Vibration based piezoelectric energy harvesting utilizing bridgeless rectifier circuit

The energy harvesting technique has the capability to build autonomous, self-powered electronic systems that does not depend on the battery power for driving the low power electronics devices. In this paper, a voltage doubler and bridgeless boost rectifier power electronic converter is proposed to increase the energy harvesting output voltage from piezoelectric vibration based transducer. The conventional full-wave diode bridge rectifier and boost converter for energy harvesting system increases significant voltage drop and power losses in the circuit. However, the proposed voltage doubler and bridgeless boost rectifier circuit reduce the voltage drop and power loses in the circuit and thus increases the efficiency of the circuit. The proposed voltage doubler and bridgeless boost rectifier circuit step-up the output voltage up to 3 V DC from an input voltage of 1.9 V AC

Performance Comparison of Artificial Intelligence Techniques for Non-intrusive Electrical Load Monitoring

The increased awareness in reducing energy consumption and encouraging response from the use of smart meters have triggered the idea of non-intrusive load monitoring (NILM). The purpose of NILM is to obtain useful information about the usage of electrical appliances usually measured at the main entrance of electricity to obtain aggregate power signal by using a smart meter. The load operating states based on the on/off loads can be detected by analysing the aggregate power signals. This paper presents a comparative study for evaluating the performance of artificial intelligence techniques in classifying the type and operating states of three load types that are usually available in commercial buildings, such as fluorescent light, air-conditioner and personal computer. In this NILM study, experiments were carried out to collect information of the load usage pattern by using a commercial smart meter. From the power parameters captured by the smart meter, effective signal analysis has been done using the time time (TT)-transform to achieve accurate load disaggregation. Load feature selection is also considered by using three power parameters which are real power, reactive power and the TT-transform parameters. These three parameters are used as inputs for training the artificial intelligence techniques in classifying the type and operating states of the loads. The load classification results showed that the proposed extreme learning machine (ELM) technique has successfully achieved high accuracy and fast learning compared with artificial neural network and support vector machine. Based on validation results, ELM achieved the highest load classification with 100% accuracy for data sampled at 1 minute time interval

Automatic mapping of concrete strength in structural element

Collapses of structure under construction can be prevented if quality control is practiced at sites. The strength uniformity of reinforced concrete structure element cast on site depends on the level of compaction of the fresh concrete. The whole element should be checked and mapped so that localized defect can be detected and removal of formwork can be stopped if applicable. A portable and quick way to check and map the uniformity and the strength of concrete has been developed utilizing the use of pressure wave and signal processing techniques. An echo is introduced to the sample by dropping a small steel ball from a certain height from the concrete surface. The impact generates stress wave, which propagate through the concrete. The accelerometer receives the wave and changes the display from time to frequency domain. The highest observed frequency is determined as the depth frequency. The velocity is calculated as CP = 2fD. Hundreds of specimens were tested. The relationship between the strength and the velocity is correlated. From correlation equation, the strength of concrete can be estimated within 10% error (Hamid et al, 2004). The mapping process is done automatically in computer-generated program. Signal-processing techniques were used to compute the data; Fourier Transform to translate a time-series signal into frequency domain, concrete strength calculation, interpolation technique and a Graphic User Interface (GUI) to complete the mapping algorithms

Behavioral analysis of thermoelectric module under different configurations and temperature gradient

This study analyzes the behavior of the thermoelectric module (TEM) in a transient status which allows natural cooling condition. The analysis mainly aims to extract energy from the ordinary heat source and convert it into useful electrical power. Several TEM configurations which involve single TEM and multi stage TEM are manipulated within the system since the previous studies only focused on single TEM behavior only. For a complete TEM behavioral analysis results, the performance of multistage TEM must be taken into account as this type of configurations is usually used in highend TEM application to produce greater voltage value. A multistage TEM that is connected electrically in series and thermally in parallel produces a higher generated voltage value compared to a single TEM. TEM temperature gradients also are changed throughout the experiment to examine how this term affects the TEM behavior. The results show that the multistage TEM contributes the highest output voltage and it depends on the number of cascaded TEM. Furthermore, a higher temperature gradient contributes to more voltage generated by the TEM. TEM analysis with heatsink is proved to have larger temperature gradient to maintain the cold side of the TEM junction. Loading effect analysis shows that the TEM system can obtain 5 V of stable voltage when the load resistor connected to the system output is 200 Ω and above

