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Transient analysis of an advanced static Var compensator using quad-series voltage-source PAM inverters

ELECTRICAL engineering IN JAPAN 1996年第2期117卷 93-106页

作者： Tominaga, S Fujita, H Akagi, H Okayama University [?]Received his Master's degree in Electrical and Electronic Engineering in 1995 from the Engineering Research Division of the Graduate School Okayama University. He is currently in the doctoral program in system science at the Natural Sciences Research Division of the Graduate School of the same university. He is engaged in research on reactive power compensators.

This paper deals with an advanced static Var compensator (ASVC) using quad-series voltage-source PAM inverters. The ASVC consists of four three-phase voltage-source inverters with a common de capacitor and four three-phase transformers, each primary winding of which is connected in series with each other. Each inverter outputs a square-wave voltage, while the synthesized output voltage of the ASVC has a 24-step wave shape. This results not only in a great reduction of harmonic currents and de voltage ripples but also in fewer switching and snubbing losses. In this paper, transient analysis is performed with the focus on the response of reactive power and the resonance between the de capacitor and ac reactors. Experimental results obtained from a small-rated laboratory model of 10 kVA are also shown to verify analytical results based on the p-q transformation. The analytical results help in the design of system parameters such as the capacity of the de capacitor and feedback gains.

关键词： reactive power compensator voltage-source inverter PAM higher harmonics power system stabilization

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Improving loss of load probability through biomass power plant integration: A case study in Tanjung Balai Karimun 2

Improving loss of load probability through biomass power pla...

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2nd IEEE International Conference on Innovative Research and Development, ICIRD 2019

作者： Sunarwoko Elsafan, Erick Suhaimi, Lalu Hudaya, Chairul Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Energy System Engineering Master Study Program Faculty of Engineering Universitas Indonesia Depok Indonesia Department of Metallurgy Engineering Faculty of Engineering Universitas Teknologi Sumbawa NTB Indonesia

ISBN: (纸本)9781728128252

Many regions in Indonesia are still lack of electricity due to geographical condition in the form of archipelago, including Tanjung Balai Karimun District, in Kepulauan Riau Province, Indonesia. Therefore, using local renewable resources to fulfill load demand is better than relying on utility grid. The potential of using biomass waste, for instance oil palm and coconut residues, as renewable energy resources should be an optional decision to make improvement, not only for the reliability of existing power system itself but also to meet the load demand generally available in every region of Indonesia. In 2016, Karimun Regency in Riau Islands Province as a Special Economic Zone (SEZ) is growing rapidly in economic and facing electrical energy crisis simultaneously. Addressing this problem, the government has taken an action by making amendment on the policy that consciously planned to increase the capacity of power plants, in particular Oil and Gas Power Plants (OGPP) in the period of 2018-2024. The objective of this study is to evaluate the reliability of Tanjung Balai Karimun power system based on its Loss of Load Probability (LOLP) index designed during the planning period of power plant addition. Then, the value of new LOLP index was recalculated after integrating new system of Biomass Power Plant (BPP). Based on LOLP calculation using recursive method, LOLP index in 2018 decreased from 3.63 days/year to 2.05 days/year, reflecting quality improvement of the power plant reliability. Integrating BPP into the existing power plant has powered up the capacity of 2.8 MW according to the availability of oil palm and coconut biomass waste. © 2019 IEEE.

关键词： Biomass

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Characterization of Municipal Solid Waste Based on Seasonal Diversity as Energy Potential Materials 7

Characterization of Municipal Solid Waste Based on Seasonal ...

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7th Astechnova International Energy Conference, ASTECHNOVA 2023

作者： Mariatunnikmah, Khusnul Ain Lubis, M Faisal Wintoko, Joko Budiman, Arief Master Program in System Engineering Universitas Gadjah Mada Jalan Teknika Utara 3 Yogyakarta55281 Indonesia Chemical Engineering Department Universitas Gadjah Mada Jalan Grafika 2 Yogyakarta55284 Indonesia

