Comparative presentation of criteria for adaptive finite-element mesh generation in multiconductor eddy-current problems

With an average herd size of 113 mature cows, Cayuga County is home to 280 dairy farms and 31,500 dairy milking cows producing approximately 855 million gallons of milk per year. The Cayuga Dairy industry is a major contributor to the countys economy, employing nearly 1200 people, while generating $140,000,000 of revenue from sale of milk alone. At the same time, the Cayuga County dairy industry also produces 5.7 million gallons of manure daily: (a) Nearly 34% of this manure is produced on smaller farms. (b) Digesters are expensive pieces of equipment and require attention and care. ( c) The on-farm digester systems have fairly long payback (>10 years) even for larger CAFO farms (>1000 milking cows). In 2005, Cayuga County Soil and Water Conservation District (The District), a Public Agency under Cayuga County, decided to undertake a centralized community digester project. The primary goal of the project was to develop an economically sustainable model, under the auspices of The District to address manure management issues facing the smaller dairies, improve the water quality and improve the quality of life for Cayuga County residents. It is believed that the District has accomplished this goal by completing construction of Cayuga County Regional Digester on a parcel of land behind the Cayuga County Natural Resource Center located at 7413 County House Road in the Town of Sennett in Cayuga County, New York. The digester facility consists of the following major components. 1. Transfer Station: This an indoor truck bay, where 35,000 gallons of manure from three local farms, 8,500 gallons of liquid organic food-processor waste, and 1,200 gallons of brown grease are unloaded from tanker trucks and the digested slurry is loaded onto the tanker trucks for delivery back to the participating farms. 2. Anaerobic Digester: The project utilizes a hydraulic mix anaerobic digester, a unique design that has no internal moving parts for mixing. The digester, which operates at mesophilic temperatures, is designed to process the daily feedstock and produce 220,000 SCF2 of biogas per day. The digester also produces 44,000 gallons of digested slurry per day. 3. Biogas Conditioning System: The plant employs a biological biogas conditioning system to remove the H2S and moisture contents of the biogas and prepare it to be used by the plant generation system. 4. Combined Heat and Power System (CHP): This is a 633kW high efficiency biogas-fired GE-Jenbacher model JMS-312 GS-NL reciprocating engine cogeneration system. The heat recovery system incorporated into the package is designed to capture the waste heat from the engine exhaust, the jacket cooling water and the engine oil circuit. 5. Electrical Substation and Power Distribution Systems: An electrical distribution system has been constructed on-site that aggregates the electrical service of the different county buildings on the District campus into a county owned electric distribution system that is interconnected with the CHP and the local electric grid. The electrical system is designed, in accordance with the utility guidelines, to allow grid-parallel operation of CHP and provide for import and export of electric power. 6. Thermal Energy Distribution System: The heat recovery system has been integrated into a high temperature water distribution system that distributes the heat to the thermal circuits for the anaerobic digester facility. Additional piping has also been installed to transfer the remaining thermal energy to other county buildings on the campus. On a daily basis, the plant will co-process 35,000 gallons of manure from local dairy farms, 8,500 gallons of food-processor waste and 1,200 gallons of brown grease to produce 200,000 ft3/d of biogas and 44,000 gallons of pathogen-free nutrient-rich digested slurry for agricultural use by farms and in the local area.The biogas fueled CHP produces 5,157,000 kWh of electricity and 19,506 dekatherms of thermal energy per year. Electrical power generated by the cogeneration system powers all the buildings on the Cayuga County campus and any surplus power is exported to the grid under a power purchase agreement. Heat recovered from the cogeneration system will be used to maintain the temperature of the process equipment and the excess will be transported to the Cayuga County Public Safety Building to offset purchase of fossil fuel to fuel the boilers. The majority of plant operations are unmanned and automated. However, the plant will have a small staff of well-trained personnel to coordinate the feedstock deliveries and shipments, supervise the day-to-day operation, monitor the systems and perform maintenance, maintain a safe and reliable operation and to respond to emergencies.

Electric Power Distribution System Learning has demands for learning outcomes so that students understand the concept, and have basic knowledge and skills in various constructions of electric power distribution networks. This requires varied and more contextual learning methods and requires contextual learning media as well. The learning media used should be able to provide real experiences for students in simulating the electric power distribution system according to the concepts they are learning. However, the ability of students in the configuration of various distribution networks has problems because there is no suitable learning media. Therefore, it is necessary to develop a valid power distribution system trainer for use in learning. This study aims to produce a valid electric power distribution system trainer. This type of research is research & development (R&D) using the ADDIE model. Research is limited to the development stage (development). The validation test was carried out by 4 validators using an instrument in the form of a validation sheet. The results of the validation show that the electric power distribution system trainer developed is in the valid category, both for content quality aspects and objectives, instructional, and technical. This indicates that the trainer developed is appropriate for use in learning in order to test its effectiveness.

