1- Introduction

2- Circuit configuration

3- Theoretical analysis

4- SPICE simulation

5- Experiments

6- Conclusion

References

Abstract

For vibration energy harvesting, we propose an inductor-less step-up ac/dc converter in this paper. To realize the inductor-less design, the proposed ac/dc converter consists of two converter blocks: Cockcroft–Walton circuit and charge pump. Unlike existing ac/dc converters for vibration energy harvesting, the proposed ac/dc converter can achieve less electro-magnetic interference (EMI), because no magnetic component is necessary. Furthermore, owing to the Cockcroft–Walton circuit, a fullbridge circuit is not necessary to convert vibration energy. Therefore, small vibration energy, namely, as 0.3 V@1 MHz, can be converted directly to dc voltage. Through theoretical analysis and simulation program with integrated circuit emphasis (SPICE) simulation, the performance of the proposed converter with 6× voltage gain is investigated, where the proposed converter is designed by assuming 0.18 µm CMOS process. The proposed converter demonstrates that about 62% power efficiency can be provided, where the output power is 30 µW, the output voltage is about 1.6 V, and the ripple factor is 0.8%. Furthermore, the feasibility of the proposed ac/dc converter is confirmed by breadboard experiments. The inductor-less design provides us to integrate the proposed ac/dc converter into a hybrid IC chip.

Introduction

Over the past few decades, wireless sensor network (WSN) systems [1] are receiving much attention for monitoring various environment parameters. The bottleneck of the WSN systems is the limited lifetime of WSN nodes, because the WSN nodes are usually driven by a battery source. For this reason, in order to extend lifetime of WSN nodes, some of wasted energy are captured by energy harvesting collectors and are used as a power supply source in recent years. There are several types of ambient energy sources, such as solar, wind, vibration, thermoelectric. Among others, we focused on vibration energy, which is a kind of kinetic energy, because it widely exists in the ambient, including the vibration of industrial machinery, transportation vibration, body movement, and so on. In the energy harvesting collectors, the ambient energy is converted into electrical energy by power converters. To utilize vibration energy, an ac/dc converter is necessary as a vital component of energy harvesting collectors. For this reason, several types of ac/dc converters have been proposed in recent years. For example, Shi et al. [2] suggested the ac/dc converter by combining a full-bridge circuit with two buck-boost converters. Wang et al. [3] designed the ac/dc converter by combining a full-bridge circuit with a synchronized switching harvesting on inductor. Shareef et al. [4] realized the ac/dc converter without full-bridge circuits. However, due to the magnetic component, such as inductors, these existing converters becomes bulky. Furthermore, these converters are applied only for low frequency ac input. To solve these problems, we undertake the development of an inductor-less ac/dc converter for vibration energy harvesting.

1- Introduction

2- Set-up description

3- Verification of the PD measuring system

4- PD measurements

5- Improved PD measurements

6- Conclusions

References

Abstract

A partial discharge (PD) measuring system has been deployed in order to identify and measure PD in a high voltage (HV) cable joint under impulse and superimposed voltages under laboratory conditions. The challenge is to enable the detection of PD during the impulse conditions. The method of measurement has been investigated by introducing an artificial defect in the cable joint in a controlled way to create conditions for partial discharges to occur. Next the HV cable system is subjected to AC, impulse and superimposed voltage. Two high frequency current transformers (HFCT) installed at both ends of the cable joint were used to identify PD from the cable joint and to separate PD from disturbance. Transient voltage suppressors and spark gaps are applied to protect the measuring equipment. Band pass filters with selected characteristics are applied to suppress transient disturbances and increase the chance to detect PD during the impulse. PD signals are separated from transient disturbances during data post processing and by means of pulse polarity analysis. The developed system enables the detection of so-called main and reverse discharges respectively occurring during the rise and tail time of the superimposed impulse. The measurement results obtained show the effectiveness of the presented PD measuring system for investigating the effects of voltage transients on a HV cable system in laboratory conditions.

