Transmission lines modelling based on RLC passive and active filter design

This paper presents a transmission line (TL) modelling which is based upon vector fitting algorithm and RLC passive filter design. Frequency Response Analysis (FRA) is utilised for behaviour prediction and fault diagnosis. The utilities of the measured FRA data points need to be enhanced with suitable modelling category to facilitate the modelling and analysis process. This research proposes a new method for modelling the transmission line based on a rational approximation function which can be extracted through the Vector Fitting (VF) method, based on the frequency response measured data points. A set of steps needs to be implemented to achieve this by setting up an extracted partial fraction approximation, which results from a least square RMS error via VF. Active and passive filter design circuits are used to construct the model of the Transmission line. The RLC design representation was implemented for modelling the system physically while MATLAB Simulink was used to verify the results

Real-time control for robotic hand application based on pressure sensor measurement

This paper presents the use of data acquisition (DAQ) device and LabVIEW program to evaluate and measure the pressure distribution for real-Time robotic hand applications. An analog conditioning circuit has been implemented to calibrate and extract data from the utilized sensors to be processed by the DAQ and LabVIEW. Furthermore, an adequate signal processing analysis is performed on acquired data to investigate the desired measurements of pressure distribution for the robotic hand control purpose. This framework is considered as one of the techniques that can be used for robotic hand applications based on pressure sensor distribution and real-Time monitored through the LabVIEW

Intelligent forecasting temperature measurements of solar PV cells using modified recurrent neural network

For microgrids to operate optimally and minimize the effects of uncertainty, anticipating solar PV measurements is essential. For residential and commercial microgrids that use solar PV, the predicting of solar energy over a short period is crucial for managing grid-connected PVeffectively. Therefore, this work develops a Recurrent Neural Network (RNN) for forecasting temperature measurements as time series records, where a combination of long short-term memory (LSTM) architecture with RNN is used to process input measurements by updating the RNN state and winding over time degrees. Data from the entire prior time steps is stored in the RNN state. A dataset of temperature waveform measurements is used, which includes 2000 unnaturally produced signals of three channels with varying length. An LSTM neural network can be used to expect future values of a time series or sequence utilizing data from earlier time steps as input. Training of a regression LSTM neural network through the output of a sequence is performed, where the goals are the training sequence with records shifting one-time step, for training theLSTM neural architecture with time series forecasting. In other words, the weights of the LSTM neural structure learn to predict the following time step values of the input sequence at every time step. By considering the past forecasts as inputs, the closed-loop prediction forecasts the next time steps of sequences. The model makes the forecast without using the true data. The cross-entropy loss serves as the loss function. It is found that the mean RMSE overall test observations were about 0.5080 which promises to make better predictions from learning the temporal context of input sequence

Alternative solar-battery charge controller to improve system efficiency

This paper proposed a high efficiency solar-battery charge controller as an alternative to that controller which is used in most conventional residential solar system , the concept of the proposed controller circuit based on using the off state energy duration of the overcharge current in a separate path, this energy delivers to auxiliary battery or direct load, such as fans, used to cool or ventilate the system components and consequently improving system performance, where the overcharge current refer to that current available stand by when the battery fully charged or reached its maximum charge voltage. It is avoided here that power losses coming from the main switching component and complexity of the conventional controller, this will leads to new electronic circuit with low losses as a compared with the conventional charge controller to be a part of the integrated and automated building solar system, the design has an algorithm based on some environment parameters like sun Irradiance and weather temperature, this algorithm seems to be inversely calculated because its start from the value of full charge battery voltage, the practical results shows the improvements if compared with other methods. A Simulink Matlab simulator is attempted in the simulation phase of this research as well as an experimental data has been collected to verify the circuit function and energy saving goal

Review of gravitational electric energy and application perspectives on modern buildings

Recently, exploitation of the renewable energy resources has been underlined in high-rise buildings, the contribution of building in energy conservation has witnessed increased advances in the recent years in both residential and commercial sectors. The increasing demand for building services and comfort levels as well as due to growth in population and the time that the people spent inside that commercial buildings and homes, which leads to upward trends for more demand on energy and continue in future. Therefore, the conservation of energy in buildings nowadays is a major objective for energy policy over all levels. From the viewpoint of energy conception efficiency and user's safety, highlighting of Gravitational Energy (GE) is a meaningful, but considered as a big challenging problem. This paper presents an investigation based on the current state of the art regarding the possibilities of energy generations in the buildings with multilevel parking. Therefore, the research divides the potential and kinetic energy of the climbed down vehicles in such buildings into mainly related technologies for utilizing all possible energy which could convert to electricity. Thus, the research Check the feasibility, energy management and control strategies of the Regenerative Braking System (RBS) in railways, Electric Vehicle (EV), and elevators depending on the modern research works. From this paper survey, it can be revealed that the RBS as a GE systems with multi-converter devices are active for the recipient energy systems to improve efficiency, quality and reliability of the power source

Transmission lines modeling based on vector fitting algorithm and RLC active/passive filter design