Achieving the right balance between centralized and distributed energy resources (DERs) is key in increasing sustainability, resiliency and energy security. As DERs continue to proliferate, more complete models will be required to study the dynamic interactions between the electric power transmission and distribution systems. To address this need, results from a study are presented concerning the new supporting role of large, fossil-based generators in a power system with an increased level of renewable energy (distributed in particular). This work considers the transmission and distribution system interplay and it contributes to the establishment of fair and transparent operational and regulatory criteria to ensure sustainability and resiliency in power grids with increased levels of renewable energy penetration.

Assuming the availability of a high energy and power density battery of 100 Wh/lb and 100 W/lb by the 1980' s, the energy consumption and efficiency of electric and heat engine cars are compared on an equal basis. This is achieved by considering a reference electric car of 3150-lb weight similar in body construction, aerodynamics, and rolling resistance to a conventional heat engine car of equal weight, and comparing the performance of the two cars over the same driving modes. The reference electric car is then used as a baseline to evaluate the possible improvements in future electric cars. The energy consumption for an optimized 2000-lb electric car of driving range, comfort, and performance comparable to a conventional car is estimated. Assuming a gradual growth in electric car population leading to their widespread use by the 1990's, the impact on electric power generation and distribution systems is estimated. Though the analysis is based on a high energy and power density battery the results may be extrapolated to electric cars using lower performance batteries. It is noted that batteries with lower energy density can provide sufficient driving range to fulfill a significant portion of our transportation needs and their continued development and improvement will accelerate the achievement of the high energy-density goal [1].

In the transmission and distribution systems there are very important activities such as: planning, design, operation, maintenance and commercialization, which are based on the knowledge with good precision of its operation variables: active powers, reactive powers and phasor voltages. Misleading values of these variables distort the mentioned activities and can cause serious technical, economic and social consequences. The measurements of these variables are made in the bars of the lines by a chain of processes, where each of them introduces an error to the measurement. The power measurement errors are usually large, of the order of 3 or 4%. In the measurements of each line, anomalous or absent measurements are detected in many intervals of each month, mainly due to the indicated limitations and temporary failures in the meters. In the present work a method of calculation for the detection, identification and reconstruction of absent and anomalous measurements in the national system of electrical transmission is proposed and developed through the use of state estimation techniques and estimation of parameters based on least squares and the equations of charge flow of the lines, using all the measurements of active energies, reactive energies and existing tensions in the fifteen minute intervals, in both ends of the lines corresponding to the month in which their evaluation is carried out. The application of the proposed method to the 220KV Chimbote -Trujillo line for a sub set of 21 data rows vectors from a total of 2880 data row vectors corresponding to its July 2018 operation is presented.

Spatiotemporal dynamics of in-use copper stocks in the Jing-Jin-Ji urban agglomeration, China

Fault identification in electrical power distribution system using combined discrete wavelet transform and fuzzy logic

Conventional electrical power transmission and distribution system are operated for the simple one-way transportation from remote and large power plants to consumers, but

Distribution transformers are a vital component of electrical power transmission and distribution system. Frequent Monitoring transformers faults before it occurs can help prevent transformer faults which are expensive to repair and result in a loss of energy and services. The present method of the routine manual check of transformer parameters by the electricity board has proven to be less effective. This research aims to develop a low-cost protection system for the distribution transformer making it safer with improved reliability of service to the users. Therefore, this research work investigated transformer fault types and developed a microcontroller-based system for transformer fault detection and protection system using GSM (the Global System of Mobile Communication) technology for fault reporting. The developed prototype system was tested using voltage, current and temperature, which gave a threshold voltage higher than 220 volts to be overvoltage, a load higher than 200 watts to be overload and temperature greater than 39 degrees Celsius to be over temperature was measured. From the results, there was timely detection of transformer faults of the system, the transformer protection circuits were fully functional, and fault reporting was achieved using the GSM device. Overall, 99% accuracy was achieved. The system can thus be recommended for use by the Electricity Distribution Companies to protect distribution transformers for optimal performance, as the developed system makes the transformers more robust, and intelligent. Hence, a real-time distribution transformer fault monitoring and prevention system is achieved and the cost of transformer maintenance is reduced to an extent.

In this paper, the authors propose a new concept of electrical power distribution system named flexible, reliable and intelligent and energy conservative distribution system (FRIENDS). In the near future, electrical power systems will be facilitated by dispersed energy resources and dispersed energy storages on the demand side. The electrical power distribution system itself will have to be changed to cope with these facilities. The authors propose a flexible power distribution system for such a situation. Noticeable characteristics for the proposed system (FRIENDS) are flexible network reconfiguration for uninterrupted power supply through power electronics devices, new protective relaying schemes, online information service to customers (including automated metering), DSM and home automation as well as multi-quality power supply. In this paper, the new concept of the power distribution system of FRIENDS is explained, and how the new functions can be realized is discussed.