Introduction

Partial discharge measurements provide a useful tool to obtain information about discharging defects in high-voltage equipment. In power cables, PD occurs at insulation defects in particular in cable joints and terminations, especially at interfaces [1]. Therefore, PD measurement on cable systems can be considered a useful tool to diagnose insulation condition for both laboratory application and on-site application [2–4]. PD in power cables is normally measured under AC voltage by using the conventional technique defined by IEC 60270 [5]. In practice, power cables are not only subjected to AC operating voltage, but also to transient voltages such as lightning and switching impulses, which occasionally will be superimposed on the normal AC voltage. Those transient voltages will have an additional stress on the cable insulation. In that regard it is important to investigate PD under impulse and superimposed voltages. One of the challenges in measuring PD under impulse and superimposed voltages concerns the suppression of the disturbances caused by the transient voltages. In laboratory tests, the applied impulse voltage causes currents in the cable under test that disturb the PD measurement. So the PD measurement system needs to have a strong suppression of the disturbance. In such a case, the conventional PD technique is not suitable anymore. The unconventional method based on the measurements of electrical signals in MHz range is of more interest as a better alternative for these conditions [4,6–10]. Three circuits for PD detection under impulse are provided in [11] with a measurement frequency from hundreds of MHz to GHz, namely: the high frequency current transformer (HFCT) with multipole filter, the coupling capacitor with multipole filter, and the electromagnetic couplers. HFCTs or other sensors are commonly used with wide/ultrawide bandwidth together with filters and a digital oscilloscope to detect PD in insulation specimens or models under impulses [12–17]. A coupling capacitor was used to measure PD in material samples in cases where only impulse [18] and square wave voltage were applied [5]. Those PD measuring systems were able to detect PD during the impulse even during its front time. For superimposed impulses, PD was detected in laminated paper using a current transformer and a high-pass filter by Hayakawa et al. [19]. Nikjoo et al. [20] used a wideband detection system consisting of a coupling capacitor, a detection impedance and a low-pass filter to measure PD in oil-impregnated paper. However, in both works, PD was measured during AC cycles before and after impulses instead of during the impulses. Moreover, PD measurements in the above-mentioned works were performed on material specimens.

1- Introduction

2- An analytical electromagnetic model of the “Sen” transformer

3- Simulation case studies

4- Conclusions

References

Abstract

In flexible AC transmission systems, the “Sen” transformer (ST) is an economical and effective method for voltage regulation and power flow control, which can achieve independent control of active and reactive power. The ST is a three-phase multi-winding transformer based on the on-load tap-changing technology. In order to reveal the internal characteristics of the ST, this paper proposes an analytical electromagnetic model considering the multi-winding coupling in the ST with the three-phase three-limb structure. Firstly, according to the electromagnetic coupling relationship in the ST, a magnetic equivalent circuit model consisting of self-inductance coefficients and mutual inductance is derived via the unified magnetic equivalent circuit (UMEC). Secondly, an electric circuit model for the internal voltage and current of the ST is established based on the electrical connection between the ST and the external system. Finally, an analytical electromagnetic model considering multi-winding coupling for the ST is obtained by combining the magnetic equivalent circuit model and the electric circuit model. Two case studies have been carried out on a three-phase three-limb model of the ST with the help of MATLAB. The effectiveness of the proposed model is verified by comparing the obtained analytic results with the existing results from time-domain simulation about the series compensating voltage of the ST. In addition, the voltages and currents of windings in the ST in the conditions of different transformer core structures and ferromagnetic materials are investigated for evaluating the influence of magnetic coupling on the results.

