Volume 10, Issue 2

A cost-effective power supply design proposed for electrostatic precipitators (ESP) is presented in this work. The cost minimization is done in terms of eliminating the power transformer and reducing power consumed by the ESP unit. Usually, transformers are used to boost the voltage level in conventional systems on its input side, which is replaced by a combination of a high-frequency converter along with a voltage multiplier in a modular arrangement. By interconnecting these modules, the suitable voltage is built-up easily. An intermittent pulse energized supply is developed by the proposed system to reduce back corona and to save energy consumption. The modular arrangement also increases the lifetime of converter switches, by reducing the switching stresses developed across them during its high-frequency operation and by reducing the Total Harmonic Distortion (THD). The complete system is designed and analyzed using MATLAB SIMULINK. The obtained results are better than the existing methods used for generating intermittent energization, the THD is reduced to 35.78% and the voltage stresses also reduced to 1800 V. And a module is experimented and found that it is capable of producing 3 kV.

Despite the intensive research carried out in the last two decades, the actual performance of piezoelectric energy harvesters needs significant improvement for widespread applicability. Custom designed experimental set-ups and methods can be applied for the evaluation of new piezoelectric energy harvesters or modified design versions of existing transducers, in terms of efficiency and specific power. In this context, two representative types of commercial cantilever piezoelectric transducers, made of PZT and PVDF material respectively, were tested in various combinations of aerodynamic and harmonic base excitation. A line type laser was used along with long exposure photography for the visualisation of the piezofilm’s mode shapes, tip deflection and the digitization of the elastic line at the oscillation extrema. The harvested power was measured at on-resonance conditions and studied relative to the excitation combinations and the mode shapes. Energy conversion efficiency, defined as the ratio of the electric-field energy accumulated by the supercapacitors, over the total elastic strain energy change of the material during the oscillations is measured and compared. Design improvements are proposed for both transducer types to extract and absorb higher amounts of energy and improve their bandwidth to match the available excitation source characteristics.

The goal of this work is to reduce power loss and improve voltage profile by formulating the optimal DG placement problem as a restricted nonlinear optimisation problem. As a novelty, the proposed hybrid algorithm, referred to as Multifactor Update-based Hybrid Model (MUHM) is constructed by merging the concepts of Lion Algorithm (LA) & Sea Lion Algorithm (Sea Lion Optimization Algorithm (SLnO). The Forward-Backward Sweep (FBSM) Model is used to calculate the power loss. Three test cases are examined for the voltage profile & loss minimization in the feeder team with DGs: “case 1(DG supplying real power alone ( P ), case 2 (DG supplying reactive power alone ( Q ) and Case 3 (DG supplying both real and reactive power)”. Application of the suggested method to various IEEE test systems, including IEEE 33, IEEE 123, and IEEE 69, respectively, is used to assess its efficacy. According, the results show that the presented work at loading percentage = 0 is 12, 15, 135, 4.65, and 8 superior to SFF, BBO, BAT, LA and SLnO, respectively.

This paper presents a single-phase seven level Cascaded H-Bridge DC-Link (CHBDCL) inverter for marine electric propulsion drives. The speed of propulsion drive can be changed by CHBDCL inverter by converting DC output from the rectifier to variable output voltage with or without change in frequency. The proposed CHBDCL inverter generates more output voltage with minimum harmonic content than classical Multilevel Inverters (MLIs). The CHBDCL inverter necessitates only ‘ m  + 3’ power devices for ‘ m ’ number of levels, although the classical MLIs requires ‘(2 m  − 1)’ power devices. CHBDCL inverter can have the effective performance by utilizing unipolar Sine Pulse Width Modulation (SPWM) and unipolar Space Vector PWM (SVPWM) with sine carrier. The effectiveness of the proposed CHBDCL inverter topology has been verified by using MATLAB/SIMULINK for various modulation indices in terms of voltage levels and harmonic analysis. Furthermore, an experimental setup involving pulse generation from a Field Programmable Gate Array (FPGA) has been used to test the performance of the proposed CHBDCL inverter.