Interrelated problems related to resource availability and population growth rates, such as energy demand and waste generation, have become pressing global concerns. Municipal Solid Waste (MSW) poses a significant challenge due to its impact on society and the environment, including the associated hazards and threats. This study was conducted at the Piyungan Integrated Santary Landfill (TPST Piyungan) in Yogyakarta, Indonesia, from June to November 2022. The annual waste generation in the city is 586,267.37 tons per year in 2021, with a daily per capita waste generation rate of 0.43 kg/person. Two types of MSW samples were collected during the dry and rainy season to assess their composition. The collected samples were sorted, sun-dried, quartered, and reduced to 1mm particles for proximate analysis. The results of MSW characterization revealed that non-organic combustible materials accounted for a higher percentage during the dry season (62.7%) compared to the rainy season (53.1%). Conversely, organic matter constituted a higher proportion during the rainy season (36.7%) compared to the dry season (30.4%). The moisture content ranged from 4 to 11%, volatile matter content varied between 60% and 66%, and fixed carbon content ranged from 19 to 31%. The energy content of MSW during the dry season was measured at 20.67 MJ/kg, while in the rainy season, it yielded 14.99 MJ/kg. These findings indicate that due to the substantial energy content and waste generation rates, waste-to-energy (WtE) technologies can be effectively applied to manage MSW in Yogyakarta, simultaneously reducing waste volumes and recovering energy. © Published under licence by IOP Publishing Ltd.

关键词： Moisture determination

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Prediction of electricity load growth of tangerang city using SIMPLE-E 2

Prediction of electricity load growth of tangerang city usin...

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2nd IEEE International Conference on Innovative Research and Development, ICIRD 2019

作者： Putra, Andi Aulia Nayusrizal, N. Untari, Indira Wibisono, Gunawan Hudaya, Chairul Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Energy System Engineering Master Study Program Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Trunojoyo Block M-I No.135 Jakarta12160 Indonesia

ISBN: (纸本)9781728128252

The electricity load growth should be planned appropriately to meet energy demand in a certain area. Electricity consumption growth is generally proportional with the economic and population growth. Using historical data on Gross Domestic Regional Product (GDRP) and population growth, the electricity load growth in the near future can be statistically predicted. The relationship between economic and population growth trend and total customers as well as the demands of contract electricity energy growth trend could be connected by the linear regression method to predict electricity energy consumptions. Through a Simple Econometric Simulation system (SIMPLE-E) program run in Microsoft Excel application, linear regression trend can be calculated. The purpose of study is to predict the growth of electricity consumption in Tangerang City-Indonesia, for the next ten consecutive years (2019-2028). Customer data that will be analyzed consist of five segments, which are Residential (R), Commercial (B), Industry (I), Public (P), and Social (S). Those can be combined with Gross Regional Domestic Product and human population using Multiples Linear Regression in SIMPLE-E. The correlation between dependent variables (total customers and contract of power) and independent variables (population and GRDP) will be computed in SIMPLE-E through rate value of correlation R, Adjusted R, and Durbin Watson test. The Actual trend data of total customer, contract power from 2012 to 2018, is compared to model equation from linear regression. The calculation of error use Root Mean Square Percentage Error and Mean Percentage Error, shows that the total error is less than 5%, meaning the simulation is scientifically accepted. This study shows that the average growth of electricity consumption in Tangerang city from 2019 to 2028 is 5.63%. It means that every 1% growth of economy in Tangerang will increase electricity load consumption for 0.94%. © 2019 IEEE.

关键词： Errors

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Hybrid Particle Swarm and Conjugate Gradient Optimization in Neural Network for Prediction of Suspended Particulate Matter 4

Hybrid Particle Swarm and Conjugate Gradient Optimization in...

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4th International Conference on Energy, Environment, Epidemiology and Information system, ICENIS 2019

作者： Warsito, Budi Prahutama, Alan Yasin, Hasbi Sumiyati, Sri Department of Statistics Faculty of Sciences and Mathematics Diponegoro University Semarang Indonesia Master Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Environmental Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

The scope of this research is the use of artificial neural network models and meta-heuristic optimization of Particle Swarm Optimization (PSO) for the prediction of ambient air pollution parameter data at air quality monitoring stations in the city of Semarang, Central Java. The observed parameter is an indicator of ambient air quality, Suspended Particulate Matter (SPM). Based on air quality parameter data in previous times which is a time series data, modeling is done using Neural Networks (NN). Estimation of weights from NN is done using a hybrid method between meta-heuristic and gradient optimization. The meta-heuristic optimization method used is Particle Swarm Optimization (PSO) while the gradient based method is the Conjugate Gradient. Optimization with PSO is done first, then proceed with optimization using the Conjugate Gradient. Four scenarios of iteration selection at the PSO stage are 10, 25, 50 and 100. At the Conjugate Gradient, stage iteration is carried out up to 1000 epohs. The predicted results were compared with the PSOs and Conjugate Gradient respectively. The results show that the hybrid method provides better predictions. The number of iterations needed at the PSO stage is not too much so it is efficient in combining the two methods. © The Authors, published by EDP Sciences, 2019.