Introduction

With the large-scale integration of renewable energy sources, it has been becoming more and more difficult for the voltage regulation and the optimal power flow control in complex power networks with UHV (Ultra High Voltage) transmission lines as the backbones[1,2]. The unified power-flow controller (UPFC) is an important way to solve the problems of voltage regulation and power flow control [3,4]. However, the high installation and operation costs prevent the UPFC from widespread applications. The “Sen” transformer (ST), as proposed in [5], has the ability of controlling active and reactive power flow independently. Compared with UPFC, the ST is lower in cost, higher in reliability and efficiency [6–8], although reducing the accuracy and dynamic performance [9]. The ST is a typical electromagnetic unified power flow controller, and is usually based on a three-phase multiwinding transformer. By changing the position of secondary winding taps, the ST can generate different voltages, achieving the adjustment of power flow. The adjustment performances between the “Sen” transformer and phase angle regulator (PAR) were compared in [10,11]. The results showed that the overall reactive power of the ST was lower than that of the PAR for enhancing the required amount of active power flow. Therefore, the “Sen” transformer is expected to be a device that will have widespread applications in flexible AC transmission systems (FACTS). As a matter of fact, the ST is a technology based on transformers and tap-changers. From the perspective of the development of electrical topologies and structural variants, many researchers have optimized the topology of the ST for the purpose of improving its power flow control performance. For example, some novel topologies of the ST were proposed in [12–15] for the sake of achieving continuous power flow control of existing transmission lines and improving the utilization rate of existing transmission lines. These topologies include the hybrid electromagnetic unified power flow controller (HEUPFC), the improved hybrid unified power flow controller (IHUPFC) and the power transistor-assisted “Sen” transformer (TAST) which consists of a high-capacity ST and a small capacity UPFC.

1- Introduction

2- Problem formulation

3- Proposed models

4- Experimental results

5- Conclusions

References

Abstract

A factor that directly impacts the lifespan of a power transformer is the hot-spot temperature, and its monitoring is vital to prevent faults, reduce costs, keep the safety, and provide a reliable service to consumers. In this paper, we propose two forecasting models to predict the hot-spot temperature of power transformers. The first is the implementation of Set-Membership in the evolving Participatory Learning with Kernel Recursive Least Squares. And the second is a combination of the evolving Participatory Learning with Kernel Recursive Least Squares and the improved version of the Set-Membership concept, named Enhanced Set-Membership. Both Set-Membership and the Enhanced Set-Membership approaches are implemented to update the rate of change of the arousal index, which is a parameter that controls the creation of rules. A data set collected from an experimental transformer is adopted to evaluate the model’s performance. The obtained results are compared with the performance of the original evolving Participatory Learning with Kernel Recursive Least Squares and with the performance of other classical models suggested in the literature. The proposals have lower errors and a competitive number of final rules, suggesting that the models are efficient approaches to modeling complex data with high accuracy.

Introduction

The power transformer is a critical equipment in power distribution [1]. It is responsible for stepped-up the voltage before to be transmitted over long distances to reduce waste, and stepped-down the voltage to provide the energy to consumers safely [2,3]. Due to the composition of a power transformer, it is the most expensive apparatus in energy distribution [4]. In the case of a power transformer’s failure, when the recovering process is possible, it is slow and inefficient [5]. Thereof, monitoring is vital to prevent faults, reduce costs, keep the safety, and provide a reliable service to consumers [6,7]. The annual spent on power transformers’ monitoring hardware will increase more than $ 642 million in eight years until 2020, according to [8,9], indicating the importance of the power transformers in power distribution. Internal failures are about 10% of the total faults, and, among them, winding and bushing defects represent approximately 44% [10]. The bushing is a fragile component constituted of four parts: insulation, conductor, connection clamp, and accessories[11,12]. In the present work, we considered power transformers composed of Resin-bonded paper bushings (RBP) [13]. The principal factor in bushing failures is the hot-spot temperature, representing 32% of the total causes [11]. The hot-spot temperature is the highest temperature near to the top of the power transformers highvoltage (HV)/low-voltage (LV) windings [7,14] and represents the main limiting factor in the load capacity of the transformer [14], since increases in this temperature reduces the lifespan of the insulation and may determine the end life of the power transformer [15]. As the estimation of the hot-spot is a complex task, many models have been proposed in the literature with the purpose of estimating the hot-spot temperature of power transformers. Among them, the most commonly used in practice is the model based on the IEEE Standard C57.91-2011 [16] which is based on transient heating equations and specific thermal characteristics and parameters of power transformers. This deterministic model is imprecise due to assumed simplifications, and consequently, the power transformer must operate below the maximum capacity to prevent damages [7].

