Large Amounts Of Electric Power Research Articles

Penggantian Halogen ke LED pada Runway Edge Lights Bandara Ahmad Yani Sebagai Efesiensi Energi Listrik

Jenderal Ahmad Yani International Airport is an airport located in the West Semarang District, Semarang City. This airport has departure and arrival terminals that facilitate domestic and international flights. Ahmad Yani International Airport also has a runway (13-31) with a length of 2,560 meters. There is airport lighting system equipment whose function is to assist and serve aircraft taking off and landing so that they can operate in cloudy, cloudy weather and at night in the runway, taxiway and apron areas. One of the equipment in the airport lighting system is the runway edge lights. Currently, the runway edge lights installed at Jenderal Ahmad Yani International Airport still use halogen type lights, which require quite a large amount of electrical power and the electricity costs incurred are not small. Replacing halogen type runway edge lights with Light Emitting Diode (LED) runway edge lights as an effort to efficiently use electrical energy. In this study the author used a comparative method to determine the comparison of the efficiency of using electrical energy between the two types of LED runway edge lights and halogen runway edge lights. From the comparison data carried out, it can be concluded that replacing halogen runway edge lights with LED runway edge lights has been proven to increase the efficiency of electrical power usage over a long period of time. From the specification data, LED lamps have a longer life time, namely 56,000 hours compared to halogen lamps, which is only 1000 hours, so the savings are also greater. From power calculations, it can be seen that LED runway edge lights have more power efficiency than halogen runway edge lights. The total power of halogen runway edge lights (2 circuits) was 21,480.58 watts, while LED runway edge lights (2 circuits) decreased by 56.2% to 9,400.58 watts.

New generation B-Field and RAD-tolerant DC/DC power converter for on-detector operation

The increase in the number of readout channels in new detectors, like the Micro Pattern Gas Detectors (MPGD), in the order of several millions, requires a large amount of electrical power to supply the front-end electronics, up to hundreds kW. If this power is generated at long distances from the detector, the voltage drop on the connection cables puts serious constraints to the supply current, to the wire cross-section and to the power distribution. A large amount of voltage drop on the cables, apart an increased power dissipation on wire resistance, determines regulation issues on the load in case of current transients. To mitigate these problems, a new generation DC/DC converter, working in a heavily hostile environment and with a power density greater than 200 W/dm3, was developed. It is modular, with up to four independent modules, eight channels each, collected in a water-cooled crate, and can supply the load with an adjustable 10 to 12 V output up to 170 W per channel. In this contribution, the design constraints of such a converter are analysed, taking as a basis the environmental, electrical and mechanical requirements of the ATLAS New Small Wheel (NSW) project. Thermal considerations require the converter to be water-cooled, and the dimensional constraints impose the adoption of an innovative design to convey the dissipated heat towards the heat exchanger. The control and monitoring system allows for the full remote management of the converter. Main electrical parameters were measured and are reported. The converter was also characterized in a harsh working environment, with radiation tests in the CERN CHARM facility beyond the limits estimated for ten years operation in ATLAS, and with magnetic field tests in various orientations, using different magnets at CERN up to 1.3 T. A better common mode noise filtering design improvement was implemented after the first characterization. Final performance measurements after the modifications are also reported.

Combined heating and power generation performance of thermal station for electricity self-sufficient characterized by two-stage heat transfer

As the living standard improves, the demand for space heating has been increasing, leading to global warming and environmental problems. The thermal station consumes a large amount of electric power. A novel electricity self-sufficient thermal station based on the organic Rankine cycle (ORC) is proposed using the primary heating network supply water as the heat source and the secondary heating network return water as the heat sink. The mathematical model is established based on the laws of thermodynamics, and the performance of combine heating and power is numerically analyzed under the design condition. The results show that the power generation performance is directly proportional to the primary heating network supply water temperature. However, the power output of ORC is at the expense of reducing the same amount of heating capacity of secondary heating network. The novel self-sufficient thermal station in electric power lowers the irreversible loss of heat transfer between the primary and secondary heating networks to construct cascade heat transfer, therefore recovering the potential power generation being ignored and realizing the self-sufficient supply of electric power.

Finite Element Simulation and Sensitivity Analysis of the Cohesive Parameters for Delamination Modeling in Power Electronics Packages.