Solar energy is sustained using the principle of photovoltaic effect through a solar photovoltaic (PV) system as the main receiver of sunlight for the island. The use of photovoltaic (PV) systems to generate power from solar energy has increased in recent years due to its availability and sustainability. The proposed bat algorithm provides a very quick confluence and high accuracy since it interactively merges with the exploration advancements with the substantial distinctive signal search during the maximum power point tracking process from the PV array. The improved bat algorithm proposes a signal search method to increase the speed and tracks more power at a longer distance by using the signal between the bat and its prey. An energy storage system (ESS) stores solar energy and releases it into the system for use when energy generation from the source is low. DC to DC converter controls and regulates the output generated voltage from the PV array. DC to AC converter converts DC power produced to AC power to be supplied to the island for use. The design and simulation were performed in MATLAB Simulink and the result shows the effectiveness of the proposed design.

Renewables always attract everything than other thrust research areas owing to the global warming issue caused by using the non-renewables therein which should be mitigated at the earliest possible time. The easiest and safest alternative is employing renewable energy resources for the generation of energy that is completely sustainable. Many countries started insisting to seek alternatives trying to terminate to the fullest extent. Even though all these measures are taken, it is very hard to mitigate the utilization of non-renewables, owing to efficacy lag in renewables. The simplest solution for this problem is hybrid usage of renewables to enhance the efficiency. This article took this as a factor, gathered data for hybrid RERs technique with its accuracy range for easy selection of techniques by the stakeholders, trending technology being adopted, and future scope abetted by the patent landscape.

In the article, the viability of adopting photovoltaic energy systems to convert solar energy into hydrogen in Iraqi four main cities are examined. A 22 kWp off-grid solar system, an 8 kW alkaline electrolyzer, a hydrogen compressor, and a hydrogen tank were modeled for an entire year in order to produce hydrogen. Using hourly experimental weather data from 2021 to 2030, MATLAB/Simulink is used to create a mathematical model of the recommended system behavior. The results revealed a range of annual hydrogen production from 1713.92 to 1891.12 kg, annual oxygen production from 1199.74 to 1323.78 kg, and annual water consumption from 7139.91 to 7877.29 L. Each kilogram of hydrogen costs $3.79. The results indicate that the optimal location for solar hydrogen production systems might be constructed in the central region of Iraq and in other regions with comparable climatic characteristics, particularly those with high radiation levels.

This research established the technoeconomic feasibility of an on-grid hybrid renewable energy system for delivering electricity to the deanery building of the Engineering College at the University of Diyala, Iraq. The most cost-effective system design was discovered by modeling and optimization, with an average daily load of 25.0 kWh and total cost and energy cost of $5142 and $0.05/kWh, respectively. In relation to the energy generated by conventional resources, the designed system is more cost-effective and has a lower carbon footprint of about 13,052 kg/year of CO 2 emissions avoided. According to the research, using a hybrid power system to electrify and decarbonize the electrical energy supply could be a reliable and economical way to do both at the same time. Innovation is in integrating the suggested hybrid system so that the use of electricity can effectively be decreased to meet the load. As a result, the system components are not oversized, which reduces system costs and reduces emissions.

Producing sustainable energy to meet the world’s current demands is a major concern. Municipal Solid Waste (MSW) is a good source for producing sustainable energy and currently gets abundantly generated in India. Usually MSW is screened to prepare Segregated Dry Municipal Solid Waste (SDMSW) pellets before subjecting it to gasification to produce producer gas. But, generation of hazardous byproducts is a key issue in the conversion of SDMSW to producer gas. In the present work a multi-purpose downdraft gasifier has been designed and developed that can process biomass and SDMSW pellets blend while reducing undesirable byproducts such as tar and ash. The calorific value, chemical composition and byproduct content of the SDMSW pallets blended with biomass are determined prior to gasification. The feedstock is characterised using ultimate and proximate analysis, and the calorific value is determined using a bomb calorimeter. Gas chromatography is used to assess the quality of the producer gas. The results indicate that adding 50% SDMSW to Biomass results in good efficiency.