1- Introduction

2- System modelling

3- Surge protective device

4- Stochastic analysis

5- Conclusion

References

Abstract

Vacuum circuit breaker operation causes transient overvoltages that may lead to severe damages to transformer insulation. Since the parameters affecting these overvoltages have stochastic nature, a statistical analysis may provide detailed insight into the overvoltages from the point of view of insulation coordination applications. In this paper, a statistical analysis of the overvoltage variations of the step-up transformer during vacuum circuit breaker operation is conducted. Some variables, including switching angle, current chopping, high-frequency current quenching capability, and wind turbine power, are assumed as random variables. Besides, some indicators representing the switching overvoltage characteristics such as the amplitude, the number of restrikes, and the rate of rise are extracted. By performing a probabilistic analysis, the destructiveness due to switching overvoltages on typical transformer insulation can be investigated. The sensitivity of different surge protective devices and their effectivities are also analyzed and statistically evaluated. The applied methodology is very useful because of the stochastic nature of the switching overvoltages. In this work, the impact of protective equipment on each of the overvoltage indicators is analyzed. It is also found that considering only the amplitudes of transient overvoltages is not enough to draw conclusions about the safety of the transformer when exposed to frequent switching surges.

Introduction

VCBs are commonly used in offshore wind farms due to their ability to eliminate high fault currents and their low maintenance costs. Due to wind speed variations, numerous switching actions (energization and de-energization) commonly occur in wind farms every day. VCB switching transients reach the step-up transformer through the short cable connected to the wind turbine. In case, the amplitude of a switching transient voltage rises above the BIL; it can lead to transformer winding failures. Previous statistical studies related to VCB opening were only focused on the amplitude of transient overvoltages regardless of their rise times [1–4] However, some transformer failures due to VCB operations have indicated that the leading cause of the failure was the high du/dt [5]. Recently performed detailed research showed that due to fast transients and during resonance conditions, the voltages with high amplitudes are non-linearly distributed along the windings [6], and the high du/dt accelerates failure mechanisms because of high interturn overvoltages in the transformer windings; causing coil-to-coil failures in the top or in the middle of the winding. Besides, the critical voltage of the transformer BIL remarkably decreases with the reduction of the rise time [7,8] and the amplitude [7] of the transient voltage applied. Moreover, the experimental studies confirm the effects of lightning impulses on oiled paper [9] and very fast transients on cast-resin insulation [10]. Accordingly, the rate of rise and the number of transient surges should be considered alongside their amplitude in a stochastic analysis in order to accurately assess the effects of the switching overvoltages on transformer insulation lifetime. The characteristics of the transient overvoltages occurring due to VCB operation depend on various parameters. The current chopping phenomenon in VCBs being one of the key parameters that contribute to the reignition overvoltages. Experimental tests conducted in Ref. [11] however, showed the low dependency of this parameter on the operation instant.

1- Introduction

2- System architecture

3- Modelling of the WECS

4- Performance analysis of proposed DC nanogrid topology

5- Conclusion

References

Abstract

Wind energy conversion system (WECS) based DC nanogrid topology is proposed in this paper. The WECS topology is based on self-excited induction generator (SEIG) which is cost effective, and has rugged construction and combination of diode bridge rectifier (DBR) with DC-DC converter to implement the maximum power point tracking technique. The combination of diode DBR with DC-DC converter allows simple control structure due to one controllable switch as compared to complex control in the conventional controlled/semi-controlled rectifier with six controllable switches. Further, proposed DC nanogrid topology enhances the SEIG efficiency due to the reduction of harmonic injection on machine side from DBR implementation. The detailed harmonic spectrum analysis is carried out by developing the laboratory scale prototype of DBR based SEIG topology for WECS to justify the selection of DBR instead of the controlled rectifier. Further, to analyze the effect of different types DC-DC converter to make combination with the DBR. Afterwards, the dynamic performance of the proposed DC nanogrid topology is analyzed to understand the selection of the DC-DC converter with DBR for different DC grid voltage conditions.

Introduction

Electricity plays a vital role in energy supply, however, the electricity generation is the single largest source of CO2 emission, which is more than 40% of CO2 emission related to global energy. By the year 2030, global electricity demand is likely to double [1,2]. Hence, climate change mitigation and increasing energy demand motivates for the development of renewable energy resources. The renewable energy resources such as solar and wind energy are distributed in nature which favors the electricity generation and consumption on site. With technological advancement and regulatory changes, the concept of supplying the load locally has led to a concept of nanogrid. Thus, the development of renewable based nanogrid are gaining attention in recent past for providing environment-friendly, sustainable and economical electricity [3]. Further, the development of power electronics has transformed the load profile of end user as the modern appliances operate on DC supply [4]. Having this understanding, the concept of DC nanogrid has been proposed in the literature to elude multiple AC-DC conversion and vice-versa [5]. The DC distribution enables easy control, no issue of frequency, power angle, phase sequence, and power factor. Mashood et al.

