs. The Pareto strategies in the multi-objective model are extracted through an expanded form of the $\epsilon$ -constraint method, whereas a posteriori approach based upon the out-of-sample assessment is applied to derive the optimal dispatch pattern among the generated Pareto strategies. The simulation results demonstrate that: 1) the proposed integrated dispatch model achieves substantial profitability, and 2) the performance of the suggested CVaR-IGDT model is superior to conventional approaches. [ABSTRACT FROM AUTHOR]

The European balancing market is undergoing radical transformation through numerous market design initiatives. These initiatives aim at improving geographical coordination among European transmission system operators, and better positioning the European system for integrating renewable resources through short-term operational efficiency and long-term investment in flexible resources. However, the European design is characterized by a missing market for real-time reserve capacity, that has been inherited from a failure to recognize the central role of real-time operations as the spot market of the electric power industry. This missing market undermines the valuation of reserve capacity, and the back-propagation of price signals to forward reserve markets that can support investment in reserves. The goal of the present paper is to develop a methodology that exposes the implications of this missing market. The methodology relies on analytical insights that can be derived under an assumption of price-taking behavior. These insights are validated by a simulation model which represents the European balancing market as a Markov Decision Process. The simulation model is used for validating the analytical insights and testing the ability of various balancing market design options to back-propagate the real-time value of reserve to forward reserve markets. [ABSTRACT FROM AUTHOR]

The power grid is a critical infrastructure that must be protected against potential threats. While modern technologies at the center of the ongoing smart grid evolution increase its operational efficiency, they also make it more susceptible to malicious attacks such as false data injection to electronic monitoring systems. This paper presents a game-theoretic approach to smart grid security by combining quantitative risk management techniques with decision making on protective measures. The consequences of data injection attacks are quantified using a risk assessment process where the well-known conditional value-at-risk (CVaR) measure provides an estimate of the defender's loss due to load shed in simulated scenarios. The calculated risks are then incorporated into a stochastic security game model as input parameters. The decisions on defensive measures are obtained by solving the game using dynamic programming techniques which take into account resource constraints. Thus, the formulated security game provides an analytical framework for choosing the best response strategies against attackers and minimizing potential risks. The theoretical results obtained are demonstrated through numerical examples. Simulation results show that different risk measures lead to different defense strategies, but the CVaR measure prioritizes high-loss tail events. [ABSTRACT FROM PUBLISHER]

With the increasing integration of PV generation in AC microgrids, it is challenging to keep the stability of system frequency due to the intermittent and stochastic nature of PVs. Thus, in order to reduce the investment and maintenance costs of storage systems, the electric utility has shown increasing interest in calling on PVs to provide frequency regulation services. In this paper, a novel sliding mode control (SMC) based adaptive power point tracking (APPT) control strategy is proposed to provide bi-directional primary frequency regulation (BPFR) of an AC microgrid. In this strategy, in order to restrain the variation of frequency, the sliding mode surface is adaptively regulated to provide an adaptive power reserve. Thus, the PVs will have a power headroom to regulate the frequency both up and down through releasing the reserved power or increasing the reserves of the PV systems. Furthermore, the sliding mode surface is adaptively regulated only based on the locally measured frequency of the microgrid without the requirements of communication, detailed PV model, irradiance sensors as well as MPP estimators. Thus, the proposed control strategy shows the advantages of easy to implement and reduces the investment and maintenance costs of installing storage systems or irradiance sensors. [ABSTRACT FROM AUTHOR]

