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This paper describes a non-classical logic course primarily indicated for graduate students in electrical engineering and energy engineering. The content of this course is based on the vision that it is not enough for a student to indefinitely accumulate knowledge; it is necessary to explore all the occasions to update, deepen, and enrich that knowledge, adapting it to a complex world. Therefore, this course is not tied to theoretical formalities and tries at each moment to provide a practical view of the non-classical logic. In the real world, the inconsistencies are important and cannot be ignored because contradictory information brings relevant facts, sometimes modifying the entire result of the analysis. As consequence, the non-classical logics, such as annotated paraconsistent logic – APL, are efficiently framed in the approach of complex situations of the real world. In APL, the concepts of unknown, partial, ambiguous, and inconsistent knowledge are referred not to trivialise any system in analysis. This course presents theoretical and applicable aspects of APL, which are successfully used in decision-making structures. The course is divided into modules: Basic, 2vAPL, 3vAPL, 4vAPL, and Final Project. [ABSTRACT FROM PUBLISHER]

This work presents an investigation on the influence of rotor position on the Frequency Response Analysis (FRA) of electric machines. Different types of machines have been analyzed. Contrary to common belief, not only the salient-pole machine suffered from rotor position influence on the FRA. This can have severe impact on the repeatability of the tests and, consequently, their ability to identify early damage in the insulation system of the machine. This paper is intended to warn practitioners of FRA that care should be taken while analyzing the results, in order to avoid false positives in their measurements. Recommendations are made aiming to avoid the influence of rotor position on the results. Also, the use of statistical techniques is proposed, in order to improve the diagnosis, even when there is some lack of repeatability. [ABSTRACT FROM AUTHOR]

This paper describes a model for power distribution grid simulation with distributed generation, designed to be a simulation environment of two proposed elements: (1) an algorithm to reconfigure the circuit topology to enable a microgrid during an outage of power supply, and (2) a specific limiter to allow safe operation of distributed generation in the network. Moreover, an interface of the simulation model with a SCADA was designed to suggest possible operational screens for both: the generator and the utility. The simulation model was designed with a synchronous generator with all cogeneration typical controls: speed, active power, voltage, reactive power and power factor. Thus, it is possible to simulate critical situations with all control modes available in a typical cogeneration plant in addition to the proposed limiter. Due to the immense number of possible combinations of circuit breakers in the grid, the proposed algorithm is based on genetic algorithms to enable a fast enough autonomous reconfiguration to avoid the outage perception by the customer. [ABSTRACT FROM AUTHOR]

This paper presents an innovative concept for the online application of Frequency Response Analysis (FRA). FRA is a well known technique that is applied to detect damage in electric machinery. As an offline technique, the machine under testing has to be removed from service—which may cause loss of production. Experimental adaptations of FRA to online operation are usually based on the use of passive high pass coupling—which, ideally, should provide attenuation to the grid voltage, and at the same time, allow the high frequency FRA signals to be injected at the machine. In practice, however, the passive coupling results in a trade-off between the required attenuation and the useful area obtained at the FRA spectra. This paper proposes the use of an active coupling system, based on power electronics, in order to cancel the grid voltage at the terminals of FRA equipment and allow its safe connection to an energized machine. The paper presents the basic concepts of FRA and the issue of online measurements. It also presents basic concepts about power electronics converters and the operating principles of the Modular Multilevel Converter, which enables the generation of an output voltage with low THD, which is important for tracking the grid voltage with minimum error. [ABSTRACT FROM AUTHOR]

This paper presents a particle swarm optimization (PSO) as a tool for loss reduction study. This issue can be formulated as a nonlinear optimization problem. The proposed application consists of using a developed optimal power flow based on loss minimization function by expanding the original PSO. The study is carried out in two steps. First, by using the tangent vector technique, the critical area of the power system is identified under the point of view of voltage instability. Second, once this area is identified, the PSO technique calculates the amount of shunt reactive power compensation that takes place in each bus. The proposed approach has been examined and tested with promising numerical results using the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