1. Introduction

2. Benefit of a thermal criterion in planning

3. Thermal Criterion: Limits in practice

4. Linear thermal criterion

5. Conclusion

Declaration of Competing Interest

Appendix A. Simplification of the thermal model

Appendix B. Linearization

Appendix C. Change of the considered thermal limit

References

Abstract

It has already been shown in the literature that power transformers may be more accurately sized by their thermal limits than by their rated power limit. In practice however, thermal limits are usually considered only in operations; but not at planning stage, where the more usual notion of rated power is used. This paper proposes a novel method to take into account (and benefit from) thermal limits directly at planning stage. This is made possible by quantifying separately the impact of each generator and load on the temperature of the distribution transformer. Decoupling the effect of individual generators and loads is achieved by linearizing and rewriting the analytical expression of the hot-spot transformer temperature. The practical value of the method is assessed using a real-world dataset, by estimating the increase in the hosting capacity of the considered transformer for additional generators and loads. Significant gains are obtained when the transformer is sized by generation, in particular when photovoltaic (PV) generators are involved.

Introduction

Distribution transformers and power (HV/MV) transformers are predominant assets in a distribution grid, and sizing them well is a crucial task for distribution system operators (DSOs). When replacing, reinforcing or adding a transformer, DSOs should find a compromise between the high capital cost of oversizing it, and the risks (in terms of endangering the reliability of electrical energy supply) of undersizing it.

The typical steps of a planning study aiming at sizing a transformer are the following. Some assumptions must first be made regarding future loading conditions, in order to generate a set of “extreme” scenarios for load and generation that will be used as stress-tests to size the transformer. For transformers sized by generation (not consumption), a typical example of such a scenario, currently used some DSOs, is to consider that all generators will output their rated power and that the load will reach its lowest possible value [1], while taking into account forecasts of the future evolution of load and generation.

After loading scenarios have been defined, one of the following two categories of methods may be used [2]:

• The first and simpler one is to simply define physical limits, typically on instantaneous active power but possibly on other criteria, and to size the equipment so that these limits are not violated in any of the stress-tests.

• And the second, more elaborate one, is to perform a so-called “lower cost optimization” that aims at finding an economical trade-off between a smaller transformer that will be heavily loaded and undergo accelerated aging and increased losses, and a larger one that will cost more but not suffer from increased aging and losses [3,4,15].

1- Introduction

2- Frequency response analysis

3- Measurement of transformer winding deformation based on frequency response method

4- Frequency response analysis based on mathematical statistical indicators

5- Conclusion and future work

References

Abstract

Since the power transformers are indispensable in power systems, their reliable operation are of significance. Winding deformation is one of the most common failures within transformers. At present, many methodologies have been proposed to detect these faults, and frequency response analysis (FRA) technique is most frequently used because of its low cost, convenience, simplicity and effectiveness. However, there is no standard and reliable code to interpret the mechanical deformations from FRA traces as so far. In this study, an actual transformer experimental platform was used to simulate variable winding deformation faults in order to standardize the interpretation of winding fault degree from FRA data. The measured FRA raw data are processed from the perspective of statistics, and some numerical indices are found to be more suitable for the diagnosis of transformer winding deformation degree.

