Useful Electrical Energy Research Articles

Performance Evaluation of a Commercial Greenhouse in Canada Using Dehumidification Technologies and LED Lighting: A Modeling Study

In this study, a lumped parameter model, developed and extensively validated by the authors, is used to simulate the impact of three different dehumidification technologies (mechanical refrigeration dehumidifier, liquid desiccant dehumidifier, and a heat recovery ventilation unit), at a commercial greenhouse growing potted roses in southwestern Ontario, Canada. Typical meteorological year (TMY) data from nearby Vineland, Ontario was used to provide the external weather data used in the model. Each greenhouse bay containing a dehumidification unit was simulated for spring, fall, and winter conditions. The potential reductions in energy use (kWh), greenhouse gas emissions (kg CO2e), and operating cost were estimated for each test case. The potential energy savings from switching from high-pressure sodium (HPS) to light-emitting diode (LED) lights were also examined. The simulation results showed that switching to LED lamps could reduce the electrical energy usage by up to 60% but would increase the space heating requirements. The expected energy-savings from using dehumidification equipment and switching from HPS to LED lighting in Canadian greenhouses is underrepresented in the literature. With the industry growing in the region, this study provides insight into the expected impact that these systems will have on the energy use in commercial greenhouses.

The Application of Energy Management Systems Using the Internet of Things to Improve the Efficiency of Electrical Energy Usage in the MSMEs Sector

Monitoring the electrical energy of the MSME sector is necessary because the current use of electricity is less effective and consumes more electrical power. The use of electrical power can only be seen through the kWh meter measuring instrument and only shows the cumulative amount of electrical energy used. The analog panel design constraint only displays aggregate consumption data, not real-time. This study aims to develop an energy management system through Internet of Things communication for monitoring and controlling electrical devices in MSME sector buildings. Designer of a real-time measurement system that can read the parameters of the amount of electricity consumed so that MSME users can monitor the use of electricity consumption quickly and accurately via the internet and become a solution for more efficient monitoring work. The monitoring system is designed for load groups in buildings by using the ESP32 NodeMCU as a data processor for data received from the PZEM-004T sensor and sent directly to the Blynk server so that the data can be monitored and controlled on the Blynk interface via a smartphone. The data displayed on the Blynk application is in the form of voltage (volts), current (amperes), power (watts), electrical energy (kWh), and electricity usage rates in rupiah in real-time. The results of the study obtained show that the proposed method can read the energy consumption data of the electrical load used with an error value of 0.54% in voltage measurement and an error value of 2.93% in current measurement and has a delay in sending data to the monitoring application of an average of 3 seconds. The proposed draft Energy Management System can improve electricity efficiency if applied to solve the problem of electrical energy consumed in MSME sector buildings.

Centralized controlling of distributed PV systems using cloud and IoT technologies

Usage of electrical energy obtained from renewable sources is rapidly increasing. Distributed solar systems will be widely used. The photovoltaic (PV) systems can be used to produce active and reactive power or to compensate reactive power. This paper proposes a solution for monitoring and management of distributed PV systems from the integrated center. The main parts of the system are a cloud infrastructure at the Data Center and Internet of Things (IoT) devices at distributed sites. Also, networks that are used for communication between main parts are an important piece of the proposed solution. While IoT devices continuously send information about electrical parameters of the system and environmental conditions, the inverter, as a part of the PV system, can be controlled by influencing the Maximum Power Point Tracking (MPPT) algorithm operation and inverter functionality.

Pyroelectric catalytic performance of Sm3+-modified Pb(Mg1/3Nb2/3)O3-PbTiO3 for organic dyes: degradation efficiency, kinetics and pyroelectric catalytic mechanism.