Delamination is a critical failure mode in power electronics packages that can significantly impact their reliability and performance, due to the large amounts of electrical power managed by the most recent devices which induce remarkable thermomechanical loads. The finite element (FE) simulation of this phenomenon is very challenging for the identification of the appropriate modeling tools and their subsequent calibration. In this study, we present an advanced FE modeling approach for delamination, together with fundamental guidelines to calibrate it. Considering a reference power electronics package subjected to thermomechanical loads, FE simulations with a global-local approach are proposed, also including the implementation of a bi-linear cohesive zone model (CZM) to simulate the complex interfacial behavior between the different layers of the package. A parametric study and sensitivity analysis is presented, exploring the effects of individual CZM variables on the delamination behavior, identifying the most crucial ones and accurately describing their underlying functioning. Then, this work gives valuable insights and guidelines related to advanced and aware FE simulations of delamination in power electronics packages, useful for the design and optimization of these devices to mitigate their vulnerability to thermomechanical loads.

Ag Dendrites on W/C as Enhanced Active and Stable Electrocatalysts for Scalable Solar-Driven CO2rr

The electrochemical conversion of solar energy into competent chemicals is the most efficient technique to ensure clean and sustainable energy source for society in the future. In fact, solar cells can electrochemically produce electricity without pollution by converting CO2 into a variety of chemicals. The carbon dioxide reduction reaction (CO2RR) is an environmentally friendly approach to produce useful hydrocarbons such as carbon monoxide (CO), methane, ethylene, formates, etc and alcohols and remove exhausted CO2, which is a greenhouse gas. Conventionally, studies on the CO2RR have been conducted by using liquid-phase H-cells and a CO2-saturated electrolyte. However, it resulted in a low current density because the low solubility of CO2 in the liquid electrolyte occurs mass transfer limitation. To improve of the current density related to the CO2RR, two types of gas-fed CO2RR electrolyzers containing gas diffusion layer (GDL) electrodes have been proposed. The first type of CO2RR devices use a liquid electrolyte, the electrolyte increases CO2RR performance through controlling the cathode conditions, such as pH and anion concentration. The second type of CO2RR devices is zero-gap electrolyzers that use an anion exchange membrane (AEM) and humidified CO2 gas. AEM transmits carbonate and hydroxide ion, inducing favorable environmental for CO2RR. These zero-gap CO2 electrolyzers are attracting attention as the most promising system owing to several advantages such as extremely low ohmic resistance, scalable and stackable configuration, and commercial applicability, as affirmed by using a system consisting of a fuel cell and water electrolyzer. Among the products of the CO2RR, CO is particularly attractive as aspect of its economic benefits and large demand. Ag-based materials exhibit the most electrochemical performance for producing CO. and high selectivity. To enhance the catalytic activity of Ag-based catalysts, various approaches have been studied to change the surface electronic structure of Ag such as alloy formation, anion-based modification, shape control, near-surface structure and engineering. However, catalyst designs that do not consider the gas phase reactions cannot enough utilize their catalytic activity although recent progress has made in the development of Ag-based catalysts for the CO2RR. Therefore, considerable efforts must be preoccupied with the development of highly active, stable, and gas-transferable structured catalysts for gas-fed CO2RR electrolyzers with incoporating a GDL. Additionally, aming for the realization of clean technology for producing CO, we demonstrate the practicalbility of sunlight-driven CO2RR on a large scale using commercial silicon-based solar cells and zero-gap electrolyzers. Silicon-based solar cells are still the preferred commercially applicapable options for producing large amounts of electrical power from solar energy because of their scalability. In this study, we report a 3D silver dendrite on W/C (as denoted WC@AgD) catalyst with abundant nanograin boundaries that show enhanced CO2RR performance and stability. WC@AgD exhibited marked catalytic activity with a maximum CO partial current density of 400 mA cm-2 and durability for 100 h at 150 mA cm-2. We also fabricated an solar-to-CO (STC) conversion device combined with a silicon-based solar cell of 120 cm2 area and a zero-gap CO2 electrolyzer with an area of 10 cm2. The stand-alone photovoltaic-electrochemical system achieved a solar-to-CO efficiency (ηSTC) of 12.1 % at 1A under AM 1.5 G illumination and realistic outdoor conditions. The device design and electrode configuration extended viable route for implementing large-scale installations for solar-driven production of chemicals. Figure 1