Introduction

The stable, reliable, safe and high quality power supply concerns the lives of hundreds of millions of people. As one of the most important pieces of equipment in power system, the stable operation of power transformer plays a critical role in the safe operation of the power system [1,2]. Statistics indicates that 25 percent of transformer faults were caused by winding mechanical deformation. Since the low voltage impulse (LVI) method was first introduced by Lech and Tyminski from Poland in 1966, many methodologies have been successively proposed to detect transformer winding deformation, for instance, the short circuit impedance (SCI) method, frequency response analysis (FRA) method and vibration method. SCI is based on the comparison and analysis of two short circuit impedance tests. In FRA, the frequency response traces are compared with its fingerprint to diagnose the occurrence of internal faults within power transformers. The vibration diagnosis method utilizes the characteristics that the transformer tank vibration will change when the winding fails [3]. Recently, some scholars present other improved techniques, namely, the sweep frequency impedance (SFI) method, which is the combination of SCI and FRA [1], the online impulse frequency response analysis (online IFRA) [4], the electromagnetic wave method [5] and the Lissajous locus method [6]. Above all, FRA is an effective and economic diagnostic technique for detection of mechanical deformations inside a power transformer [7]. FRA is sensitive to failures in the windings and iron core. What’s more, it can provide reliable information about the geometry of active parts of the power transformer without any needs to dismantle the unit. FRA uses input voltage as the input signal and another voltage measured at the other terminal of transformer winding as the output signal, besides, the measured current could also be used as output signal. In most cases, the output voltage is used. However, a standard and widely accepted code for interpretation of FRA traces can be improved; at present, experienced personnel are still needed to diagnose winding faults by using visual inspection [8], which is still a matter of great concern. At present, there are variable FRA interpretation methods, for instance, the equivalent electric model simulation method [9], the artificial intelligence method [10], and the mathematical statistics method [11]. In the first method, finite element analysis (FEA) of transformer winding is often used to build its equivalent electric model [12], to aid in interpreting the FRA curves. N. Hashemnia has studied the impact of winding axial displacement and radial deformation fault on equivalent electric parameters and FRA curves based on FEA [8,13], to improve the detection of winding faults. Besides, Z. W. Zhang has built a hybrid model based on FEA and multi-transmission line (MTL) to study the FRA curve beyond 1 MHz [14]. In the artificial intelligence method, M. Bigdeli has applied support vector machine (SVM) algorithm to classify the winding faults [15].

1- Introduction

2- Design of the proposed optimal DG algorithm

3- Formulation of algorithm objectives and constraints

4- Modelling of test system with component profiles

5- Optimal DG planning

6- Optimal DG operation

7- Conclusion

References

ABSTRACT

In this paper, an optimised framework utilising a Differential Evolution algorithm is presented to optimally integrate multiple distributed generation sources simultaneously into the distribution grid. By considering the important power system constraints, the proposed algorithm optimises the location, sizing and power factor setting for each distributed generation source to minimise network losses and maximise distributed generation integration. Various case studies were conducted at constant or varying levels of load and generation in both the planning stage and the real-time operation stage. The results of all case studies revealed that the proposed Differential Evolution-based algorithm delivered better performance in terms of network loss reduction and maximised distributed generation compared to other existing methods. The network loss reduction of 95.71% was achieved when all three parameters of placement, sizing and power factor of distributed generation were optimised simultaneously. In addition, a practical framework with a varying optimal power factor for distributed generation was designed. The optimal power factor setting for each distributed generation source was dynamically adjusted during real-time power grid operation, resulting in further minimisation of the system loss reduction. The overall loss reduction achieved was 96.04% relative to the base case of no distributed generation connection.

Introduction

In recent decades, global warming has resulted in worldwide desert expansion, temperature increase and rise in sea level. If this global warming issue is not addressed properly, some of the main landmasses and islands will eventually become uninhabitable. In the energy sector, the conventional electricity generation process based on the burning fossil fuels emits greenhouse gases, which are known to be the main cause of global warming. The use of Renewable Energy (RE) serves as an excellent countermeasure to the effects of global warming because RE is a non-depleting indigenous resource that produces insignificant waste pollutants [1]. Therefore, RE-based Distributed Generation (DG) has emerged as a preferred choice in the energy sector to reduce the amount of greenhouse gases emission [2]. Despite the environmental benefits, the technical aspects of RE-based DG integration to the power grid must be carefully assessed because these resources are intermittent in nature and rely heavily on weather conditions [3]. While integrating a small portion of RE into a large power grid is relatively easy to accomplish, the escalating penetration of RE is posing new challenges to both system planning and operation [4]. In the literature, researchers have reported various technical impacts on the grid due to DG connection to the power network [5]. The main impacts are grid voltage rise, reverse power flow and power quality problems. Severe grid voltage rise occurs if DG sources are connected in a weak power network [6]. Reverse power flow, which occurs during periods with high DG power generation and low demand, may affect the existing power protection schemes [7]. Moreover, power quality problems, such as harmonics and flickers, are caused by the switching of DG inverters [8].