In the modeling of the transmission line, the electric energy produced at generating stations is transported over highvoltage transmission lines to utilization points, and the trend toward higher voltages is motivated by the increased line capacity while reducing line losses per unit of power transmitted. An electric transmission line is modeled using series resistance, series inductance, shunt capacitance, and shunt conductance. For some studies, it is possible to omit the shunt capacitance and conductance and thus simplify the equivalent circuit considerably. Frequency Response Analysis (FRA) on the transmission line application is utilized for behavior prediction and fault diagnosis, but a need for more investigation is important for the bases on which the diagnosis determined. The utilities of the measured FRA data points need to be enhanced with suitable or developed modeling category to facilitate the modeling and analysis process. This research proposes a new method for modeling the transmission line based on a rational approximation function which can be extracted through the Vector Fitting (VF) method, which attempts on the frequency response measured data points. A set of steps needs to be implemented to achieve this by setting up the extracted partial fraction approximation, which results from a least square RMS error via VF, in such a way that would construct as real numbers, first and second order parts as well as the gain constant. Active and passive filter design circuits are attempting to construct the model of that rational function of the transmission line. RLC design representation has been implemented for modeling physically the system with MATLAB, Simulink for verifying the results

Identifying some regularities of radio frequency propagation of a radar system by analyzing different environmental effects

Free space path loss is a function of frequency and propagation distance and the RF signal propagates at light speed in all directions in free space. The performance evaluation of wireless and radar communication technologies is related to understanding the propagation environments. This work presents the modeling of several RF propagation properties that include atmospheric attenuation due to rain, free space path loss, gas, and fog, as well as multipath propagations caused by ground bounces. The methodology discusses the developed model according to the series of (ITU) International Telecommunication Union references to radio wave propagation. This work discusses the Free Space Path Losses (FSPL), and Propagation Losses (PL) due to the atmosphere, precipitation, snow, rain, clouds, fog, atmospheric lensing and absorption, and polarization mismatch. The work also discusses the vertical coverage diagram and radar propagation factor. The obtained results demonstrate that the PL increases with frequency and range, at a 90-degree roll angle, the attenuation approaches infinity, and as the altitude rises, the amount of attenuation caused by lensing decreases. The analysis of attenuation at 1 km vs. frequency variations, at roughly 60 GHz, indicated a high absorption owing to air gas. Lensing attenuations are also offered as secondary outputs for convenience, the wideband channels present higher performance crossways and a wide range of target height as expected. When the target height increases, the influence of multi-path fading approximately vanishes entirely due to the variation increasing in the spreading delay between the bounce and direct pathway signals. This will reduce the coherence sum between these two samples on receiving by the targe

Silicon PV module fitting equations based on experimental measurements

Solar photovoltaic (PV) characteristic curves (P‐V and I‐V) offer the information required to configure the PV system to operate as near to its optimal performance as possible. Measurement‐based modeling can provide an accurate description for this purpose. This work analyzes the PV module performance and develops a mathematical formula under particular weather conditions to accurately express these curves based on a custom neural network (CNN). The study initially presents several standard mathematical model equations, such as polynomial, exponential, and Gaussian models to fit the PV module measurements. The model selection is subjected to the minimum value of an evaluation parameter. To simplify the solution of the symbolic equations for the CNN network, two neurons in the hidden layer with nonlinear activation function and linear for the output layer were selected. The results show the effectiveness of the proposed CNN model equations over other standard fitting models according to the root mean squared error (RMSE) evaluation. This method promises further improved results with multi‐input parameter modeling

Smart plug prototype for monitoring electrical appliances in home energy management system

Recently, the technology of Home Energy Management System (HEMS) has expanded for the purpose of reducing energy consumption. This paper presents the development of a smart plug with a wireless Zigbee sensor for measuring power consumption of electrical appliances in the HEMS. Experiments were carried out to evaluate the power consumption of a wireless sensor node in a smart plug using only Zigbee as a microcontroller. Experimental results showed that the smart plug using Zigbee is capable of processing and analyzing the analogue sensor signal with lower power consumption. In addition, the data obtained from the wireless sensor is more accurate and smoother as compared with the data obtained from the oscilloscope. The proposed smart plug has the characteristics of simple design, low cost, low power consumption and easy to control electrical home appliances by switching on/off from the HEMS controller

Daily real-time monitoring of the PV thin film modules for analysis and system modeling

The power output of a Photovoltaic system is mainly influenced by the weather conditions. Semitransparent [CdTe] Thin-Film PV module is one of the promising green energy sources that need to be more investigated in terms of efficiency and modeling. This paper presents real-time daily measurements for such modules that serve the system design, prediction, and modeling. Single and multi-layer configurations categories have been used as a platform to test the PV system at various temperature and irradiance ranges. Experimental measurements were conducted at UPM University, Serdang, Malaysia, where a 6 different modules are tested according to their interconnection and installation. A wireless data acquisition card, of one second sampling interval, has been utilized to acquire the weather and electrical parameters (module temperature, solar irradiance, Voltage, and Current). The result of the harvested daily energy shows a value around (2.51) as a maximum efficiency in a cloudy day conditions and it is influenced by the transparency factor when configured in a multi-layer. It is found that the modules' performance is similar to that of a Silicon-based solar panels