Under the deregulated environment, electric utility companies have been encouraged to ensure maximum system reliability through the employment of cost-effective long-term asset management strategies. Previously, the age based Weibull distribution has been used vastly for modeling and forecasting aging failures. However, this model is only based on asset age and does not consider additional information such as asset infant mortality period and equipment energization delay. Some works on modifying Weibull distribution functions to model bathtub-shaped failure rate function can be practically difficult due to model complexity and inexplicit parameters. To improve the existing methods, this paper proposes four modified Weibull distribution models with straightforward physical meanings specific to power system applications. Furthermore, this paper proposes a novel method to effectively evaluate different Weibull distribution models and select the suitable model(s). More importantly, if more than one suitable model exists, these models can be mathematically combined as a joint forecast model, which could provide better accuracy to forecast future asset reliability. Finally, the proposed approach was applied to a Canadian utility company for the reliability forecast of electromechanical relays and distribution poles to demonstrate its practicality and usefulness. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are recently gaining traction in the power sector due to various challenges and opportunities they provide to utility operators. For electric utilities that incorporate demand side management (DSM) programs, EVs could become either a burden or an advantage depending on their charging control strategy and the signaling of the DSM program. This paper proposes a decentralized fuzzy-based controller to successfully integrate and coordinate the charging of EVs that ensures fair charging of EVs at different point of connections (POCs) in the distribution grid where voltage conditions might not be the same. The controller operates in an autonomous mode that reduces the monetary cost of the communication overhead and preserves bandwidth. The proposed controller takes into consideration the owner requirements in terms of energy needed and time to charge, the voltage at the POC with the grid, and the pricing signal coming from the utility. The controller is tested under different DSM programs that exist in the literature. This paper also proposes a new DSM program that is capable of benefiting from EVs as prosumers that can provide grid services. The controller's performance was validated through MATLAB simulations that showed the controller's ability to successfully coordinate the charging of EVs in a fair manner and achieve flat system peaks without any rebound effect. The controller was also successfully tested in the presence of voltage control units, such as capacitor banks, and in the presence of distributed generations. [ABSTRACT FROM AUTHOR]

Voltage sag is one of the most prominent power quality problems in the electric power system. Accurate estimation of voltage sag parameters is an important reference for electric utilities and users to evaluate power quality. In this paper, a novel algorithm based on modified S transform with digital prolate spheroidal window (DPSW) is proposed to achieve accurate detection of voltage sag. The DPSW and its time-frequency characteristics are firstly detailed. Then, the construction and performance of modified S transform with DPSW are given. Since DPSW has superior time-frequency distribution, characteristics of voltage sag signal, such as sag depth, duration, and phase jump, can be obtained by analyzing the two-dimensional complex matrix after the modified S transform with DPSW. Simulation and experimental results verify the accuracy and validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The distribution network has typically been the least observable and most dynamic and locally controlled element in the power grid. Complete information about the network topology is continuously changing and is not always readily available when needed. This makes the phase identification and network rebalancing a hard, costly, and time-consuming task for electric utilities, however, it is of great importance to future grid planning and advanced distribution management system (ADMS) type operation. Phase identification traditionally is executed manually, although there are existing voltage measurement based methods that are not always reliable. This paper develops a machine learning based data mining method for an accurate and efficient phase identification of residential customers in a distribution network by leveraging power consumption data collected through the advanced metering infrastructure (AMI). The proposed method uses a high-pass filter to remove the redundant and irrelevant parts of the power consumption time series, then identifies the residential customers’ phase connectivity by proposing a modified clustering algorithm. Simulation results show the effectiveness of the proposed method in phase identification in both small and large networks and under complete and incomplete data scenarios. [ABSTRACT FROM AUTHOR]

Leakage and magnetizing inductances of transformer windings are routinely measured by power utilities during scheduled maintenance. They are often used to confirm the diagnosis of mechanical damages in windings after Swept Frequency Response Analysis shows a mismatch. Inductance measurements performed at power frequency can possibly reveal the presence of damages that have substantially progressed but cannot detect them at their nascent stages since inductances at power frequency remain almost unaltered. This paper investigates the possibility of using high-frequency inductance to this end considering a frequently encountered mechanical damage, viz., disk-space variation in a disk winding. Effect of disk-space variation is investigated in this article using FEM at first and inductances at different frequencies are considered: magnetizing and leakage inductances at 50 Hz, and inductance at a higher frequency region corresponding to winding resonances, say, 500 kHz. The inductance at high frequencies not only exhibited increased sensitivity compared to that at power frequency, but also captured the extent of damage. Simulations performed using Ansys Maxwell and experimental results on an actual 1- $\phi$ transformer are reported. Results show that the high-frequency inductance not only offers a considerably increased sensitivity to disk-space variation in windings compared to the power frequency inductances, but also provides insight regarding the extent of movement which is not apparent from the frequency response. [ABSTRACT FROM AUTHOR]