Sequential Data-Driven Long-Term Weather Forecasting Models’ Performance Comparison for Improving Offshore Operation and Maintenance Operations

Offshore wind turbines (OWTs), in comparison to onshore wind turbines, are gaining popularity worldwide since they create a large amount of electrical power and have thus become more financially viable in recent years. However, OWTs are costly as they are vulnerable to damage from extremely high-speed winds and thereby affect operation and maintenance (O&M) operations (e.g., vessel access, repair, and downtime). Therefore, accurate weather forecasting helps to optimise wind farm O&M operations, improve safety, and reduce the risk for wind farm operators. Sequential data-driven models recently found application in solving the wind turbines problem; however, their application to improve offshore operation and maintenance through weather forecasting is still limited and needs further investigation. This paper fills this gap by proposing three sequential data-driven techniques, namely, long short-term memory (LSTM), bidirectional LSTM (BiLSTM) and gated recurrent units (GRU) for long-term weather forecasting. The proposed techniques are then compared to summarise the strength and weaknesses of these models concerning long-term weather forecasting. Weather datasets (wind speed and wave height) are intermittent over different time scales and reflect offshore weather conditions. These datasets (obtained from the FINO3 database) will be used in this study for training and validation purposes. The study results suggest that the proposed technique can generate more realistic and reliable weather forecasts in the long term. It can also be stated that it responds better to seasonality and forecasted expected results. This is further validated by the calculated values of statistical performance metrics and uncertainty quantification.

Exploration of CO2 capture from blast furnace gas using (semi)clathrates

This paper aims to contribute to the search for sustainable solutions for CO2 capture from industrial processes such as steelmaking. This is realized by exploring possibilities of a CO2 capture from blast furnace gas using clathrates and comparing this technique to conventional absorption with monoethanolamine (MEA). First a design with pure clathrate hydrates was made to act as a reference and aid to construct a more detailed model for the semiclathrate tetra-n-butyl ammonium bromide (TBAB). Herein the capture process was modeled as a crystallization process in a bubble column like crystallization vessel. It was found that the TBAB process suffers mostly from the low capacity which requires high volume flows. Because of the low temperature, large amounts of expensive refrigerants are required (>300 MW). Because of the high pressure, a large amount of electrical power is required as well (>80 MW). Overall, the process as designed here cannot compete with the conventional MEA process. However, several options were identified that could improve the process in such a way that it could become more feasible. These include an apparently higher capacity than estimated and the use of more stable semiclathrates, hence reducing the need for expensive refrigerants.

Communication—Power Enhancement of Fabric Triboelectric Energy Harvesters Using Ultraviolet Light and Fluoro-Based Treatment

Triboelectricity is a self-powered phenomenon that has recently attracted attention because it is capable of instantaneously generating a large amount of electrical power. In this study, we developed a method to fabricate a fabric-based triboelectric energy-harvesting device and enhanced the output of this device using a Fluorinert coating and ultraviolet (UV)/ozone surface treatment. Through simple surface treatment processes, the electrical output of triboelectric self-generation device will be significantly increased, and at the same time, it will present the possibility of being naturally suitable for next-generation electric clothing products.

Modulation of Magnetorheological Fluid Flow in Soft Robots Using Electropermanent Magnets

Magnetorheological (MR) fluids, which stiffen in the presence of magnetic fields, have been shown to be an effective means for controlling the inflation of soft actuators. However, past efforts have largely focused on binary control. Proportional control schemes have faltered due to the difficulty in producing sufficient magnetic fields without requiring large amounts of electrical power. Electropermanent magnets (EPMs) offer one solution to this issue, since they can produce magnetic fields which are similar in magnitude to permanent magnets, they can be controlled electrically, but they do not require any power to hold their state. In this letter, we use EPMs to control the material properties of an MR fluid, allowing us to modulate the pressure within soft actuators. We demonstrate and quantify this behavior for several classes of soft actuators via bending and blocked force testing. We then demonstrate the ability to independently control the actuation of multiple-DoFs systems operating in both a binary and fully-modulated manner, thus providing an important step towards the development of reprogrammable, autonomous soft robots.