1- Introduction

2- Proposed feature extraction methods for thermal image processing

3- Experimental study

4- Conclusion

References

Abstract

Induction motors are widely used in many industrial applications. Hence, it is very important to monitor and detect any faults during their operation in order to alert the operators so that potential problems could be avoided before they occur. In general, a fault in the induction motor causes it to get hot during its operation. Therefore, in this paper, thermal condition monitoring has been applied for detecting and identifying the faults. The main contribution of this study is to apply new colour model identification namely Hue, Saturation and Value (HSV), rather than using the conventional grayscale model. Using this new model the thermal image was first converted into HSV. Then, five image segmentation methods namely Sobel, Prewitt, Roberts, Canny and Otsu was used for segmenting the Hue region, as it represents the hottest area in the thermal image. Later, different image matrices containing the best fault information extracted from the image were used in order to discriminate between the motor faults. The values which were extracted are Mean, Mean Square Error and Peak Signal to Noise Ratio, Variance, Standard Deviation, Skewness and Kurtosis. All the above features were applied in three different motor bearing fault conditions such as outer race, inner race and ball bearing defects with different load conditions namely No load, 50% load and 100% load. The results showed that the proposed HSV colour model based on image segmentation was able to detect and identify the motor faults correctly. In addition, the method described here could be adapted for further processing of the thermal images.

Introduction

Different faults are likely to occur on the induction motor during its operation causing it to fail. However, through condition monitoring the lifetime of the motor could be increased by receiving up-to-date information about its behavior. In general, induction motors have two main types of faults namely electrical and mechanical, which are caused by heavy loading conditions. The most common and frequent fault is the mechanical fault as it accounts for about 53% of faults [1,2]. Generally, bearing defects are classified as mechanical faults referred to as inner race, outer race and ball bearing defects [3–5]. Recently, with the purpose of keeping the rotating machinery working in safe and reliable mode, the area of fault diagnosis based on condition monitoring has received the researchers’ attention to develop novel fault detection and classification methods which are capable of overcoming the limitations of the current condition monitoring methods. In recent years, Infrared Thermography (IRT) has been used as a condition monitoring technique, as it is non-intrusive, non-contact, single sensor based on the temperature measurements and fine-grained system [6]. Thus, infrared thermography has been adopted for monitoring the induction motors and diagnose its faults by comparing the hot region of the healthy motor image (reference image) with the hot region of the faulty motor image (faulty image). The thermal image contains much information about the motor and this information could be extracted using different image processing techniques [7].

1. Introduction

2. Modelling of PMSG

3. Stability analysis and dynamic performance of the proposed VSM

4. Simulation and discussion

5. Conclusion

Acknowledgements

Appendix A.

References

Abstract

This paper proposes a Virtual Synchronous Machine (VSM) strategy for Permanent Magnet Synchronous Generator based wind turbines which enables seamless operation in all operating modes. It guarantees Maximum Power Point Tracking in grid-connected operation, Load Following Power Generation in islanded operation and Low Voltage Ride Through capability during faults. To achieve optimal performance in all operating modes, the stability of the VSM is investigated in the event of small and large perturbations. The small-signal stability analysis of the VSM is conducted using a linearized state space model and the impact of the controllers on the dominant modes are derived using participation factor analysis. The transient stability and dynamic performance of the VSM are analyzed using a non-linear model. Based on this analysis, design guidelines and operational limits of the VSM are established. The results of this analysis are validated using time-domain simulations in MATLAB/SIMULINK.