This work presents an innovative application of Frequency Response Analysis (FRA) in order to detect early degradation of Metal Oxide Surge Arresters (MOSAs). This technique has been widely used in power transformers, but has never been applied to MOSAs. It consists in comparisons of spectra, measured at different instants of the lifetime of the arrester. Differences between these spectra are an indicator that some electrical properties of the arrester have changed. An incremental deterioration test has been performed on arrester samples (with controlled circulation of leakage current, which increases the energy dissipation over the device), and the FRA spectra correctly identified the progression of damage. Although preliminary, the FRA results seemed promising, and it is expected that this technology could be used as another diagnostic tool for arresters. [ABSTRACT FROM AUTHOR]

The application of power electronics equipment in medium voltage (MV) distribution grids can provide new management solutions for power flow control, load balancing and voltage problems. A series MV VSC-based power flow controller has recently been presented to interconnect two radial distribution feeders performing active and reactive power transfers to improve the flexibility and utilization of these circuits in a controlled and secure way. Although not previously explored, this power flow controller can integrate the functionality of a series power filter, accomplishing independent control of the fundamental power flow while isolating the harmonic content between the two interconnected feeders. This prevents harmonic pollution from one feeder from propagating to the other, improving the voltage quality. To implement the harmonic isolation, several control strategies can be used. Therefore, this paper provides a comparative analysis between two of the main harmonic control techniques found in the literature: the Synchronous Reference Frame (SRF) controller and the Proportional Resonant (PR) controller. Assessments are conducted both through simulations and experimental results in a meshed network at 13.8 kV with different types of non-linear loads. In the simulation cases, both algorithms showed similar results; however, in the experimental cases, the PR-based solution exhibited better performance in isolating the harmonics from one feeder to the other. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) energy markets constitute a promising approach for locally coordinating the increasing amount of distributed energy resources (DERs) in the distribution system. Although the benefits of P2P markets for the prosumers are already well understood, their impact on utilities is not well discussed nor well understood. This hinders the development of regulatory frameworks, which are still needed to allow for the widespread adoption of decentralized energy markets in any interested country. So far, research has been conducted in specific isolated aspects, making it difficult to understand the overall implications for utilities. The present study aims to tackle this research gap by comprehensively evaluating P2P markets' effects, considering utilities as primary stakeholders. A qualitative roadmap with the overall benefits and challenges of adopting P2P by utilities is outlined to reach this purpose. Technical and economic criteria are assigned for comparing a P2P market to the current regulatory framework. Each criterion is evaluated in a co-simulation platform connecting a market model to a power flow model. Market performance is assessed by revenue analysis, and grid operation indicators evaluate grid performance. Furthermore, network fees are introduced as compensation mechanisms for the net revenue loss. Comparison scenarios encompass network fees and the number of agents, PV, and storage penetration. Results demonstrate that there is no possible benefit for both utilities and prosumers simultaneously if looking exclusively at the financial balance of the market. An equilibrium in benefits for all stakeholders is achievable if non-financial metrics are considered in an integrated market and fee structure analysis. Moreover, results demonstrate that the design of market structures must be sensitive to network configurations and DER penetration changes. This study contributes toward comprehending how the utilities could embrace P2P markets as a feasible solution for grid coordination challenges, opening a new set of questions for further research. [ABSTRACT FROM AUTHOR]

This study presents a new Model Predictive Controller (MPC), built with algorithms based on Paraconsistent Annotated Logic (PAL), with application examples in the excitation control of a synchronous generator. PAL is a non-classical evidential and propositional logic that is associated with a Hasse lattice, and which presents the property of accepting the contradiction in its foundations. In this research, the algorithm was constructed with a version of the PAL that works with two information signals in the degrees of evidence format and, therefore, is called Paraconsistent Annotated Logic with annotation of two values (PAL2v). For the validation of the algorithmic structure, the computational tool MATLAB® Release 2012b, The MathWorks, Inc., Natick, MA, United States was used. Simulations were performed which compared the results obtained with PPC-PAL2v to those obtained in essays with the AVR (Automatic Voltage Regulator) controls in conjunction with the PSS (Power System Stabilizer) and the conventional MPC of fixed weights. The comparative results showed the PPC-PAL2v to display superior performance in the action of the excitation control of the synchronous generator, with a great efficiency in response to small signals. [ABSTRACT FROM AUTHOR]