Design Considerations of Low Bypass Ratio Mixed Flow Turbofan Engines with Large Power Extraction

The possibility of extracting large amounts of electrical power from turbofan engines is becoming increasingly desirable from an aircraft perspective. The power consumption of a future fighter aircraft is expected to be much higher than today’s fighter aircraft. Previous work in this area has concentrated on the study of power extraction for high bypass ratio engines. This motivates a thorough investigation of the potential and limitations with regards to performance of a low bypass ratio mixed flow turbofan engine. A low bypass ratio mixed flow turbofan engine was modeled, and key parts of a fighter mission were simulated. The investigation shows how power extraction from the high-pressure turbine affects performance of a military engine in different parts of a mission within the flight envelope. An important conclusion from the analysis is that large amounts of power can be extracted from the turbofan engine at high power settings without causing too much penalty on thrust and specific fuel consumption, if specific operating conditions are fulfilled. If the engine is operating (i) at, or near its maximum overall pressure ratio but (ii) further away from its maximum turbine inlet temperature limit, the detrimental effect of power extraction on engine thrust and thrust specific fuel consumption will be limited. On the other hand, if the engine is already operating at its maximum turbine inlet temperature, power extraction from the high-pressure shaft will result in a considerable thrust reduction. The results presented will support the analysis and interpretation of fighter mission optimization and cycle design for future fighter engines aimed for large power extraction. The results are also important with regards to aircraft design, or more specifically, in deciding on the best energy source for power consumers of the aircraft.

A Lightweight Optimal Scheduling Algorithm for Energy-Efficient and Real-Time Cloud Services

To support ever-chainging user needs such as large storage volumes, web search, and high-performance computing, numerous companies have expanded their systems to cloud computing servers. Cloud environment systems generally consume large amounts of electrical power, leading to tremendously high operational costs. In addition, they require computing infrastructures to run various real-time applications such as financial analysis, cloud gaming, and web-based real-time services. To represent performance guarantees, the negotiated agreements in real-time computing, expressed as deadline (or latency), can be specified by <i>service level agreements</i> of cloud services between users and cloud server providers. Thus, a number of research works have started focusing on reducing the energy consumption and simultaneously satisfying the temporal constraint in a cloud environment. Although we previously proposed an optimal real-time scheduling algorithm for multiprocessors, it is difficult to use it for cloud environments handling a large number of cloud services because of the high computational complexity of <inline-formula> <tex-math notation="LaTeX">$\Omega (N^{3}logN)$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> is the number of tasks. Thus, we introduce a real-time task scheduling algorithm for cloud computing servers, which alleviates the computational complexity of <inline-formula> <tex-math notation="LaTeX">$O(N^{2})$ </tex-math></inline-formula> from the complexity of the previous algorithm using a novel flow network-based optimization method. To the best of our knowledge, our scheduling algorithm in a cloud environment, which ensures optimality for real-time tasks and achieves energy savings using dynamic power management simultaneously, is the first in the problem domain. We show that the proposed scheduling algorithm guarantees an optimal schedule for real-time tasks and achieves energy savings simultaneously. Our experimental results show that the proposed algorithm outperforms the latest existing algorithms in terms of both time complexity and energy efficiency.

Study on the Design and Operation of an Outdoor Air-Cooling System for a Computer Room

Due to the recent growth of the Internet and the rapid development of information and communications technology, the number of data centers and the amount of power consumed are expected to increase rapidly. However, these data centers consume large amounts of electric power throughout the year, regardless of working days or holidays; hence, measures to save energy at these facilities are urgently required. A numerical analysis was conducted in this study by changing various variables to examine the effects of various design and operating conditions on outdoor air-cooling systems and to derive some operating plans to minimize electric power consumption through the introduction of outside air into the computer room. When designing the system, it is desirable to select airflow considering various factors, such as the heat generated by the computer equipment, the efficiency of the fan, and the performance of the refrigerator, rather than the theoretical maximum outdoor airflow. As a result, the optimal design air volume was calculated according to the equipment load. Consequently, the optimal design air volume of the modeled computer system was obtained as 26,200 m3/h. The application of this optimal design air volume is expected to yield an annual energy-saving effect of 56.1% compared with the power consumption in the air-conditioning period during which the application of outdoor air cooling is impossible.