Wireless sensor networks (WSNs) have been deployed widely in many different application including in civil and military fields. The sensing data from the networks is very diverse and may cost huge energy consumption for transmission. Hence, mobile sensors with high capacity are deployed to support the static sensors dealing with longer range communicating distances and also supplying power wirelessly the sensors if possible. This paper focuses on an energy harvesting (EH) design for either mobile agents or sensor nodes in WSNs. A hybrid EH system can harvest energy from ambient environment around to power the mobile sensors and static sensors. In addition, these mobile sensors and transfer power wirelessly to the sensors if required. We provide different scenarios for harvesting energy from both RF and solar energy to support the devices. All the designed circuits based on mathematical equations are provided, specifically. Simulation and experimental results are addressed to clarify all the scenarios for the networks. The results show promise and practical.

The occurrence of hotspots in photovoltaic panels is one of the most common problems of solar power plants, which reduces the output power of photovoltaic arrays and can also cause irreparable damage to the solar cells. There are several ways to identify hotspots, including using custom datasets using thermographic camera images, which will be later used to teach YOLO and Faster R-CNN computer vision algorithms. In practice, it is observed that the YOLO algorithm is many times faster than the Faster R-CNN in high-density solar panels. Therefore, the applied method is the safest choice for automatic hotspot detection in large-scale photovoltaic power plants to improve overall efficiency. In this paper, by comparing the performance of methods such as Faster R-CNN with YOLO, we concluded that the YOLO algorithm has far better advantages in terms of quality of detection, and speed. Therefore, this factor makes the use of YOLO significantly helps to speed up the troubleshooting of solar modules caused by hotspots, and this factor improves the efficiency of solar power plants in the long run. Meanwhile, in the studies for this paper, the results extracted by Python have been optimized as an algorithm to be used for hotspot detection.

The solar photovoltaic system is one of the technologies which is used to pump water in rural, isolated and desert areas where electric connection to the main grid is a problem. The study area is selected because of its higher natural resources of solar radiation over the year. Thus, that encourages us to adopt this study in order to understand the effects of various operating parameters on performance behaviour, which leads to enhancing the system design. This paper aims to assess the solar water pump system’s design and estimated performance in real environmental conditions. The PVsyst has been used to design and simulate a system which allows us to analyse the operating behaviour of a photovoltaic solar water pumping system. The solar PV pumping system design is considered; the photovoltaic module has characteristics and the pumping system characteristics. The photovoltaic array losses due to temperature were estimated about −14.3% and the soiling losses represented approximately −5%. The results showed that performance losses were significant variance in the months of the summer season from May to July. Therefore, their implication on the water flow rates significantly decreases throughout the months of the summer season from May to July, respectively.

Real time monitoring of high voltage devices in smart grid is implemented using wireless sensors. They ensure reliable power transfer and avoid cascading power failures. Powering these sensors remotely is a challenge. This paper presents a novel method of powering sensors remotely using magnetic field harvester. A dumbbell shaped magnetic core is designed and optimized to harvest magnetic field near high voltage bus bars/transformers in electrical substation. The harvested power is rectified and boosted. Impedance matching circuit is designed to obtain maximum power transfer to the wireless sensor. The energy thus harvested is used to power wireless sensors and make them self sustainable. The experimental results show that the proposed core with 40,000 turns can harvest 17.6 mW of output power when placed in magnetic flux density of 9 µT rms.