Synchronized phasor measurement systems are being widely used around the world and have become essential elements in the evolution of the operation of large electrical power systems (EPS). These systems, called Phasor Measurement Units (PMUs), are capable of recording and communicating dynamic data from the EPSs in a synchronized way by GPS and with a high sampling rate, generate a huge set of data that, among many applications, has the capacity to detect events. In this way, this work presents a data management system architecture applied to a real PMU system located in the state of Paraná, Brazil that detects and storages events using principal component analysis and Pearson correlation. This method can detect and store electrical events that occurred during the operation of the national interconnected system of Brazil with good results. [ABSTRACT FROM AUTHOR]

This work proposes a new statistical index, based on hypothesis tests, to be used on frequency response analysis (FRA) of electric machines. This index is, particularly, interesting on the detection of early failures (which appear as small deviations from the baseline spectrum), even when the measurements have high variability (such as the case of online measurements in rotating machines). The majority of the indexes proposed so far in the FRA literature only compares two spectra at a time and mix data from the measurements at different frequencies. The index proposed in this paper calculates one hypothesis test for each frequency (in order to assure randomness, independence and normality) in the spectra of several measurements (in order to take into account the variability on the measurements) and performs the normalized sum of the individual tests. Experimental results are presented on a synchronous generator (both offline and online) to validate the proposed index. [ABSTRACT FROM AUTHOR]

This work presents an application of Frequency Response Analysis (FRA) on the detection of insulation failures on electric generators. An equipment for FRA of electric machines has been developed and its online connection to an induction generator through a C–L–C T-type coupling is presented. It is shown that the coupling circuit implies in a design trade-off between the attenuation of the power signal at fundamental frequency (which may damage the electronics of the analyzer) and the useful area obtained in the FRA spectra. It is shown that a C–L–C coupling greatly improves the performance of a regular capacitive coupling, improving its attenuation at fundamental frequency while maintaining similar frequency response at high frequencies. Experimental results are presented to validate the proposed equipment. [ABSTRACT FROM AUTHOR]

This work presents some guidelines in order to achieve a more reliable diagnosis using the frequency response analysis (FRA) technique. Conventionally, this technique relies on comparisons between spectra obtained at different stages of the machine lifespan. A difference between the spectra may indicate the onset of a failure. However, these comparisons are very subjective to the experience of the analyst. To achieve a more objective diagnosis, statistical indexes have been introduced in the literature of FRA. This work presents a survey on these indexes and also compares them using experimental data. Another contribution of this work is the proposition of a trend based diagnostics. Thus, even if the FRA measurements are obtained at different temperatures/humidity or other external factors, the trend curve of the indexes is able to provide a more reliable diagnosis. [ABSTRACT FROM AUTHOR]

Thermoelectric plants are one of the main forms of energy generation in the world, being the second main source of generation in Brazil. However, with rising fuel costs and greater concern for the environment, controlling the efficiency levels of these plants has become critical. This work presents a system to identify failures and evaluate the efficiency of internal combustion engines used in thermal power plants. To assess efficiency, the developed system monitors subsystem losses (such as cooling, lubrication, turbocharger, etc.). In addition, sensors for cylinder pressure and instantaneous speed were installed and comprise an online monitoring system for the pressure condition of each cylinder of the engines. All this is combined into a supervisory system that presents the Sankey diagram of the engine as its main information online and remotely. To validate the system, experiments were carried out in a controlled configuration (where faults were purposely inserted) and in a Brazilian thermal power plant. The results show that by using in-cylinder pressure and the WOIS database, it was possible to detect the presence of a fault as well as pinpoint its location. [ABSTRACT FROM AUTHOR]

This study presents an application for a series VSC (voltage source converter) in distribution grids for power flow management. Series devices have been widely studied for FACTS (flexible AC transmission systems), however, more recently these devices have gained increased interest in applications for loading balance in medium voltage distribution grids. As the number of distributed generation (DG) units increases, increasing the capacity and reliability of distribution grids while maximizing the benefits of installed DGs and loading behavior is an ever more important task. In this paper, we describe a test system and control proposals for a practical application of series converters interconnecting two distribution feeders at 13.8 kV under load variation disturbances. This approach provides solutions when installed at the end of distribution lines by interconnecting two feeders, resulting in capacity increases in the feeders without needing grid reconfigurations using a small-rated series VSC. [ABSTRACT FROM AUTHOR]