The development of photocatalysis is hindered, in part, by the quick recombination of photogenerated carriers and the instability of light sources. In this study, the problem of too-fast electron-hole pair compounding in photocatalysis is effectively regulated by the polarization field of pyroelectric materials using the pyroelectric method. Self-polarized pyroelectric materials that depend on temperature variations can generate usable electrical energy and polarized charge carriers to degrade organic pollutants. Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT) is a relaxor ferroelectric material with spontaneous polarization characteristics. The PMN-0.30PT:1 mol%Sm3+ catalyst was prepared by applying the high-temperature solid-state reaction method. Under the dark condition and nine cold-hot cycles of 23 °C-68 °C, using H2O2-assisted PMN-0.30PT:1 mol%Sm3+ as a catalyst, the degradation rate of rhodamine 6G (10 mg L-1) was 94.3 ± 2.5%. In addition, the degradation rates of 88.52% and 64.32% were obtained for rhodamine B (10 mg L-1) and methylene blue (10 mg L-1), respectively. This study provides a new approach to the pyroelectric catalytic degradation of organic pollutants.

A Case Study on Potential Saving of Energy Consumption at Hospital Putrajaya

Efficient electrical energy usage has been recognised as one of the significant factors to reduce the cost of electrical energy consumption. In this world, hospitals are public buildings that use the enormous energy of other buildings. Due to its 24 hours service, the use of hospital building energy is estimated to be among the highest compared to commercial and residential buildings. In this research, the main building of Putrajaya Hospital has been selected. The main building covered by the first floor until the fifth floor will be focused to conduct this research. This research aims to identify energy consumption, cost savings and the provision of solutions to achieve the cost savings target of Putrajaya Hospital. The characteristics and location of the building were recognised at the beginning of the research. Besides, this study was continued by identifying the lighting system presented at Putrajaya Hospital and the electricity tariff published by Tenaga Nasional Bhd. The calculation of energy consumption and cost for each floor of the main building, starting from the first floor to the fifth floor proposed the energy saving method. Four potential savings methods are proposed later in this research which include the switch to LED lighting saving potential, occupancy sensor, regular maintenance, and reduce light operation hour by using the alternate system. The result was found that energy consumption can be reduced up to 73.38% by switching the current lamp to LED lamp.

DESIGN A MONITORING SYSTEM OF A SINGLE-PHASE ELECTRICITY METER BASED ON THE INTERNET OF THINGS

This research aims to create systematic monitoring of a single-phase electricity meter that is accompanied by power monitoring features, the amount of electrical energy usage costs and relay control features using internet connections. The design has been carried out using PZEM-004T current and voltage sensors. The microcontrollers have been implemented by using ESP8266. This configuration is to reduce separate micro-controller. The embedded microcontroller and WiFi are made improvements from previous research. This embedded microcontroller is used to send data to the internet through WIFI. This monitoring system can then be accessed using the Cayenne interface. The test results of this tool show that the connection between the microcontroller and the Cayenne application works well through an internet connection. With this tool, users can see real-time data on the use of electrical energy and its cost, as shown in the cayenne dashboard. The voltage sensor test results show an average accuracy is 99.17%. The current sensor testing has an average accuracy rate of 96.9%. On average, the wattage delta between the cayenne dashboard and multimeter measurement is 2.16 watts.

Self-powered liquid crystal lens based on a triboelectric nanogenerator

Liquid crystal (LC) is an intermediate state compound between liquid and crystal, which has the anisotropy of crystal molecules while having the fluidity of liquid. It is a cutting-edge technology in optoelectronics. The large-aperture LC lens require larger voltages, and there are certain safety issues and equipment requirements. This situation indicates a great need for a safe and portable low-power device. A triboelectric nanogenerator (TENG) can collect the energy in the environment and convert it into usable electric energy. It has the advantages of small size and convenient portability, and can realize the use of renewable energy. This paper proposes a novel feather TENG (F-TENG) using feathers as friction materials. The approximate values of open-circuit voltage and short circuit current of the manufactured F-TENG can reach 247 V and 27 μA, respectively. After simple processing of the device, the performance can be further improved. We realized the use of F-TENG to power a LC lens test system, thus providing a new application idea for the display field. This study provides a simple and inexpensive method for harvesting mechanical energy to power experimental test equipment and facilitate the large-scale, intelligent practical application of TENG systems.