关键词： Forecasting

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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A Vision-Based Neural Networks Model for Turbine Trench-Filler Diagnosis 1

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7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023

作者： Isaza, Cesar Guerrero-Garcia, Fernando Anaya, Karina Jenab, Kouroush Ortega-Moody, Jorge Networking and Telecommunication Academic Program Polytechnic University of Queretaro Queretaro Mexico Productive System Master Academic Program Polytechnic University of Queretaro Queretaro Mexico School of Engineering and Computer Science Morehead State University MoreheadKY40351 United States

ISBN: (数字)9783031396199

ISBN: (纸本)9783031396182

Vision-based neural networks as artificial intelligence models have been critical in many manufacturing industries, including automotive, food, and aerospace. Machine vision and deep learning have provided practical, promising, and accessible innovations to address many problems during manufacturing and diagnostics. Recent studies offer beneficial results in implementing industrial artificial intelligence systems that require determining, comparing, and evaluating optimal technological solutions. The aerospace industry has to deal with the problem of diagnosing critical components that continually need the expertise of a trained human being. On the other hand, automatic diagnostics are becoming a critical technology to deal with this problem. However, these systems require a particular configuration of computer vision algorithms which, in the case of turbine trench-filling components, have yet to be added to the literature. Considering the above, we report in this paper a new methodology that uses a pre-trained deep neural network framework available online to automatically diagnose geometric nonconformities in aeronautical components that protect the turbines from vibrations and reduce noise from the engines to the aircraft deck. The method is based on the following stages: a computer vision system with a monochrome camera to acquire images, training of deep neural networks with transfer learning, and a stage to analyze nonconformities automatically. In addition, a benchmark of several pre-trained deep neural networks is presented to address the problem. According to the experimental results, the YOLO deep neural network topology significantly contributes to automatic diagnosis with high precision and exact rate. Finally, we show that integrating deep neural networks with control graphs is a promising strategy to optimize online diagnostics in the production lines of the aeronautical industry. © The Author(s), under exclusive license to Springer Nature Switzerland

关键词： Deep neural networks

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Synthesis of Biodiesel from Second-Used Cooking Oil

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Energy Procedia 2013年 32卷 190-199页

作者： Wanodya Asri Kawentar Arief Budiman Master Program of System Engineering Faculty of Engineering Gadjah Mada University Yogyakarta Indonesia Chemical Engineering Department Gadjah Mada University Yogyakarta Indonesia

These days, many used cooking oils from restaurants were re-used by street sellers to fry their food. Those waste oils commonly just throw away. Whereas waste oils which have not any treatment first, will pollute the environment. One of the ways to treat the waste oil is by converting to biodiesel. This research aimed to study the kinetic reaction of second-used cooking oil transesterification into biodiesel and find the optimum condition of its process. This research was done by transesterification reaction in batch reactor. The feedstock was collected from the street sellers in Yogyakarta. Methanol was used as a reactant and KOH was used as a base catalyst. The study parameters were temperature, alcohol to oil molar ratio, and catalyst concentration. Several types of analysis used were free glycerol analysis, total glycerol analysis, free fatty acid (FFA) analysis, and saponification analysis. These analyses were used to calculate the yield of conversion and ester content of biodiesel sample. From this research, it is found that the kinetic reaction of second-used cooking oil transesterification can be expressed by k = 0.0251exp (-15.29/RT) dm3/(***). The optimum condition (the ester content 92.76%) of biodiesel production were obtained at temperature 66.5oC, molar ratio of methanol to oil 6.18:1, and 1 wt.% KOH.

关键词： Biodiesel Second-used cooking oil Transesterification Reaction kinetic

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on Computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical system (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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Decision Support system in Determining the Achievement of Widyaiswara Value Using WASPAS and TOPSIS Algorithm 1

Decision Support System in Determining the Achievement of Wi...

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1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022

作者： Pratama, Yudhistira Adhitya Iswara, Bagus Ajie Nababan, Adli Abdillah Information System Studies Program Pelita Harapan University Medan Campus Faculty Of Computer Science Medan Indonesia Master's Study Program Informatics Engineering Universitas Sumatera Utara Faculty Of Computer Science And Information Technology Medan Indonesia Digital Business Study Program Stmik Pelita Nusantara Medan Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material by the BPSDM PROVSU. However, the assessment process that occurs is still not precise and time-consuming. Therefore, to minimize this, a decision support system is needed that can minimize time errors and data processing in decision-making so that the assessment runs well and accurately. This system was built by applying the WASPAS method and the TOPSIS method. Based on the results of tests carried out five times, the results of the WASPAS method processing time resulted in an average processing time of 0.00029791 ms and an average memory usage value of 2.836.44 kb, while the results of the TOPSIS method processing time test resulted in an average processing time - an average of 0.000296428 ms and an average memory usage value of 2.862.34 kb. © 2022 IEEE.

关键词： Decision support systems

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