The importance of power in society is indisputable. Virtually all economic activities depend on electricity. The electric power systems are complex, and move studies in different areas are motivated to make them more efficient and solve their operational problems. The smart grids emerged from this approach and aimed to improve the current systems and integrate electric power using alternative and renewable sources. Restoration techniques of these networks are being developed to reduce the impacts caused by the usual power supply interruptions due to failures in the distribution networks. This paper presents the development and evaluation of the performance of a multi-objective version of the Bacterial Foraging Optimization Algorithm for finding the minor handling switches that maximize the number of buses served, keeping the configuration radial system and within the limits of current in the conductors and bus voltage. An electrical system model was created, and routines were implemented for the network verification, which was used as a function of the Multi-Objective Bacterial Foraging Optimization Hybrid Algorithm. The proposed method has been applied in two distribution systems with 70 buses and 201 buses, respectively, and the algorithm's effectiveness to solve the restoration problem is discussed. [ABSTRACT FROM AUTHOR]

The wood industry is an essential part of the economy of some regions in Brazil. Although the excess of wood residue is an environmental concern, it is also an alternative source for electricity generation. This allows for compliance with current legislation to minimize environmental impacts such as strategies to control the emission of pollutants and the decarbonization in the wood exploration activity. Despite this, the thermoelectric plants based on wood residues face problems associated with the low efficiency in generation due to the high moisture content of the residues, and challenges related to transport and storage. In this sense, this work is to evaluate the application of a self-sustainable briquetting plant as an alternative for solving the problems associated with the high moisture content, transport, and storage of wood residues. The aspects related to the construction of the briquetting plant and economic indicators associated with the economic feasibility, such as, the estimation of the net present value over the project lifecycle, internal rate of return and pay-back period, are also presented and discussed. The results demonstrated the feasibility of the plant mainly due to the better energy/volume ratio of the briquette (drying and compaction) and the transportation cost savings associated to the density of the compacted material. [ABSTRACT FROM AUTHOR]

Examines the proposed linguistic (qualitative) modeling approach which is presented in a fuzzy-neural network (FNN) form. What the approach combines; Reference to the learning algorithm of an FNN being composed of three phases; Information on these phases.

Optimal scheduling is a requirement for microgrids to participate in current and future energy markets. Although the number of research articles on this subject is on the rise, there is a shortage of papers containing detailed mathematical modeling of the distributed energy resources available in a microgrid. To address this gap, this paper presents in detail how to mathematically model resources such as battery energy storage systems, solar generation systems, directly controllable loads, load shedding, scheduled intentional islanding, and generation curtailment in the microgrid optimal scheduling problem. The proposed modeling also includes a methodology to determine the availability cost of battery and solar systems assets. Simulations were carried out considering energy prices from an actual time-of-use tariff, costs based on real market data, and scenarios with scheduled islanding. Simulation results provide support to validate the proposed model. Data illustrate how energy arbitrage can reduce microgrid costs in a time-of-use tariff. Results also show how the microgrid's self-sufficiency and the storage system's capacity can impact the microgrid's energy bill. The findings also bring out the need to consider the scheduled islanding event in the day-ahead optimization for microgrids. [ABSTRACT FROM AUTHOR]

Recent developments, such as smart metering, distributed energy resources, microgrids, and energy storage, have led to an exponential increase in system complexity and have emphasized the need to include customer behavior and social and cultural backgrounds in planning activities. This paper analyzes how emergent behavior in electricity consumption can affect the planning of distribution grids with a smart grid vision. For this, an agent-based model that uses insights from the field of behavioral economics to differentiate four consumer categories (high income, low income, middle class, and early adopters) was used. The model was coupled with a real distribution feeder and customer load curve data, and the results showed that heterogeneity of customer's preferences, values, and behavior led to very distinct load growth patterns. The results emphasize the relevance of modeling customer's behavioral aspects in planning increasingly complex power systems. [ABSTRACT FROM AUTHOR]