Introduction

Driven by environmental, technical and economical factors, the grid topology is evolving, from centralized fossil-based power generation to distributed generation from renewable energy sources (RES) [1]. Irrespective of the power generation source, substantial system inertia is required to maintain stability and suppress oscillations due to disturbances on the network. According to National Grid [2], 70% of the British power system inertia is currently provided by large synchronous generators (SG). However, with the commitment of the UK to reduce 80% of its greenhouse emission by 2050, RES must generate at least 60% of power demand. This results in a massive reduction in the system inertia, which must be compensated by implementing ancillary infrastructures or integrating RES with control paradigms which offer similar robustness as the SG [3,4]. In terms of infrastructures, Nguyen et al. [5], studied the impact of synchronous condensers (SC) in maintaining the stability of the future grid. A model of the western Danish power system was utilized for the test scenario and results confirmed that, the application of SC at strategic locations, adequately damps power system oscillations and improves the frequency stability. Several research works [6–8], have corroborated this findings and it has been applied in some HVDC projects [4,9], to improve grid strength. Despite the benefits that the SC offers, it may not be economically viable for scenarios with 100% RES. Hence, several research works have been focused on augmenting the control paradigm of RES rather than adding expensive infrastructures to support the grid.

1- INTRODUCTION

2- SYSTEM LAYOUT

3- CONTROL SCHEME

4- CONCLUSION

REFERENCES

Abstract

In this paper, we are proposing currentcontrolled hill-climbing strategy used in Maximum power point tracking (MPPT) of the solar photovoltaic array to Charge OFF Board Electric vehicle lithium-ion batteries within the safety limits and supported rating of batteries so that EV battery does not get damaged and can also increase the life of the battery. Here, a current sensor and potential difference sensor-based electric vehicle off-board battery charging by hill-climbing strategy is tested on MATLAB simulation. The satisfactory steady-state battery is charging within the rated charging limit, under variable solar irradiance.

INTRODUCTION

The transportation sector has seen a major shift towards electric vehicles as it not only stops our dependence on fossil fuels and stop pollution from these vehicles that vehicles release. Hence, we are moving towards cleaner sources of energy. Also, photovoltaic resources are increasing in demand as they are the source of clean energy and don’t emit carbon dioxide

Two types of charging method are there ON Board charging and OFF Board charging. ON Board charging is when Battery is kept in the Electric vehicle and charging circuit is not on the vehicle itself but near the charging station. And the battery is charged directly through the DC supply.

1- Introduction

2- The model

3- Global boundedness under control limits

4- Hopf bifurcation and periodic attractors

5- Conclusion

References

Abstract

In this paper we investigate whether continuous oscillations are probable for the wind turbines dynamics when connected to the grid. This can have negative consequences on the mechanical parts of the system, the power grid and, possibly, on other power systems connected to the same grid. We consider the wind turbine when the pitch control is activated, exposing it to higher wind speeds. In order to find out if there are continuous oscillations in the state variables that may realistically occur, we investigate if there are periodic attractors for the dynamics that are still allowed within the control limits suggested by many in industry, such as, and not limited to General Electric. The paper provides rigorous mathematical proofs for boundedness of the systems state variables and their derivatives under the imposed control limits by industry. This establishes the existence of attractors in a bounded system under the controls. We then find that there is a Hopf bifurcation in which periodic attractors within the control limits exist. The results are supported by simulations. The nonlinear model used in the analysis is validated versus a real measured data to magnify the finding of this paper. The conclusion of this paper is significant for the nonlinear dynamics and control literature for wind turbines complex system, and the possible consequences on studying/questioning the control limits (limeters) suggested by industry.

Introduction

According to the US Department of Energy [1], wind is the fastest growing energy resource being used. This rapid expansion requires more scientific research and studies to comprehend the dynamics of Wind Turbine Generators (WTGs), if we are to gain the most from this valuable resource. Governments and corporations are working on understanding the challenges and consequences of integrating WTGs within large cities with/without other power systems. As a result of the complexities of the WTG mechanical and electrical systems, dynamic and control studies have increased recently. This has been observed by the comprehensive review article [2]. Additionally, the reader may consider [3,4] for studies that are looking into the challenges facing the future of power grid with large share of wind and renewable energies. According to [5], three-bladed (type-3) WTGs are more efficient in extracting power from the air streams, when compared to other types. Coefficients of Performance ( curves) of type-3 can go to up 0.4-0.5 efficiency (also see [6]). Most agree that Doubly Fed Asynchronous/Induction Generator (DFAG/DFIG) is mostly the technology used with WTGs systems. A detailed study describing this can be found in the literature review of [2] with citations to many sources in the literature that focus mainly on investigating the implementation and advantageous of DFAG/DFIG technologies.