This paper presents a set of nonlinear differential equations to model a piezoelectric energy harvesting (PEH) system with a full-bridge waveform rectifier (FWR) under arbitrary base excitations. The PEH comprises a piezoelectric element modeled as a current source with a capacitor in parallel, which are connected with an inductor and a resistor. The inductor is proposed to smooth the current generated by the piezoelectric element under rapid mechanical variations and improve the convergence of the set of differential equations. The equations are obtained using piecewise linear modelling for the diodes. The main advantage of this piecewise linear modelling is considering different bias points to represent the nonlinear characteristics of real diodes. Numerical simulations are employed to obtain the optimum inductor value through a comparison with an analytical result, validated with experimental tests. A real case of random acceleration in a bike is applied to the PEH-FWR to evaluate the performance of the proposed equations. They are validated with experiments, a LTspice formulation and a numerical previous one. The proposed formulation can estimate the output DC voltage and energy for a large range of excitation frequencies, including resonant and nonresonant conditions and arbitrary or harmonically externally excited PEHs with FWR.

Considering the ever-increasing human need for energy resources and on the other hand, the reduction of fossil fuel resources, the use of renewable energy has become one of the attractive topics of researchers. One of the available and ambient sources in nature is mechanical energy in nature, such as the energy of body movements, wind energy, energy in sea waves, etc. One of the methods of converting and extracting energy from the mentioned forms is the use of triboelectric nano generators. Triboelectric nanogenerators have various structures. In the current research, the contact mode and two electrodes of triboelectric nanogenerators have been discussed and also the relationships governing the nano generator have been calculated. By comparing the response of the nano generator in ideal and non-ideal state, it can be understood that considering the effects of edge capacitors will be effective on the final response of the nano generator. Finally, the effect of various parameters on the performance of the triboelectric nano generator has also been investigated.

The electrolysis of renewable energy to produce hydrogen has become a strategy for supporting a decarbonized economy. However, it is typically not cost-effective compared to conventional carbon-emitting methods. Due to the predicted intermediate of low-and zero-marginal-cost renewable energy sources, the ability of electrolysis to connect with electricity pricing offers a novel way to cost reduction. Moreover, renewables, particularly photovoltaics, have a deflationary effect on the value of the grid when they are deployed. This study investigates solar electrolysis configurations employing photovoltaic cells to feed a proton exchange membrane water electrolyzer for hydrogen production. Using experimental meteorological data at 1-min precision, the system has been evaluated in Baghdad, the capital of Iraq. Positioned at the yearly optimum tilt angle for the selected site, the solar array is rated at 12 kWp. Temperature effects on solar module energy loss are taken into account. Several electrolyzers with capacities ranging from 2 to 14 kW in terms of hydrogen production were examined to determine the efficacy and efficiency of renewable sources. MATLAB was utilized for the simulation procedure, with a 2021–2035 project lifespan in mind. The results suggest that a variety of potentially cost-competitive options exist for systems with market configurations that closely approximate wholesale renewable hydrogen. At 4313 h of operation per year, the planned photovoltaic array generated 18,892 kWh of energy. The achieved hydrogen production cost ranges between $5.39/kg and $3.23/kg, with an ideal electrolyzer capacity of 8 kW matching a 12 kWp photovoltaic array capable of producing 450 kg/year of hydrogen at a cost of $3.23/kg.

Globally, Solar Power (SP) is generated by employing Photovoltaic (PV) systems. Accurate forecasting of PV power is a critical issue in ensuring secure operation along with economic incorporation of PV in smart grids. For providing an accurate forecasting model, various prevailing methodologies have been developed even then, there requires a huge enhancement. Thus, for Solar Power Generation (SPG) forecasting with deviation analysis, a novel Strengthen Gaussian Distribution-centric Deep Long Short Term Memory (SGD-DLSTM) methodology has been proposed here. Firstly, the PV modelling is formulated. After that, as of the PV, the data is gathered; likewise, for the deviation analysis, the historical data is gathered. Next, the pre-processing is performed; this stage undergoes two steps namely the Missing Value (MV) imputation and the scaling process. Afterwards, the features pertinent to the weather condition along with SP are extracted. After that, by utilizing the Intensive Exploitation-centric Shell Game Optimizer (IESGO) algorithm, the significant features are selected as of the features extracted. Then, the SPG is predicted by inputting the selected features into the SGD-DLSTM classifier. Next, by computing the Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE) measures, the predicted outcome’s deviation is assessed. In the experimental evaluation, by means of these measures, the proposed system’s performance is contrasted with the conventional techniques. Therefore, from the experimental assessment, it was established that the proposed model exhibits better performance than the prevailing research works. When analogized to the prevailing methodologies, a better accuracy of 97.25% was attained by the proposed system.