Evaluation of Wind Speed Potential Using Correlation Coefficient Model in Medan, North Sumatra, Indonesia

Medan is the capital city of North Sumatra Province, consisting of various tribes and a dense population that requires a large amount of electrical power. Energy demand continues to increase along with population and business growth, so that additional energy sources are needed; one of which is wind. An evaluation of the potential of wind energy sources is needed to determine the feasability of its use as an environmentally-friendly, renewable energy source without emissions.This paper aims to evaluate the potential wind speed in the city of Medan using the correlation coefficient (R2) model. The four application models proposed for the probability density function used are Normal Distribution, Lognormal, Weibull 2-parameters and Weibull 3-parameters. The analysis results show that the four models used are all potentially feasible options that can be used to evaluate the potential sources of wind energy in Medan. The potential of these models for use, ranked from most to least, are the Weibull 3-parameter Model, followed by the Lognormal, Normal Distribution and Weibull2-parameter. In addition to the analysis, the results of the Normal, Lognormal and Weibull Distribution tests are also presented.

Energy Pulsation Reduction in Modular Multilevel Converters Using Optimized Current Trajectories

In power electronics, the modular multilevel converter (MMC) is an easily scalable topology with an high output voltage quality. It is suitable for the transmission of large amounts of electrical power over long distances, which supports the realization of the ongoing energy transition. State-of-the-art methods require a comparatively large total cell capacitance in the system for energy pulsations during operation. In the present paper, in order to minimize this total capacitance, first a new method is developed to model the system, and second, by help of this model, optimal current trajectories are calculated. These currents are used for control to reduce the energy pulsation over the complete operating range, and thus, to better utilize the hardware. The new method independent on the Clarke transformations is implemented on a laboratory scale setup, and measurement results are presented which validate the new method. Furthermore, the new method is compared to the state-of-the-art method of the compensation of the 2nd harmonic and outperforms the latter significantly. This applies to the entire operating range for different power factors. A total reduction of up to 44% of the energy pulsations is achieved.

Pengembangan Perangkat Lunak Untuk Analisis Aliran Beban Tiga Fasa Pada Jaringan Tegangan Rendah Dengan Metode Newton Berbasis Calculus Wirtinger

AbstractLoad flow analysis is a study to plan and determine the amount of power in an electric power system. During its development, industry requires a large amount of electric power and uses electrical equipment as a means of production. The benefits of an electric load flow analysis are to find out the amount of power in the electric power system whether it still meets predetermined limits, and to find out the amount of voltage at each point, and to obtain initial conditions for the new system planning. Load flow analysis begins calculating the active power and reactive power at each node (bus) installed, loading on the channel or conductor, the load flow calculation will be assisted using the Julia program. From the results of calculations using the Julia program, the voltage at each point with the smallest stress is obtained, namely the 10th point of 209.89 - j10.34V for phase A, -107.39 - j186.87V for phase B, -108.12 + j178,51V for phase CKey Words: Drop Voltage, Julia, Load Flow

Artificial Intelligence: An Energy Efficiency Tool for Enhanced High performance computing

Power-consuming entities such as high performance computing (HPC) sites and large data centers are growing with the advance in information technology. In business, HPC is used to enhance the product delivery time, reduce the production cost, and decrease the time it takes to develop a new product. Today’s high level of computing power from supercomputers comes at the expense of consuming large amounts of electric power. It is necessary to consider reducing the energy required by the computing systems and the resources needed to operate these computing systems to minimize the energy utilized by HPC entities. The database could improve system energy efficiency by sampling all the components’ power consumption at regular intervals and the information contained in a database. The information stored in the database will serve as input data for energy-efficiency optimization. More so, device workload information and different usage metrics are stored in the database. There has been strong momentum in the area of artificial intelligence (AI) as a tool for optimizing and processing automation by leveraging on already existing information. This paper discusses ideas for improving energy efficiency for HPC using AI.