This paper presents the development of a peak-shaving equipment, composed by a multilevel converter in a cascaded H-bridge topology and battery banks on the DC links. Between specific time periods, when the demand is higher, the equipment injects active power from the batteries into the grid to provide support to the system. During the other times of the day, when the demand is lower, the converter charges its battery banks with the exceeding (and low producing cost) energy from the grid. The charge and discharge control algorithms are implemented in a digital signal processor (DSP). The precise time of the day information is obtained from a real-time-clock from a global positioning system module (GPS), which communicates with the DSP through the serial interface. This paper presents the control algorithms and experimental results obtained in a 24 h continuous operation of the equipment. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for a high-resolution urban spatial load demand forecasting. This methodology is meant to improve the visualization, analysis and inference of load density information in the electric distribution systems in the near future. The proposed methodology converts input data into grid maps and then divides the grid map into larger regions, which will have their expected growth according to convolution matrices and weighting factors that search for characteristics in the history of this region. The definition of the characteristics of the region's growth is obtained by processing the imperialist competitive algorithm that searches the best array of convolution, which will set the expected growth of the region. Thus, it is possible to obtain a spatial growth forecast of high resolution and with great precision, which are important factors for smart-grid planning. [ABSTRACT FROM AUTHOR]

Induction motors consume a great portion of the generated electrical energy. Moreover, most of them work at underloaded conditions, so they have low efficiencies and waste a lot of energy. Because of this, the efficiency estimation of in-service induction motors is a matter of great importance. This efficiency estimation is usually performed through indirect methods, which do not require invasive measurements of torque or speed. One of these methods is the modified Air-Gap Torque (AGT) method, which only requires voltage and current data, the stator resistance value, and the mechanical losses. This paper approaches the computation of a modified stator resistance including the mechanical losses effect to be applied in the AGT method for torque and efficiency estimation of induction motors. Some improvements are proposed in the computation of this resistance by using a direct method, as well as the possibility to estimate this parameter directly from the nameplate data of the induction motor. The proposed methodology only relies on line voltages, currents, and nameplate data and is not intrusive. The proposed methodology is analyzed through simulation and validated through experimental results with three-phase induction motors. Also, a comparison of methods for in-service induction motors efficiency estimation is presented for the tested motors. [ABSTRACT FROM AUTHOR]

This paper applies finite control set model predictive control (FCS-MPC) for dynamic reactive power compensation using a hybrid active power filter (HAPF). The FCS-MPC uses a model based on LCL-filter equations to predict the system behavior and optimize the control action. In fact, the application of FCS-MPC in grid-connected converters with LCL-Filter is quite recent. This algorithm is a very promising control technique for power electronics converters and its use for reactive power control of hybrid filter has not been reported in the literature yet. This paper uses the FCS-MPC in a multivariable structure along with an adaptive notch filter to damp resonance. The main purpose is to improve the dynamic response of the HAPF. Simulation as well as practical results prove the feasibility of FCS-MPC application in HAPF reactive power control. The dynamic response of the equipment was significantly improved and represents the main contribution of this paper. As a result, the FCS-MPC allows tracking fluctuations and abrupt changes in load reactive power. [ABSTRACT FROM PUBLISHER]

This article presents a novel methodology for the determination of synchronous machine parameters from the sudden short-circuit (SCC) test. Records of armature and field currents transient behavior are used to evaluate thed-axis equivalent circuit, including the rotor characteristic reactance, and the traditional synchronous machine parameters. The method is based on the evolutionary computer algorithm, the hybrid particle swarm optimization (HPSO). The developed program has been successfully applied into two large salient pole synchronous machines test data. [ABSTRACT FROM PUBLISHER]

Consumer behavior is complex and is difficult to represent in traditional economic theories of decision-making. This paper focuses on the development of an agent-based approach to analyze people's behavior in consuming electricity using a behavioral economics framework, where the consumer is the main agent of power systems. This approach may bring useful insights for distribution companies and regulatory agencies, helping to shift thinking to amore user-centric approach. The emergent properties of electricity consumption are modeled by the means of consumer's heuristics, taking into account the electricity price, consumer's satisfaction level, willingness to invest in new technologies, social interactions, and marketing strategies by the power utility. Analysis on the emergent behavior of this approach through simulation studies showed that it is indeed valuable, as does not require in-depth data of all details on human behavior. However, it contributes to the understanding of relations among various objects involved in electricity consumption. [ABSTRACT FROM AUTHOR]