Recent years have witnessed significant interest in convex relaxations of the power flows, with several papers showing that the second-order cone relaxation is tight for tree networks under various conditions on loads or voltages. This paper shows that ac-feasibility, i.e., to find whether some generator dispatch can satisfy a given demand, is NP-hard for tree networks. [ABSTRACT FROM AUTHOR]

This paper proposes a comprehensive framework to detect non-technical losses (NTLs) and recover electrical energy (lost by abnormalities or fraud) by means of a data mining analysis, in the Spanish Power Electric Industry. It is divided into four section: data selection, data preprocessing, descriptive, and predictive data mining. The authors insist on the importance of the knowledge of the particular characteristics of the Power Company customer: the main features available in databases are described. The paper presents two innovative statistical estimators to attach importance to variability and trend analysis of electric consumption and offers a predictive model, based on the Generalized Rule Induction (GRI) model. This predictive analysis discovers association rules in the data and it is supplemented by a binary Quest tree classification method. The quality of this framework is illustrated by a case study considering a real database, supplied by Endesa Company. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of a multiyear security constrained hybrid generation-transmission expansion planning. It is assumed that the overall generation requirements of a network are known along the planning horizon, but their allocations are unknown. Moreover the fuel cost throughout the net- work is not uniform. By allocating the overall generation capacity among the grid nodes, and determining the new transmission element additions along the planning horizon, the overall cost of the system is minimized. The problem is formulated as a mixed integer nonlinear programming problem, which for a large-scale system is very difficult to solve. In this paper a new constructive heuristic approach is proposed, so that the problem can be readily solved. To assess the capabilities of the proposed approach, two networks are studied: the Garver test grid as a small grid and the Iranian power grid as a large-scale grid. [ABSTRACT FROM AUTHOR]

This paper describes a novel regenerative braking control scheme of electric power-assisted wheelchairs for safety driving on downhill roads. The "electric power-assisted wheelchair" which assists the driving force by electric motors is expected to be widely used as a mobility support system for elderly people and disabled people; however, it has no braking system to suppress the wheelchair's velocity and brings the dangerous and fearful driving particularly on downhill roads. Therefore, this paper proposes a navel safety and efficient driving control scheme based on the regenerative braking system. This paper applies the regenerative braking system with the step-up chopper circuit serially connecting two motors and realizes the velocity feedback control with the variable duty ratio so that it tracks the optimal velocity based on the Minimum Jerk Model. In addition, the dynamic braking system is also applied at the low-speed range instead of the regenerative braking in order to suppress the acceleration. Some driving experiments on the practical downhill roads show the effectiveness of the proposed control system. [ABSTRACT FROM AUTHOR]

This paper proposes a procedure and methodology for performance target setting related to continuity metrics in electricity distribution networks. This proposal deals with one of the key issues in the monopoly regulation, which is either the reduction of the information asymmetry among economic agents or the emulation of a competitive environment in industry segments usually considered as natural monopolies. This paper develops an approach toward standard definitions for Customer Average Interruption Duration Index (DEC) and Customer Average Interruption Frequency Index (FEC) based on inter-companies comparative analysis. This approach introduces productive efficiency concepts to the definition of network performance. In order to do so, the data envelopment analysis (DEA) technique, used for defining the efficiency frontier, was combined with the dynamic cluster technique, oriented toward models of identification of similar networks. A technique for comparative analysis was used for the definition of the network expected performance. Examples with the Brazilian electric systems are provided to clarify the methodology suggested by this paper. [ABSTRACT FROM AUTHOR]

The objective of this paper is to analyze the dynamics of distribution systems that contain fuel cells and to enhance the stability of these systems by controlling the fuel cells. The models used in this second part of the two-part paper are the solid-oxide fuel cell (SOFC) models developed in part one. The fuel-cell control loops through the power conditioning units are first explained using a one-machine infinite bus system. Then, fuel cells are integrated into a power distribution test system, which initially contains gas turbines only. Simulation results show how a combination of fuel cells and gas turbines can help control frequency fluctuations, and supply power after islanding of the distribution system. [ABSTRACT FROM AUTHOR]