Optimization of furnace working index

The need for high quality product has necessitated the scientists to put in more effort to produce metal of high quality at lower price. This job considered the possibility of optimizing the product and brings out the product at cheaper price. Nigeria as a developing country needs metal for different purpose like construction of roads, houses, bridges, and other infrastructure. Defined parameters of optimum work of EAF-50 comparing with the basic variant expenditure by limit has reduced by 33% (from 41,1 to 28,2 Ruble\ton) Relative usage of electric energy by 51% (from 0,5463 to 0,2669 mw Hour/ton) Hour productivity rose by 74% (from 71,17 to 123,61 ton/hour).

Installation and Performance Study of a Vertical-Axis Wind Turbine Prototype Model

Amongst various sources of renewable energy, the kinetic energy of blowing wind has environmental friendliness and easy availability, together with other benefits. The wind energy is converted into usable electrical energy by means of a robust device termed a wind turbine. To carry out a performance study of such a device, a small-scale model vertical-axis wind turbine was installed at the laboratory and was run by artificial wind energy produced by a pedestal fan for low and medium speeds and a blower for higher speeds. The variation in critical parameters such as output power and voltage with different speeds was studied. The average output power and voltage were observed to increase with average shaft speed with linear and curvilinear patterns, respectively. The vibration produced at the bearing shaft resulting from the rotating components was analyzed as well. As observed, the peak values of critical vibration parameters such as displacement, velocity, acceleration, and frequency mostly varied curvilinearly with average shaft speeds. To study the applicability of the power generation, an electronically controlled automatic drip irrigation system was allowed to run by the wind turbine and important observations were made. Theoretical analyses (numerical and analytical) of the wind flow and power generation were also performed.

RANCANG BANGUN DC-DC CONVERTER TERKENDALI DALAM SISTEM PENGISIAN BATERAI PADA MODUL PEMBANGKIT LISTRIK TENAGA BAYU (PLTB) BERBASIS FUZZY

The wind is one of the new renewable energy sources that can be used as a source of electrical energy. But the wind in nature has a speed that varies greatly with each time and place. This can be overcome by using the DC-DC Converter tool with a fuzzy method to produce a stable electrical voltage so that it becomes usable electrical energy. This tool uses a series of converters connected to the Arduino microcontroller. The DC-DC converter circuit in this study also uses a voltage sensor as feedback for the Fuzzy method to maintain the stability of the circuit output which varies from 2V-5V, so that it can maintain a voltage of 6.5V which is used as a 6V battery charging. This circuit has an average efficiency of 60% for the open-loop system and 63% for the closed-loop system.

MODIFIKASI SEPIC CONVERTER UNTUK PENGONTROLAN TEGANGAN KELUARAN BERBASIS LOGIKA FUZZY

Sun is one of the new renewable energy sources that can be used as a source of electrical energy that is available on the earth. But the sun in nature has a light intensity that varies greatly with each time and place. This issue can be overcome by using the Modification Sepic Converter tool with a fuzzy method to produce a stable electrical voltage so that it becomes usable electrical energy. This tool uses a series of converters connected to photovoltaics. The tool also uses a voltage sensor as feedback for the Fuzzy method to maintain a voltage of 21-23VDC to 48VDC.

PMMA Lens Arrays for Micro Concentrator Solar Cells Produced by Hot Embossing

The rising energetical needs of modern society have been increasingly pushing for the improvement in energy efficiency. Thin-film solar cell technology encompasses several types of devices whose purpose is to gather energy emitted from a luminous source and convert it into usable electrical energy for a variety of applications, particularly low-powered devices. Micro concentrator solar cells are promising devices to solve the materials availability problem and address the power conversion efficiency simultaneously. Since the energy conversion efficiency for this type of solar cell is not particularly high, it stands out to benefit greatly from using an optical concentrator element to increase the light intensity reaching the active surface. The micro-concentrator element is comprised of a micro-lens array, which can be manufactured by different technologies, such as polymer injection moulding, extrusion, or hot embossing. In this work, we explore how hot embossing can be used to inexpensively produce spherical lenses with Ø 1 mm in an array according to micro concentrator solar cell requirements. A simple compression system coupled with an infrared lamp heat chamber was used to emboss PMMA disks. Different mould insert manufacturing technologies were used and different hot embossing parameters were assessed. The process replicability of the micro-lens cavities was determined by infinite focus microscopy and optical microscopy. The most promising lens array was achieved with a mould insert produced by μ-EDM (with Ra and Rz values of 0.6 μm and 4.58 μm, respectively).