Design of improved incremental conductance with fast intelligent (FI) based MPPT technique for solar PV system

Currently, the solar PV power extraction technology is undergoing significant improvement. Towards this, the paper proposed the design for a photovoltaic (PV) array and the output performance of a photovoltaic system under the influence of irradiance. To achieve this, the design for improved incremental and conductance fast tracking INC -FI based MPPT technique for solar PV system has been presented. The purpose of employing the improved INC -FI technique is to improve the efficiency of the system. The accuracy and performance of the proposed INC -FI method was increased due to its better tracking capability by utilizing variable ΔD for tracking the MPP in comparison to the conventional INC method at variable temperature while keeping the irradiance constant. Further, the results of the proposed method were compared with the conventional method where the INC -FI based technique outperforms the conventional INC method in terms of better accuracy. For the irradiance with 800w/m2, the achieved MPPT efficiency was 58.21 for conventional method and 80.53 for the improved technique. It was also noted that the tracking efficiency of the conventional method was 84.39 as compared to 99.92 for the proposed INC -FI technique in terms of MPPT efficiency at the irradiance of 1000w/m2. Furthermore, the improved method delivered fast tracking ability of the MPPT system with a time of less than 10 s(approx.). The MATLAB Simulink platform was utilized for designing the proposed technique. In future, the proposed INC based technique would be implemented on hardware for better outcomes and validatio

Pengawasan beban tak mengganggu menggunakan mesin penyokong vektor

Kertas kerja ini membentangkan pembangunan pengawasan beban tak mengganggu (PBTM) untuk mengenal pasti beban dengan menggunakan pengelasan mesin penyokong vektor berbilang (MPVB). Suatu kaedah pengawasan beban diselia dilaksanakan untuk mengenal pasti tiga jenis beban yang kebiasaannya terdapat di bangunan komersial iaitu lampu pendaflour, penghawa dingin dan komputer peribadi. Parameter kuasa asas yang terdapat pada meter pintar dan penyarian sifat kuasa lain yang lebih terperinci dipertimbangkan dalam kertas kerja ini. Sifat kuasa yang berkesan ditentukan dengan melakukan pemilihan sifat mengikut kombinasi yang berpotensi. Selain itu, teknik baru penyarian sifat, iaitu, jelmaan masa-masa (MM) diperkenalkan dalam kajian ini. Suatu kaedah pemilihan sifat kuasa yang sistematik dilaksanakan dengan mempertimbangkan kombinasi terbaik untuk tujuan perbandingan. Berikutan penggunaan meter pintar komersial di sektor pengguna adalah majoriti dengan kadar pensampelan yang rendah, perlaksanaan eksperimen dan kajian yang dilakukan adalah di bawah pengukuran penggunaan yang sebenar dengan pensampelan yang rendah. Kadar pensampelan rendah yang sesuai untuk PBTM dikaji mengikut spesifikasi meter pintar komersial dengan tiga keadaan pensampelan iaitu 1 minit, 10 minit dan 30 minit. Satu set data pengesahsahihan dengan aktiviti beban secara rawak digunakan untuk menguji kemantapan kaedah PBTM yang dibangunkan. Justeru, teknik pengelasan beban menggunakan MPVB dibandingkan dengan teknik lain seperti bayes lurus dan K-kejiranan terdekat (KKT) untuk menilai prestasi MPVB yang dicadangkan untuk PBTM. Menerusi keputusan yang diperolehi, kaedah yang dicadangkan iaitu MPVB menunjukkan keputusan pengelasan yang terbaik dengan 99.94% ketepatan dalam mengenal pasti beban. Justeru, berdasarkan kadar pensampelan yang dikaji pensampelan 1 minit menunjukkan penggunaan pengawasan beban yang terbaik berbanding pensampelan lain yang dikaji untuk tujuan PBTM

Investigation of temperature gradient between ambient air and soil to power up wireless sensor network device using a thermoelectric generator