Maintenance management—as a part of the asset management policies—plays a vital role in enhancing the reliability of the electricity distribution system (EDS). The electric utility companies devote a considerable effort to allocate their financial resources to critical parts of the system, to achieve higher efficiencies. In this paper, a practical method is proposed for reliability-centered maintenance budgeting. The proposed method determines the optimal maintenance actions and their execution times in EDS feeders. The objective is to minimize the total reliability cost, including: the total customer interruption cost and total energy not supplied cost. Moreover, four cases are considered to explore the performance of the proposed maintenance method, including: the conventional EDS, the EDS equipped with remote-controlled switches (RCSs), maintenance budgeting and time allocation for the conventional EDS, and maintenance budgeting and time allocation for the EDS equipped with RCSs. The proposed reliability improvement approaches are applied to bus number two of the Roy Billinton test system, as well as a real scale distribution network followed by discussions on the obtained results. [ABSTRACT FROM PUBLISHER]

If an extreme contingency strikes the Kinmen Island power system in Taiwan, it is very likely to cause blackouts. Although an underfrequency protection scheme has been applied, some drawbacks of the protection scheme hinder the Kinmen power system from avoiding blackouts. In the past decade, several blackouts have occurred in the Kinmen power system. To avoid further possible blackouts, a special protection system (SPS) is summoned. This paper describes the design guidelines and deployment procedures of an SPS for the Kinmen power system. The design depends on the Kinmen power system characteristics, and the deployment hinges upon the supervisory control and data acquisition system. Exquisite software was also developed to testify the Kinmen system SPS. Operational records have demonstrated that the proposed SPS can indeed prevent blackouts from occurring in the Kinmen power system. The design, implementation, and operation of the SPS dealt with in this paper might foster further deployments of other SPSs. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of how to regulate the collective charging load of a large fleet of plug-in electric taxies (PETs) in a metropolis from the viewpoint of utility company. Because the charging load of PET is much higher and less predictable compared with common private electric vehicle, the unregulated charging load of PET fleet can potentially bring large and unpredictable peaks to the distribution system and cause severe damage. To address this problem, this paper proposes a real-time pricing mechanism that can successfully regulate the collective charging load to track a given load profile. The mechanism design consists of three steps. First, we propose two aggregated models for PET fleet to characterize, separately, the relationship between charging decisions of the fleet and real time prices, and the relationship between energy dynamics and charging decisions of the fleet. Then, an optimization problem is designed to calculate the optimal charging load profile that can be accomplished by the fleet. Finally, an efficient online method is launched to calculate proper real time prices, such that the collective charging load of fleet can track the desired value as the response to the prices. Simulation results validate the effectiveness of the proposed mechanism. [ABSTRACT FROM PUBLISHER]

Distributed generation (DG) technology arises in several applications of power supply to tackle the issues of increasing energy demands. The concept of microgrids is introduced to integrate the DG technology into utility power networks. This paper introduces a fuzzy control scheme for networked systems utilizing a quantized H∞ estimator over communication networks for DGs subject random constraints. The developed estimation algorithm is worthy for ensuring the network stability and enduring any sort of quantization, time delay, and packet drops. In these senses, adequate conditions have been mainly derived by means of linear matrix inequalities. An illustrative examples are demonstrated to confirm the effectiveness of the meant design procedure. [ABSTRACT FROM AUTHOR]

In power systems, an asset class is a group of power equipment that has the same function and shares similar electrical and/or mechanical characteristics. Predicting failures for different asset classes is critical for electric utilities toward developing cost-effective asset management strategies. Previously, physical age based Weibull distribution has been widely used for failure prediction. However, this mathematical model cannot incorporate asset condition data. As a result, the prediction cannot be very specific and accurate for individual assets. To solve this important problem, this paper proposes a novel and comprehensive data-driven approach based on asset condition data: K-means clustering as an unsupervised learning method is used to analyze the inner structure of historical asset condition data and produce the asset conditional ages; logistic regression as a supervised learning method takes in both asset physical ages and conditional ages to classify and predict asset operation statuses. Furthermore, an index called average aging rate is defined to quantify, track, and estimate the relationship between asset physical age and conditional age. This approach was applied to a medium-voltage cable class in an urban distribution system in West Canada. Case studies and comparison with standard Weibull distribution are provided. The proposed approach demonstrates higher accuracy measured by F1-Score than Weibull distribution method for asset class failure prediction. [ABSTRACT FROM AUTHOR]

