2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)最新文献_第7页

Health Index prediction using Artificial Neural Network (ANN) on Historical Data of Power Transformer 基于历史数据的电力变压器健康指数人工神经网络预测

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093199

Gemelfour Ardiatus Sudrajad, S. Suwarno, R. A. Prasojo

{"title":"Health Index prediction using Artificial Neural Network (ANN) on Historical Data of Power Transformer","authors":"Gemelfour Ardiatus Sudrajad, S. Suwarno, R. A. Prasojo","doi":"10.1109/ICPEA56918.2023.10093199","DOIUrl":"https://doi.org/10.1109/ICPEA56918.2023.10093199","url":null,"abstract":"Power transformer is an important equipment in the electric power system. The power transformer has the main task of changing the voltage, transmitting electricity, and distributing electricity. Disruption or failure of the transformer can result in asset fires and power outages. Transformer power failure can result in social and economic losses. The right maintenance strategy can reduce the risk of transformer failure and optimize operational costs and maintenance costs. The Health Index is used to provide an overall assessment of the condition of the power transformer, assess the reliability of the power transformer, and the strategy for maintaining the power transformer. In addition to durability, the health index of the transformer can be assessed from the life expectancy of the transformer. Health Index values can be obtained from expert judgment, calculations, and prediction methods using Artificial Intelligence. This paper discusses the implementation of Artificial Neural Network (ANN) as one of the Artificial Intelligence (AI) algorithms to predict the condition of the transformer health index. The result is compared to the calculated HI, then validated by 79 transformers that have been comprehensively assessed by the expert.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132132632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Power Quality Control Strategy of MMC Rectifier as Solid State Transformer in MVAC Network MMC整流器作为MVAC网络中固态变压器的电能质量控制策略

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093220

K. Mangunkusumo, M. Ridwan, Sriyono, F. D. Wijaya, R. Irnawan, Yohan Fajar Sidik, P. P. Oktarina

{"title":"Power Quality Control Strategy of MMC Rectifier as Solid State Transformer in MVAC Network","authors":"K. Mangunkusumo, M. Ridwan, Sriyono, F. D. Wijaya, R. Irnawan, Yohan Fajar Sidik, P. P. Oktarina","doi":"10.1109/ICPEA56918.2023.10093220","DOIUrl":"https://doi.org/10.1109/ICPEA56918.2023.10093220","url":null,"abstract":"The development of electricity technology in distribution networks such as Electric Vehicles and Distributed Generation (Rooftop PV, etc.) can lead to increased instability due to the characteristics of generation that tends to fluctuate and the characteristics of power electronic devices. Conventional transformers behave passively to the problems faced by the distribution network. One solution to this problem is the use of solid state transformers (SST). This study will describe the consideration of topology selection and rectifier control system as one of the main converters of SST. The rectifier topology used is Modular Multilevel Converter (MMC). MMC is chosen because it has the flexibility of feature development and low THD compared to other converter topology options. The Higher Level Control algorithm used is Vector Current Control and the Lower Level Control uses Nearest Level control. Simulation results show that the MMC rectifier in the designed SST is able to support reactive power by sending and absorbing reactive power according to load demand or dispatch commands on the MVAC network. Moreover, the designed MMC rectifier is able to respond to the emergence of power quality problems in the form of voltage sag and swell.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131446791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Three-Phase Power Transformer Fault Diagnosis Based on Support Vector Machines and Bees Algorithm 基于支持向量机和蜜蜂算法的三相电力变压器故障诊断

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093147

Othman Abdusalam, Fatih Anayi, M. Packianather

{"title":"Three-Phase Power Transformer Fault Diagnosis Based on Support Vector Machines and Bees Algorithm","authors":"Othman Abdusalam, Fatih Anayi, M. Packianather","doi":"10.1109/ICPEA56918.2023.10093147","DOIUrl":"https://doi.org/10.1109/ICPEA56918.2023.10093147","url":null,"abstract":"In this paper, a new method is presented for the classification of current signals faults in three-phase transformers. In this method, Support Vector Machines are used in two different ways. The study utilized two support vector machines, SVM1 and SVM2, for detecting faults and inrush currents in 3-phase transformers, as well as differentiating between internal faults (turn-to-turn and turn-to-ground) and external faults. To evaluate the performance of the proposed model, laboratory experiments were conducted on a transformer system with both internal and external faults, and the resulting current signals were utilized to develop the model. By training machine learning classifiers to detect faults by SVM, a process for optimal feature identification has been proposed. To extract statistical characteristics from unprocessed data, discrete wavelet transform was used. An optimized subset was then created using the Bees algorithm (BA), which minimized the amount of data needed and improved the model's accuracy. 5k-fold cross-validation was used to train these models. This model has been analysed based on accuracy. The study compares SVMs to ANN-based classifiers and finds that SVMs are more reliable and provide faster results.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132845634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generation Expansion Planning Considering Photovoltaic (PV) and Wind turbine Systems Using Optimization of Evolutionary Programming (EP) Technique 基于进化规划优化技术的光伏和风力发电系统扩容规划

