An advanced flexible and reliable distribution system

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%.

Objectives: Distribution automation is a pre requisite for an intelligent power network. In this paper we investigate the effect of control devices in distribution automation system. Methods/Analysis: According to the importance of improving reliability of electric distribution system, reliability improving approaches by developing control devices in the network is investigated. Also, the effect of developing control devices located in electric distribution network on reliability of system in the form of numerical studies on a sample network in two equipped and non-equipped steps by load cut keys is presented. Findings: Comparing the results obtained from two investigated steps. Shows that equipping the investigated network with control devices has no effect on SAIFI index, but developing load cut keys leads to the improvement of SAIDI and CAIDI indices. Developing control devices such as load cut keys allows the isolation of error place and detection of tripped loads. Thus detectable subscribers of damaged feeder experience shorter turn out time, which finally leads to the improvement of reliability in distribution system. Thus, according to the reliability measurements, control devices development leads to the improvement of reliability in electric distribution system. Conclusion/Application: According to the obtained results in measurements of reliability, it is observed that developing control devices leads to improving reliability and decreasing outages in electric distribution system. Keywords: Control Devices, Decreasing Outages Time, Electric Distribution Automation, Intelligent, Reliability

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

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.

The offshore oil and gas industry is developing subsea processing systems far away from the shore and in ultra-deepwater. These subsea systems are usually power intensive, and thus a reliable electrical transmission and distribution (T&D) system is desired. In this paper, the modular stacked direct current (MSDC) architecture is presented to meet the technical challenges of the ultra-deepwater subsea systems. Instead of using a bulky centralized high voltage direct current (HVDC) converter station, the high dc voltage is achieved by stacking a number of power converter building blocks in series on both the on-shore station and the seabed stations. The dc-link current is controlled to be constant, and the dc-link voltage will vary according to the loading condition. This architecture renders fault-tolerant capability and feasibility for field extension. The details for the system architecture, the control algorithm, the simulation and experimental results will be described. The test results and the studies show that the MSDC system is a very attractive solution for subsea applications. Introduction The diminishing conventional oil and gas reservoirs and the always growing energy consumption have been driving the efforts to explore the deep-sea water petroleum resources, as shown in the diagram in Fig. 1. These resources are usually in ultra-deepwater and far away from the shore, where subsea process is usually preferred for technical and/or economic reasons. Subsea processing is especially attractive for the locations with tough topside environment since the manned topside platform can be removed. However, in order to achieve subsea process, turbo machines, e.g., pumps and compressors, and other processing equipment need to be deployed on the seabed. Accordingly various electrical equipment, including variable speed drives, power supplies, motors, connectors, switch gears, etc., are required to drive the machinery loads subsea. The overall power requirement ranges from tens of kW to tens of MW. As the scale and power consumption of the subsea process continue to grow, there is a clear need for a reliable power transmission and distribution system to power the subsea equipment over long step-out. Long step out distances and the ultra-deepwater environments have brought significant technical challenges to the electrical system. In ultra-deepwater and long step-out situation, accessibility of any equipment deployed in the subsea field is extremely limited. Subsea operation and maintenance is dependent on availability of vessels with remotely operated vehicles (ROV) and sufficient lifting/installation capacity, hence unplanned stops due to failures will cause large losses in production due to lost time. The cost of the vessel and offshore operation is also significant. Therefore, other than being designed for installation in ultra-deepwater, the electrical system must be very reliable and require minimum regular maintenance in its lifetime. The electrical system should also be as compact as possible and modularized, so that they can be installed and retrieved without heavy vessels and lifts which have very limited availability. In addition, the electrical system should be flexible and easy to be reconfigured since the power requirement, the tie-back length, and the number of loads will vary from site to site. And it should also have the flexibility for future expansion since additional field might be found in the adjacent area. In order to meet the above mentioned challenges and requirements, the MSDC architecture has been developed for the subsea power transmission and distribution with long step-out. This paper compares different technology options for subsea transmission and distribution (T&D), presents the MSDC architecture, describes the details of the system operation, and discusses the results of the field case simulation and the lab demo.

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.

Design of an advanced electric power distribution systems using seeker optimization algorithm

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.

&lt;span&gt;The increasing demand of electricity and number of distributed generations connected to power system greatly influence the level of power service reliability. This paper aims at improving the reliability in an electric power distribution system by optimizing the number and location of sectionalizers using the Ant Colony Optimization (ACO) and Simulated Annealing (SA) methods. Comparison of these two methods has been based on the reliability indices commonly used in distribution system: SAIFI, SAIDI, and CAIDI. A case study has been taken and simulated at a feeder of Pujon, a place in East Java province of Indonesia, to which some distributed generators were connected. Using the existing reliability indices condition as base reference, the addition of two distributed plants, which were micro hydro and wind turbine plants, has proven to lower the indices as much as 0.78% for SAIFI, 0.79% for SAIDI, and 2.32% for CAIDI. The optimal relocation of the existing 16 sectionalizers in the network proved to decrease further the reliability indices as much as 43.96% for SAIFI, 45.52% for SAIDI, and 2.8% for CAIDI, which means bringing to much better reliability condition. The implementation of the SA method on the considered data in general resulted in better reliability indices than using the ACO method.&lt;/span&gt;

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.

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].

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.

Discusses the growing role of microprocessor and communications technologies in the control of electric power operational and distribution systems especially with the expected future growth of dispersed energy storage and generation systems.

This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study was carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been developed.

In this paper, load modelling has been done in electrical distribution system using local real time test data. This distribution system supplies base loads, residential, industrial, commercial and composite loads. Using power and current-mismatch functions in polar form, a comprehensive framework for applying the Newton–Raphson method to solve power flow problems is presented. The Newton–Raphson approach for solving power flow problems can be applied in six different ways using these two mismatch functions. For load (PQ)buses and generator (PV) buses, we propose a theoretical framework for analyzing these versions. In addition, we compare newly created versions of the Newton power flow method to current variants in this study. Numerical studies on distribution networks are used to study the convergence behavior of all approaches. The measurements are formed for short term load forecasting with different types of realistic loads such as base loads, residential, industrial, commercial and composite loads. The long-term load forecasting and their losses also has been performed along with short term load forecasting. The results are obtained and validated through MATLAB.