Evaluation of a solar-powered absorption cooling system to a data center

Nowadays, data processing is a fundamental operation for modern businesses such as banks, technology companies, and factories, among others. However, computers dissipate significant amounts of heat yielding to an operational temperature rise. Considering that these machines cannot operate properly in inappropriate temperatures or at extreme conditions, they can come to a stop due to overheating. Consequently, cooling and air-conditioning systems are necessary to keep the proper operating temperature as well as the room temperature itself. On the other hand, a data center air-conditioning system drains a large amount of electrical power. Based on this, this paper evaluates a solar-powered absorption cooling system to assist the traditional electric chiller system resulting in energy saving, an advantage over conventional cooling, and day availability for this system. A case study is analyzed in a conventional data center located in the city of Sao Paulo, Brazil. First, the electric power density consumed by computers is 2.0 kW/m2, which represents a typical power load of an IT room. In addition, some other power density cases are also analyzed, namely: 0.5, 1.0, 4.0, and 8.0 kW/m2; these would occur at partial or at high operational loads. Local solar irradiation indexes are based on ASHRAE temperature and solar data for that city. The results are valid for a typical year and are compared to (1) a conventional data center and (2) the event combined with the solar-powered cooling system.

A missing power data filling method based on improved random forest algorithm

Missing data filling is a key step in power big data preprocessing, which helps to improve the quality and the utilization of electric power data. Due to the limitations of the traditional methods of filling missing data, an improved random forest filling algorithm is proposed. As a result of the horizontal and vertical directions of the electric power data are based on the characteristics of time series. Therefore, the method of improved random forest filling missing data combines the methods of linear interpolation, matrix combination and matrix transposition to solve the problem of filling large amount of electric power missing data. The filling results show that the improved random forest filling algorithm is applicable to filling electric power data in various missing forms. What's more, the accuracy of the filling results is high and the stability of the model is strong, which is beneficial in improving the quality of electric power data.

A solid-state wind-energy transformer

We show that a solid-state apparatus with no moving parts can harvest electrical power from the wind. This apparatus, a Solid-state Wind-Energy Transformer (SWET), uses coronal discharge to create negative air ions, which the wind carries away from the SWET. The SWET harnesses the wind-induced currents and voltages to produce electrical power. We report on the operation of a low-power, proof-of-concept SWET. This device consists of a number of parallel electrical wires: “emitter wires,” which have numerous, sharp coronal emitters attached to it, and bare “attractor wires.” When a negative bias voltage is applied to the emitter wires relative to the attractor wires, the coronal emitters generate negative ions. The wind carries off these ions, which eventually settle to ground. The power imparted to the ions by the wind is extracted from the current returning to the SWET from the ground. This proof-of-concept SWET demonstrates that it is possible to generate net electrical power from the wind using only air ions. We estimate that SWET can be scaled up to commercially interesting powers by increasing the number and length of emitter and attractor wires and by controlling the bias voltage. SWETs have the potential to produce large amounts of electrical power at low costs with little negative environmental impact.

MMC as nonlinear vector current source for grid connection of wave energy generation

Modular multilevel converter (MMC) is a type of electronic converter currently used as voltage source in real HVDC transmission systems. This paper presents, as an alternative, a control system designed to operate an MMC as a nonlinear vector current source (NLVCS). From the design point of view, it features advantages such as constant switching frequency, robustness against grid parameters changes and that the algorithm is entirely designed from space vectors. From the application point of view, the main advantages are its fast dynamic response combined with its capability to handle large amounts of electric power. Together, these two features allow the MMC to deal with highly variable renewable energies.To show the advantages of the proposed control system, it has been chosen a very demanding application: wave energy. In this type of applications, the random nature of the sea produces large and fast variations of the generated power, that enters the DC link and that the grid side converter has to handle very fast, injecting it into the grid in order to maintain the DC voltage constant.The capability of the NLVCS for MMC to handle the energy generated has been tested in two different wave energy applications. Firstly, on a single wave energy converter (WEC), a point absorber. This case is characterized by smaller and faster power changes. Secondly, on a wave farm made up of 200 WECs connected to the grid through an MMC. This case is characterized by much larger but smoother power changes.Wave farms, WECs and MMC are large and sophisticated facilities or devices that are almost impossible to gather in the same laboratory. Consequently, the features of the new control system for MMC and the advantages that provide in the connection of wave energy power plants and point absorbers to the grid has been simulated using detailed models.The results demonstrated the capability of the MMC operating as NLVCS to deal with the fast and random power changes present in renewable energy sources.