Electrical signature analysis (ESA) has been successfully applied to predictive maintenance of synchronous machines. The fault diagnosis is performed by analyzing failure patterns in the current or voltage spectra, which allow the discrimination of a healthy and a faulty condition on the monitored machine. Generally, the failure patterns are a function of the line frequency, rotor rotation frequency, and some structure features of the machine. The rotor rotation frequency pattern, for instance, is indicative of rotor mechanical problems and rotor winding interturn short-circuit. An increase of this frequency component magnitude may indicate the incipience of a rotor fault but may not discriminate the nature of the fault (electrical or mechanical). Thus, it is necessary to distinguish the effects of electrical and mechanical faults in these components in order to get a reliable diagnosis of the machine. No works have been found in the literature approaching this specific issue. This paper proposes a simple and innovative methodology to distinguish the effect of electrical and mechanical faults in the mentioned ESA failure patterns based on the method of symmetrical components. Its effectiveness is validated by experiments performed on a synchronous generator test rig. The proposed condition monitoring system is simple, low cost, and low intrusive, as it only relies on stator electrical quantities. Moreover, it is in operation in a Brazilian 404-MW thermal power station. [ABSTRACT FROM PUBLISHER]

Rolling element bearings are machinery elements that are widely used in aerospace and industrial applications to support rotating shafts, thereby reducing mechanical friction and heating. However, these components are subject to several kinds of faults which, in general, can be divided into single-point or localized and distributed faults. A common way to detect ball bearing localized or raceway faults is by identifying and analyzing the so-called characteristic “bearing frequencies.” This article presents an approach to bearing condition-based maintenance which comprises fault detection and identification and condition prognosis, based on spectral kurtosis and squared envelope spectral analysis of stator current. In this work, envelope spectrum analysis, based on spectral kurtosis, is applied to identify these frequencies and to evaluate its applicability as a severity estimation index. To evaluate the performance of this index, experimental tests were carried out considering bearings with outer raceway defects at different stages, simulating different fault severities. The numerical results confirm the applicability of the described methodology for detecting and identifying faults, as well as estimating the generated fault severity levels, suggesting that the proposed fault severity index can be applied for bearing monitoring in real world industrial applications. [ABSTRACT FROM AUTHOR]

This paper presents an air-gap torque (AGT)-based method for efficiency estimation of induction motors. A new concept of stator resistance that includes the mechanical losses effect is proposed. This new stator resistance is estimated through a particle swarm optimization approach based on the stator flux equations and minimization of torque error at the rated operation point. Then, the obtained stator resistance is used in the AGT equations to estimate the shaft torque and then the efficiency. Moreover, the rotor speed is estimated using induction motor current signature analysis. Thus, the proposed methodology for induction motor efficiency estimation relies only on line currents, line voltages, and nameplate data, being appropriate for in-service applications. Finally, the simulation and experimental results are presented to validate the proposed method at different load conditions. [ABSTRACT FROM PUBLISHER]

This article presents the theoretical development and implementation of an adaptive algorithm for real-time measurement of electrical powers under sinusoidal, non-sinusoidal, balanced, and unbalanced conditions according to the definitions given by IEEE Standard 1459-2010. The algorithm is based on adaptive filter notch filter implementation, where the parameters are adjusted by tracking the amplitude and phase variations to improve the accuracy of the power measurement. The algorithm uses the filter coefficients to calculate powers, resulting in low computational burden. The results of computer simulation and practical implementation using a fixed-point digital signal controller are shown in detail, proving the accuracy and efficiency of the algorithm. [ABSTRACT FROM PUBLISHER]

Early detection of faults in electrical machines, particularly in induction motors, has become necessary and critical in reducing costs by avoiding unexpected and unnecessary maintenance and outages in industrial applications. Additionally, most of these faults are due to problems in bearings. Thus, in this paper, experimental bearing fault detection of a three-phase induction motor is performed by analyzing the squared envelope spectrum of the stator current. Spectral kurtosis-based algorithms, namely, the fast kurtogram and the wavelet kurtogram, are also applied to improve the envelope analysis. Experimental tests are performed, considering outer bearing faults at different stages, and the results are promising. [ABSTRACT FROM PUBLISHER]