Comparison of robust machine-learning and deep-learning models for midterm electrical load forecasting

Electrical load forecasting (ELF) is gaining importance especially due to the severe impact of climate change on electrical energy usage and dynamically evolving smart grid technologies in the last decades. In this regard, medium-term load forecasting, a crucial need for power system planning (generation optimization and outages plan) and operation control, has become prominent in particular. Machine learning and deep learning-based techniques are currently trending approaches in electrical load estimation due to their capability to model complex non-linearity, feature abstraction and high accuracy, especially in the smart power systems environment.
 In this study, several load forecasting models based on machine learning methods which comprise linear regression (LR), decision tree (DT), random forest (RF), gradient boosting, adaBoost, and deep learning techniques such as recurrent neural network (RNN) and long short-term memory (LSTM) are studied for medium-term electrical load demand forecasting at an aggregated level. Performance metric results of these analyzes are presented in detail. State-of-the-art feature selection models are examined on the dataset and their effects on these forecasting methods are evaluated. Numerical results show that forecasting performance can be significantly improved. These results are validated by the results of other studies on the subject and found to be superior.

A collision-free gallop-based triboelectric-piezoelectric hybrid nanogenerator

Energy harvesting technologies that convert fluid energy into usable electrical energy are of great significance, especially in long-distance pipeline systems. Here, in order to avoid the collision of conventional galloping triboelectric nanogenerators (GTENGs), and cause material damage or noise, a freestanding gallop-based triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) is proposed to reduce material wear and improve the reliability of GTENG. Two piezoelectric sheets are attached to the cantilever beam. The root-mean-square (RMS) and peak output power of the HG P-TENG are 68.9μW and 1.27 mW, respectively. To improve the harvesting efficiency, the fixed copper electrodes are segmented, and experiments indicate that this way of segmenting electrodes can improve theenergy harvesting efficiency. Finer electrodes can effectively increase the charging rate of capacitors. A self-powered thermohygrometer and light-emitting diodes (LEDs) are demonstrated in the wind tunnel. It demonstrates that the proposed hybrid nanogenerator will exhibit great potential in pipeline systems.

Effect of Partial Shading on the Performance of Various 4×4 PV Array Configurations

Electrical energy usage has drastically increased in recent decades, resulting in significant demand for renewable energy sources, especially solar. With the development of technology, extracting energy from photovoltaic (PV) modules has become easier and more economical. The performance of PV array decreases under an intermittent environment such as partial shading conditions (PSCs), causing fluctuations in PV array power output. This paper presents the analysis of a 4×4 PV array configuration under different PSCs. The power output of PV array depends on factors such as the type of configuration, size of array, and shading patterns. The performance of various types of 4×4 PV array configurations under different shading situations are compared and analyzed in this study, and the results presented.

Frequency domain analysis of a piezoelectric energy harvester with impedance matching network

Abstract Piezoelectric energy harvesters are electromechanical systems, capable to convert ambient dispersed mechanical vibrations into usable electrical energy. They can be used for supplying power to sensors and actuators that are wireless connected, miniaturized and remote located. In this work, we analyze piezoelectric energy harvesters for mechanical vibrations in the frequency domain. White Gaussian and colored noise models for random vibrations are considered. The governing equations for the harvester are derived from mechanical properties, the characteristic relationships of piezoelectric materials, and circuit description of the electrical load. We show that the energy harvester can be modelled by cascade connected electromechanical two-ports, and that frequency domain methods are the perfect tool for analysis. Formulas for the harvested power and power efficiency are derived. We also show that application of matching networks reduces the impedance mismatch between the mechanical and the electrical parts, significantly increasing the harvested power and power efficiency. The matching network solution is compared to others, previously proposed solutions, such as application of power-factor correction. We show that the matching network offers nine times more average power and better power efficiency than the unmatched resistive load, and increases by more than 10% the harvested power and efficiency, with respect to the power-factor corrected solution.