The reliability of the electric power distribution system is crucial for industrial consumers, particularly in Karawang Regency, one of the industrial centers in Indonesia. The management of electricity supply for industries in Karawang Regency is entrusted to the Indonesian State Electricity Enterprises, also known as PLN. However, there are still disturbances in the distribution system that affect industrial customers. The primary causes of these disturbances are 39% jointing damage, 36% damage caused by third parties, and 15% damage to cubicles. The occurrence of these disturbances is closely tied to maintenance activities on the electric power distribution system. To assess the distribution system's reliability, various indices are calculated, including the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), energy not supplied (ENS), and feeder disturbance indices. Currently, PT PLN (Persero) UP3 Karawang employs a maintenance model that combines corrective and preventive methods with the four-discipline execution (4DX) approach. This study aims to develop an improved maintenance model that enhances the overall performance of the electric power distribution system for industrial customers. In this study, a maintenance model is proposed by integrating the total productive maintenance (TPM) method, reliability-centered maintenance (RCM) method, and four-discipline execution (4DX) approach. The developed maintenance model is tested on 40 feeders serving industrial customers. A comparative analysis is performed before and after implementing the maintenance model, considering the SAIFI, SAIDI, ENS, feeder disturbance, and overall equipment effectiveness (OEE) indexes. The analysis of the 40 feeders reveals improvements in performance following the implementation of the maintenance model using the TPM, RCM, and 4DX methods. Prior to implementation, the SAIFI was 0.24 times/cust.yr, SAIDI was 1.877 min/cust.yr, ENS was 60,470 kWh, feeder disturbance occurred 8 times, and OEE was 0.99935. After implementation, the SAIFI improved to 0.016 times/cust.yr, SAIDI reduced to 1.342 min/cust.yr, ENS decreased to 41,241 kWh, feeder disturbance reduced to 4 times, and OEE increased to 0.99962. Consequently, the performance improvements are as follows: SAIFI by 33%, SAIDI by 29%, ENS by 32%, feeder interference by 50%, and OEE by 0.027%.

High power solid state laser systems are being developed for advanced weapons and sensors for a variety of Department of Defense applications including naval surface combatants. The transient power and cooling requirements of these emerging technologies present significant challenges to the electric power distribution and thermal management systems, particularly for applications requiring back fit of the new systems onto existing platforms with limited electric power generation and cooling capacities. The University of Texas Center for Electromechanics (UT-CEM) and the Naval Postgraduate School (NPS) have collaborated in the development of simulation models of ship power systems to evaluate and help guide the integration of pulsed laser loads onto existing ship platforms. Key to the success of these efforts is the definition of a suitable energy storage system to handle the effect of the transient load. This paper reports on the progress of detailed MatLab/Simulink models of a destroyer class ship service electric power distribution system that have been developed to evaluate the performance of battery, flywheel, and capacitor energy storage in support of laser weapons. The models allow the user to develop comparative studies of the three energy storage systems in regard to several relevant metrics that can be used for their discrimination. Examples of some of these results based on the simulations are given.

In the new designs of military aircraft and unmanned aircraft there is a clear trend towards increasing demand of electrical power. This fact is mainly due to the replacement of mechanical, pneumatic and hydraulic equipments by partially or completely electrical systems. Generally, use of electrical power onboard is continuously increasing within the areas of communications, surveillance and general systems, such as: radar, cooling, landing gear or actuators systems. To cope with this growing demand for electric power, new levels of voltage (270 V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DC</inf> ), architectures and power electronics devices are being applied to the onboard electrical power distribution systems. The purpose of this paper is to present and describe the technological project HV270DC. In this project, one Electrical Power Distribution System (EPDS), applicable to the more electric aircrafts, has been developed. This system has been integrated by EADS in order to study the benefits and possible problems or risks that affect this kind of power distribution systems, in comparison with conventional distribution systems.

Historically, electric power distribution systems were considered passive subsystems served by the larger transmission grid. Recently, smart grid initiatives have driven the evolution of distribution systems into active systems with market-aware customers and distributed power generation. Along with more diverse and complex injections, contemporary distribution systems are equipped with additional sensing equipment, two-way communications networks, and advanced metering infrastructure (AMI). These are essential technologies that enable several core functions of a smart grid, including real-time monitoring and online control. This thesis presents several tools for the online analysis and control of modern electric power distribution systems. "Online" refers to a control framework that can react to changing system conditions in order to maintain static security and meet different operating objectives. Specifically, the objective of this research is to integrate temporal information (i.e., forecasts) into distribution system analysis tools while maintaining fundamental engineering requirements by re-examining classical problems through a contemporary lens. Connected by an underlying injection forecast model, three research topics are explored: 1) distribution load capability, 2) analytical time window selection for quasi-static time series (QSTS) analysis, and 3) distribution state estimation with explicit consideration of non-synchronized measurements. The work proposed here is a necessary step towards distribution system optimization in an online setting with uncertain and/or bidirectional power flows.

The electric power distribution system is an important part in modern aircraft electric power supply system. In this paper, the fundament of the aircraft electric power distribution system is briefly described through an example. According to the aircraft electric power characteristics defined in National Military Standard, the models of important components in the distribution system are established, such as GCU, GB, BTB, TRU. The logic relations of these components are abstracted. The approaches to establish distribution system models are discussed. The distribution system of the new type of aircraft is simulated applying the models. The validity of the models is verified by comparing the simulation waves and the experiment wave.