This paper proposes a study of an energy harvesting system for powering wireless sensor network (WSN) devices. The thermal energy harvesting system used is based on the thermal energy source between ambient air at the soil surface with five depth levels. Measurement was taken for 46 days in a garden area located in Melaka, Malaysia. A feasibility study of soil temperature measurement to obtain a temperature gradient can be used for harvesting by using thermoelectric generators (TEG) modules. Then, the efficiency of TEG with several different configurations based on temperature gradient data has been tested in the laboratory. The results revealed that the depth of soil 6 cm between sensors 1 and 3 will gave the best representation of level average temperature different around 1 ℃. Based on the temperature gradient data, the combination of three TEG SP1848 in a series connection with DC-DC step-up circuit DC1664 will produce an optimum voltage output of about 3 V. This output voltage is enough to operate low power IoT device derived from thermal energy

Design of fast intelligence hybrid fuzzy logic and improved incremental conductance based MPPT technique

Presently, there has been a significant growth in the solar PV technology due to various factors such as clean technology, zero carbon emission and low maintenance. However, it becomes significant to extract the power in abundance from solar PV system due to its intermittent nature. To extract the significant power, a suitable maximum power point tracking (MPPT) technique has been presented. The MPPT technique is developed based on the hybrid fuzzy logic (FL) and improved incremental and conductance (IInC) method. The aim of developing hybrid FL-IInC technique for MPPT is to regulate duty cycle so that maximum power point (MPP) is achieved with stable and accurate outcomes during dynamic and steady state conditions. The IInC method was developed by regulating the duty cycle and step-size. of It was observed that proposed hybrid FL-IInC delivers accurate and stable results as compared with IInC method. During the model testing at the irradiance with 1000w/m2, the achieved MPPT efficiency was 99.96% as compared with the IInC with an outcome of 98.47% for the improved technique. Additionally, the settling time for the proposed hybrid FL-IInC was less compared with the IInC method. All the simulations were conducted with the MATLAB Simulink Platform. In future, the hybrid FL-IInC method can be employed with other conditions such as partial shading for better applicability

Partial discharge signal propagation, modelling and estimation in high voltage transformer windings

The thesis concerns partial discharge (PD) propagation within a high voltage transformer winding. Location of PDs and magnitude estimation are important tools for both diagnosis and prognosis of the health of large transformers. In reality there is limited access and knowledge of a winding and consequently any practical method requires the use of estimation techniques. The approach taken in this thesis is by considering lumped circuit parameter models. Firstly, a lumped capacitive parameter model was considered and secondly a transmission line lumped parameter approach developed. A technique of split winding analysis is introduced for both types of model. The derivation of the capacitive network considers the source location of a PD by defining the PD signal propagation in two directions. At the source, the currents are equal in magnitude and are attenuated as they flow in each direction. This provides information for a fixeddistribution model equation. Under transmission line lumped parameter models, split winding analysis explains the development of accumulated harmonic waveforms of the PD propagation signal towards the neutral and bushing tap-point. At the source, a D’Alembert solution is employed to estimate the oscillation level and found to be in very good agreement with measured data using rectangular wave signal injection. PD signal behaviour is then considered using a time varying boundary conditions model with a principle of superposition equation of source signal. Duhamel’s principle is employed to find a solution for any waveform applied to some point on the transformer winding. Under the influence of losses and distortion, an accumulated harmonic amplitude analysis from the Duhamel’s principle estimates the PD propagation level. For different injection points along the transformer winding, the measured PD level at the neutral and bushing tap point caused by the accumulated harmonic amplitude revealsdifferent patterns. As the PD injection point is altered from the bushing tap point to the neutral, the measured signals significantly change. This in turn contains information of the level of discharge signal at the source. From this analysis a technique based on minimum mean error (MME) calculation using the measurements at the bushing tapand neutral points can be used to identify the source location of PDs based on the analysis of accumulated harmonic amplitudes. With a known location, the information can then be used to estimate PD levels. As the actual charge transferred at the location of a partial discharge cannot be measured directly, by using the D’Alembert solution, the PD source level is found to have approximately twice the apparent magnitude. By using the predominantly capacitive model derived based on split current propagation, PD estimation at higher frequencies is also possible. As a result, an estimation of PD level can be estimated for measurement signals having bandwidth of up to 150MHz