Kinetic energy harvesting based sensing and IoT systems: A review

The rapid advance of the Internet of Things (IoT) has attracted growing interest in academia and industry toward pervasive sensing and everlasting IoT. As the IoT nodes exponentially increase, replacing and recharging their batteries proves an incredible waste of labor and resources. Kinetic energy harvesting (KEH), converting the wasted ambient kinetic energy into usable electrical energy, is an emerging research field where various working mechanisms and designs have been developed for improved performance. Leveraging the KEH technologies, many motion-powered sensors, where changes in the external environment are directly converted into corresponding self-generated electrical signals, are developed and prove promising for multiple self-sensing applications. Furthermore, some recent studies focus on utilizing the generated energy to power a whole IoT sensing system. These systems comprehensively consider the mechanical, electrical, and cyber parts, which lead a further step to truly self-sustaining and maintenance-free IoT systems. Here, this review starts with a brief introduction of KEH from the ambient environment and human motion. Furthermore, the cutting-edge KEH-based sensors are reviewed in detail. Subsequently, divided into two aspects, KEH-based battery-free sensing systems toward IoT are highlighted. Moreover, there are remarks in every chapter for summarizing. The concept of self-powered sensing is clarified, and advanced studies of KEH-based sensing in different fields are introduced. It is expected that this review can provide valuable references for future pervasive sensing and ubiquitous IoT.

Optimization of Furnace Working Index

The need for high quality product has necessitated the scientists to put in more effort to produce metal of high quality at lower price. This job considered the possibility of optimizing the product and brings out the product at cheaper price. Nigeria as a developing country needs metal for different purpose like construction of roads, houses, bridges and other infrastructure. Defined parameters of optimum work of EAF-50 comparing with the basic variant expenditure by limit has reduced by 33% (from 41,1 to 28,2 Ruble\ton) Relative usage of electric energy by 51% (from 0,5463 to 0,2669 mw Hour/ton) Hour productivity rose by 74% (from 71,17 to 123,61 ton/hour).

Enhancement of Biogas Production in Anaerobic Digestion Using Microbial Electrolysis Cell Seed Sludge

Anaerobic digestion (AD) can produce renewable energy and reduce carbon emissions, but the energy conversion efficiency is still limited in some waste streams. This study tested the effect of applied voltage removal for microbial electrolysis cells (MECs) treating primary sewage sludge. Two MECs were operated in parallel: a MEC-0.3 V with an applied voltage of 0.3 V and a MEC-OCV with open circuit voltage. Both reactors were inoculated with seed sludge originating from a MEC at 0.3 V applied voltage, and three batch cycles were operated for 36 d. The methane production of the MEC-OCV was 3759 mL/L in the first cycle and 2759 mL/L in the second cycle, which was similar (105% and 103%, respectively) to that of the MEC-0.3 V. However, in the third cycle, the methane production of the MEC-OCV (1762 mL/L) was 38.8% lower than that of the MEC-0.3 V (4545 mL/L). The methane contents in the biogas were 68.6–74.2% from the MEC-OCV, comparable to those from the MEC-0.3 V (66.6–71.1%). These results indicate that not only the MEC-0.3V but also the MEC-OCV outperformed AD in terms of methane yield and productivity, and the promotion using MEC-derived inoculum persisted equally with the MEC-OCV for two batch cycles after removing the applied voltage. Therefore, a MEC operation with cycled power supply may be beneficial in reducing the electric energy usage and improving the biogas production performance, compared to conventional AD.

Literature Review of Energy Management in Combined Heat and Power Systems Based on High-Temperature Proton Exchange Membrane Fuel Cells for Residential Comfort Applications

Combined heat and power technologies represent an efficient way to ensure energy efficiency, as they promote usage of both electrical and thermal energy, something not done by most traditional energy sources, especially in residential environments. In this context, high-temperature proton exchange membrane fuel cells allow the implementation of combined heat and power systems. Additionally, in this environment, fuel cells are more efficient and less polluting than their traditional counterparts. We present a literature review of energy management in residential systems based on this type of fuel cell. In addition, we classify and detail the current state of fuel cell technologies, paying special attention to their characteristics, mathematical modelling and control, as well as combined heat and power systems and energy management strategies.