This paper presents a ultrasonic-capacitive system for online analysis of the quality of fuel oils (FO), which are widely used to produce electric energy in Thermal Power Plants (TPP) due to their elevated heating value. The heating value, in turn, is linked to the quality of the fuel (i.e., the density and the amount of contaminants, such as water). Therefore, the analysis of the quality is of great importance for TPPs, either in order to avoid a decrease in generated power or in order to avoid damage to the TPP equipment. The proposed system is composed of two main strategies: a capacitive system (in order to estimate the water content in the fuel) and an ultrasonic system (in order to estimate the density). The conjunction of the two strategies is used in order to estimate the heating value of the fuel, online, as it passes through the pipeline and is an important tool for the TPP in order to detect counterfeit fuel. In addition, the ultrasonic system allows the estimation of the flow rate through the pipeline, hence estimating the amount of oil transferred and obtaining the total mass transferred as a feature of the system. Experimental results are provided for both sensors installed in a TPP in Brazil. [ABSTRACT FROM AUTHOR]

This paper describes new strategies to improve the transient response time of harmonic detection using adaptive filters applied to shunt active power filters. Two cases are presented and discussed, both using an adaptive notch filter, but one uses the least mean square algorithm to adjust the coefficients and the other uses the recursive least squares algorithm. The synchronization of the adaptive notch filter orthogonal input signals, which are generated by the Clarke transformation of the load currents, is achieved automatically without the need of a phase-locked loop. This procedure significantly reduces the real-time computation burden. Simulations using Matlab/Simulink are presented to clarify the algorithm, and practical implementation is performed using the DSP Texas Instruments TMS320F2812. The experimental results are presented and discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a novel phase-locked loop (PLL) control strategy to synthesize unit vector using the modified synchronous reference frame (MSRF) instead of the traditional synchronous reference frame. The unit vector is used for vector rotation or inverse rotation in vector-controlled three-phase grid-connected converting equipment. The developed MSRF-PLL is fast in transient response compared to standard PLL technique. The performance is robust against disturbances on the grid, voltage wave with harmonic distortion, and noise. The proposed algorithm has been analyzed in detail and was fully implemented digitally using digital signal processor TMS320F2812. The experimental evaluation of the MSRF-PLL in a shunt active power filter confirms its fast dynamic response, noise immunity, and applicability. [ABSTRACT FROM PUBLISHER]

The city of Aripuana is one of the largest wood producer in the state of Mato Grosso, Brazil. Wood residues are used in the electricity generation at three thermoelectric plants in this region. However, the plants have high costs in transporting the wood residues (due to poor road conditions). Hence, this paper compares the energy performance of wood residues in natura and compacted as briquettes by calculating the heating value and determining the influence of moisture content on the energy characteristics of wood residues. The goal is to demonstrate the viability of using briquettes in order to improve thermoelectric generation. The wood residues from this region are affected by the high humidity of the biome. An alternative to improve the use of energy contained in the wood residues is to produce briquettes with lower humidity. This allows one to maintain high levels of heat energy in a lower volume, facilitating handling and storage. The results show that the use of briquettes improved the performance of thermoelectric plants, generating 1 MW of electricity power with less than 1 ton of briquettes. This contributes to the preservation of the environment, reducing operating costs, transportation and storage of the raw materials. [ABSTRACT FROM AUTHOR]

This paper presents the practical aspects of development of a reduced scale laboratory and a set of monitoring tools for Internal Combustion Engines used in Thermal Power Plants. The reduced scale laboratory is based on the necessity of researchers to test new sensors and monitoring strategies that, otherwise, are seldom allowed to be installed in real plants without certification. In addition, the reduced scale laboratory allows the flexibility to insert failures on purpose, in order to evaluate the performance of new sensors/strategies in a safe and controlled environment. The paper also presents the development of a set of reduced cost sensors for monitoring in-cylinder pressure, crank angle, and the position of inlet and exhaust valves (without using ultrasound sensors, which may produce noisy readings on engines operating on gas-diesel fuel mode). [ABSTRACT FROM AUTHOR]