This numerical investigation is made to estimate the effect of Al 2 O 3 and Cu nanofluids on heat transfer rate, friction factor and thermal performance factor of a shell and tube heat exchanger. Mass flow rates of shell side (water) fluid are varied. Water based nanofluids are used inside the tubes with 0.01, 0.03, and 0.05% volume concentrations of Al 2 O 3 and Cu nanofluids. Nusselt number obtained from the present investigation is compared with Dittus–Bolter equation and Pongjet Pomvonge et al. and found to be in good agreement with a maximum deviation of 3%. The Nusselt number of the dispersed nanofluids increased with the increase of nanofluids volume concentrations and shell side mass flow rate. In this study, maximum enhancement in Nusselt number is 7.50%, 8.65%, and 9.61% for Al 2 O 3 , and 1.46%, 2.23%, and 3.18% for Cu nanofluid respectively at 0.01, 0.03, and 0.05% volume concentrations were compared to base fluid as water. Friction factor is highest by 58.00% at 0.05% volume concentration of Cu/H 2 O nanofluid when relate to Al 2 O 3 /H 2 O nanofluid. Thermal Enhancement factor achieved is highest for Al 2 O 3 /H 2 O nanofluid.

The output of Solar Panels is directly dependent on the intensity of direct Sunlight that is incident on the panels. But this efficiency reduces due to shadow effects for rooftop-mounted panels. These shadows can come from other solar panels, nearby buildings, or high-rise structures. It is possible to optimize Maximum Power Point Tracker (MPPT) controllers, which draw the most power possible from PV modules by forcing them to function at the most efficient voltage to increase the output of solar panels even while they are in the shade. Thus, the MPPT analyses the output of the PV module, compares it to the voltage of the battery, and determines the best power the PV module can provide to charge the battery. It then converts that power to the optimum voltage to allow the battery to receive the maximum level of currents. Additionally, it can power a DC load linked directly to the battery. Existing shadow detection and MPPT control models are highly complex, which increases their computational requirements, thereby reducing the operating efficiency of the solar panels. This text discusses a novel Saliency Map-based low-complexity shadow detection model for Solar panels to overcome this issue. The proposed model initially extracts saliency maps from connected Solar panel configurations and evaluates the background for the presence of shadows. Based on the intensity shadows, the model tunes MPPT parameters for optimal voltage & current outputs. Due to this, the model can maximize Solar panel output by over 8.5%, even under shadows, making it useful for various real-time use cases.

With the rapidly growing population, energy demand is increasing. The power supply to consumers must be free from distortions. By injecting voltage in quadrature with line current and varying the magnitude, the SSSC offers series compensation to the line. The injected voltage, which offers the effect of inserting an inductive or else capacitive reactance in series with the transmission line, is in quadrature with the line current. Using MATLAB/Simulink software, a phasor model of a 2-machine device with SSSC integration and POD as a subsidiary controller is simulated in this paper to evaluate efficient power flow regulation. The simulation has been used to study the time domain behavior of SSSC under normal and faulty conditions. The SSSC is implemented for correcting the voltage and analyzing power responses during a low voltage fault in the power system, whereas in normal conditions, the power system’s voltage stability for maintaining steady acceptable voltages at every bus is analyzed. It has been revealed that POD controller assists SSSC by supplying the reference voltage signal to damp out the low frequency power oscillations. The objective of this study is to reduce the crest outreach and clearing time during the fault thus improving the transient stability.