The online condition assessment of circuit breakers (CBs) has been increasingly requested by power utilities in recent years. Trip and close coil current (CC) signature is an effective and noninvasive parameter in CB online condition monitoring. This paper gives an insight into the impacts of the various failures on the coil current waveform, as well as on the CB operation time. The failures and their causes are categorized based on the outcome of these investigations. Finally, a new algorithm using trip/close CC is proposed to detect the mode and cause of CB incipient failures. In this study, the CC patterns are acquired by measurements carried out on (healthy and faulty) CBs of 72.5-kV and 24-kV rating voltages, having SF6 insulation medium, and are equipped with a spring-drive mechanism. [ABSTRACT FROM PUBLISHER]

Residual demand curves (RDCs) can be used to represent the strategic interaction of participants in electricity markets. RDCs relate the energy that an agent can buy or sell in one hour with the clearing market price that would be obtained in such hour, assuming the market is organized as simple bid independent auctions. Despite the fact that they have been widely used in the literature, the existence of time and/or spatial constraints in the market clearing algorithm makes the RDCs not directly applicable. This paper tries to overcome these difficulties by extending the concept of RDCs to zonal pricing markets where complex offering conditions and transmission constraints are taken into account. Therefore, the RDCs are redefined in order to capture such effects, which are usually neglected or oversimplified. A new method for computing the redefined RDCs is established and its application to the Iberian electricity market is presented. The results show that modeling complex conditions and transmission constraints in RDCs can have a significant effect when compared to the standard approach found in the literature. Therefore, the method presented in this paper modeling the effect of firm's decisions on market prices in a more accurate way. [ABSTRACT FROM AUTHOR]

A novel model for the clearing of European day-ahead electricity markets, with all associated types of orders, namely simple hourly orders, block orders, complex orders and PUN (“Prezzo Unico Nazionale”) orders is presented in this paper. An iterative algorithm is employed for the market clearing, bearing an inner iteration process for the handling of Paradoxically Accepted block and MIC orders, and an outer iteration process for the handling of PUN orders. During the iterative process a Master Problem and a PUN subproblem are sequentially solved and coordinated, for the efficient handling of all order clearing conditions and market and/or system constraints. The clearing conditions of each order type are explicitly incorporated in the PUN subproblem, formulating a Mixed Complementarity Problem bearing both primal and dual decision variables. The PUN subproblem concerns the sequential clearing of 24 hourly subproblems, employing a special technique for handling the possible inefficiencies due to the myopic nature of the hourly subproblem solutions, leading to enhanced behavior in terms of social surplus with respect to the state-of-the-art day-ahead market clearing solver. The model and the algorithmic process are evaluated in a west-European test case, demonstrating minimal computational requirements and proving its excellent escalation capabilities. [ABSTRACT FROM AUTHOR]

The first of this two-paper series addresses a practical day-ahead auction model, where generation revenue constraints are explicitly incorporated in the problem formulation, as routinely done in several national electricity markets across Europe. The revenue-constrained market-clearing procedure includes the effect of the transmission network, inter-temporal constraints associated with generation scheduling, demand-side bidding, and marginal pricing. This auction design is an instance of price-based market clearing which features two major complicating factors. First, locational marginal prices become decision variables of the optimization process. In addition, producer revenues are formulated as bilinear and highly nonconvex products of power outputs and market-clearing prices. The resulting problem is formulated as a mixed-integer nonlinear bilevel program with bilinear terms for which available solution techniques rely on heuristics, approximations, or modeling simplifications. This paper presents a novel and exact methodology whereby the original problem is recast as an equivalent single-level mixed-integer linear program. As a consequence, finite convergence to optimality is guaranteed and the use of standard commercial software is allowed. The proposed transformation is based on duality theory of linear programming, Karush-Kuhn-Tucker optimality conditions, and integer algebra results. In the second part of this two-paper series, numerical results from several case studies illustrate the effective performance of the proposed solution approach. [ABSTRACT FROM AUTHOR]