In thermal power plants, the internal combustion engines are constantly subjected to stresses, requiring a continuous monitoring system in order to check their operating conditions. However, most of the time, these monitoring systems only indicate if the monitored parameters are in nonconformity close to the occurrence of a catastrophic failure—they do not allow a predictive analysis of the operating conditions of the machine. In this paper, a statistical model, based on the statistical control process and Nelson Rules, is proposed to analyze the operational conditions of the machine based on the supervisory system data. The statistical model is validated through comparisons with entries of the plant logbook. It is demonstrated that the results obtained with the proposed statistical model match perfectly with the entries of the logbook, showing our model to be a promising tool for making decisions concerning maintenance in the plant. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of increasing the loadability of power systems which, in turn, can be linked to voltage collapse occurrences. As voltage collapses may be caused by insufficiency of reactive power support, and considering that reactive power can be locally supplied, for Stance, by shunt capacitors, this paper addresses the impacts of local control actions on the system loadability. The study is carried out in two steps. First, by using the tangent vector technique, two important areas of the power system are Identified: the critical area under the point of view of voltage collapse, and the area most sensitive to active power losses reduction. Second, once these two areas are Identified, an optimization technique takes place to optimize the amount of shunt reactive power compensation that should be available in each bus. Numerical results are obtained using the IEEE 14- and 118-bus systems. [ABSTRACT FROM AUTHOR]

Motor current signature analysis (MCSA) enables non-invasive monitoring, without interruption of machine operation in a remote and online way, allowing the identification of various types of faults of electrical and mechanical nature without the need of accessing the motor itself, but only its supply cables. Despite its advantages, it has limitations in accurately diagnosing incipient roller bearing faults. For the detection of incipient roller bearing faults, envelope analysis of vibration signals is a well-known and stablished technique used by motor condition monitoring experts for a long time, overcoming MCSA for that purpose. Thus, it is proposed in this paper, that the fault characteristic frequencies of roller bearings are identified in the current spectrum with the aid of envelope analysis on the bearing vibration signal. After this aided identification, the fault related spectral components in the current spectrum can be correctly tracked over time for trending evaluation and decision-making. This approach can represent a significant economic value in a motor condition monitoring program, since vibration envelope analysis is performed only at a first step and, after that, its results can be applied for the MCSA monitoring of all same-model motor drivers in an industrial site. This approach is even more valuable considering the concept of the Self-Supplied Wireless Current Transducer (SSWCT) also proposed in this paper. The SSWCT is an Industrial Internet of Things (IIOT) device for MCSA application in an Industry 4.0 environment. This proposed device has wireless communication interface and wireless/battery less power supply, being supplied by the energy harvested from the magnetic field of the same currents it is transducing. So, it is a completely galvanic isolated monitoring device, without batteries and without any electric connections to the industry electric system, easily installable to the motor cables, not using precious space in the electric panels of the motor control centers and not having any physical contact to the monitored asset. [ABSTRACT FROM AUTHOR]

The condition of synchronous generators (SGs) is a matter of great attention, because they can be seen as equipment and also as fundamental elements of power systems. Thus, there is a growing interest in new technologies to improve SG protection and maintenance schemes. In this context, electrical signature analysis (ESA) is a non-invasive technique that has been increasingly applied to the predictive maintenance of rotating electrical machines. However, in general, the works applying ESA to SGs are focused on isolated machines. Thus, this paper presents a study on the condition monitoring of SGs in bulk electric systems by using ESA. The main contribution of this work is the practical results of ESA for fault detection in in-service SGs interconnected to a power system. Two types of faults were detected in an SG at a Brazilian hydroelectric power plant by using ESA, including stator electrical unbalance and mechanical misalignment. This paper also addresses peculiarities in the ESA of wound rotor SGs, including recommendations for signal analysis, how to discriminate rotor faults on fault patterns, and the particularities of two-pole SGs. [ABSTRACT FROM AUTHOR]

Summary: In a demand‐side management (DSM) program, a set of activities are designed to influence electricity consumption in a way that may produce desired changes in the utility's load shape. Detailed analysis when planning DSM programs is crucial because the utility intends to achieve technical and economic benefits but does not wish to lose revenue unnecessarily. To assist utilities in planning for price‐based demand response (DR) programs (an approach to DSM), this paper proposes an optimization system focused on the targeting of residential customers to enroll in a new time‐of‐use tariff. The developed system uses optimal power flow to estimate the reduction needed to achieve the proposed objectives of the DR program in each bus, followed by the selection of the customers that will provide this reduction via binary particle swarm optimization. The optimization system has been tested using real data acquired from a Brazilian utility including customers' load curves, radial distribution feeder data, a time‐of‐use tariff, and estimated elasticity matrices from the literature. The main results show that the system can be of great value supporting power utilities' implementation of price‐based DR programs. [ABSTRACT FROM AUTHOR]