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093202

Adibah Binti Mashudi, Muhammad Murtadha Othman, Masoud Ahmadipour, Kamrul Hasan

引用次数: 0

Comparison of Enhanced Isolation Forest and Enhanced Local Outlier Factor in Anomalous Power Consumption Labelling 增强型隔离林与增强型局部离群因子在异常电耗标识中的比较

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093186

Rawan ELhadad, Yi-Fei Tan, W. Tan

{"title":"Comparison of Enhanced Isolation Forest and Enhanced Local Outlier Factor in Anomalous Power Consumption Labelling","authors":"Rawan ELhadad, Yi-Fei Tan, W. Tan","doi":"10.1109/ICPEA56918.2023.10093186","DOIUrl":"https://doi.org/10.1109/ICPEA56918.2023.10093186","url":null,"abstract":"Anomaly detection in power consumption is one of the major challenges faced by the modern world in response to the excessive electric consumption in developing countries. As a result, researchers were motivated to conduct extensive studies in this area to develop algorithms that classify the abnormal data instances from smart meter readings. In this paper, we examine and compare the effectiveness of two anomaly labelling algorithms, namely: the Enhanced Isolation Forest (E-IF) and the Enhanced Local Outlier Factor (E-LOF), in detecting the abnormal power consumption in building. The E-IF and the E-LOF are proposed based on the Isolation Forest (IF) and the Local Outlier Factor (LOF) algorithms with an additional step of applying a threshold to distinguish the high and low electricity consumptions anomalies. Experiments were performed to 10 smart meters readings and the capabilities of E-IF and E-LOF in detecting the injected anomalies were investigated. The results showed that the E-IF outperformed E-LOF, with E-IF managed to detect 100% of the injected anomalies at contamination levels of 0.30 and 0.35. The E-LOF, on the other hand, could detect an average of 68% of the injected anomalies for contamination level of 0.30 and 78% for contamination level of 0.35.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132252887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Thermal Characterization of Power Gallium Nitride Transistor 功率氮化镓晶体管的热特性

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093146

Jungkyun Kim

引用次数: 0

Line-Interactive Transformerless Bidirectional Buck-Boost Uninterruptable Power Supply System With Battery Control Algorithm 线路交互无变压器双向升压不间断供电系统及电池控制算法

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093170

N. A. Rahman, N. Sukimin

{"title":"Line-Interactive Transformerless Bidirectional Buck-Boost Uninterruptable Power Supply System With Battery Control Algorithm","authors":"N. A. Rahman, N. Sukimin","doi":"10.1109/ICPEA56918.2023.10093170","DOIUrl":"https://doi.org/10.1109/ICPEA56918.2023.10093170","url":null,"abstract":"This paper presents integrated control algorithms for a single-phase line-interactive transformerless bidirectional buck-boost Uninterruptable Power Supply (UPS). The control algorithms consist of two battery control algorithms and one dc to ac conversion algorithm. The battery control algorithms are applied to a bidirectional buck-and-boost converter. Additionally, an AC/DC-DC/AC converter employs the dc to ac conversion algorithm. The battery control algorithms utilise two Proportional-Integral (PI) controllers to regulate voltage and current, respectively. In contrast, the dc to ac conversion algorithm applies one PI voltage controller and a bandless hysteresis current controller. The battery reference value is set according to the battery’s fully-charged voltage for the battery charging control algorithm. Meanwhile, the dc output voltage is set higher for the battery discharging control algorithm to allow the success of dc to ac conversion by the AC/DC-DC/AC converter. Based on the simulation findings, both independent control algorithms can govern the functioning of both converters in both modes of operation. Consequently, the UPS system can supply sinusoidal voltage and current waveforms with low Total Harmonic Distortion (THD) output.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123874662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Power Transformer Insulation System Health Index with Missing Data Prediction using Random Forest 随机森林缺失数据预测的电力变压器绝缘系统健康指数

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093216

Geby Chintia, R. A. Prasojo, Suwarno

引用次数: 0

Mixed-Integer Linear Programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty 考虑一次能源不确定性的火电厂运行优化降额问题的混合整数线性规划方法

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093175

Nur Fauziyah, N. Hariyanto

{"title":"Mixed-Integer Linear Programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty","authors":"Nur Fauziyah, N. Hariyanto","doi":"10.1109/ICPEA56918.2023.10093175","DOIUrl":"https://doi.org/10.1109/ICPEA56918.2023.10093175","url":null,"abstract":"Electricity has an important role in economic development and people’s lives in a country. As the population increases, so does the demand for electricity, resulting in the problem of shortages of electricity supply which leads to huge economic losses. The important problem to be considered is the primary energy used to produce electricity, especially coal, one of the primary energies of thermal power plants where coal availability has a contribution to the non-optimal scheduling of thermal power plants operation which causes the derating problems. This paper proposes a new algorithm with combining algorithms of unit commitment and economic dispatch, coal transshipment, coal blending and inventory problems which will be implemented using Pyomo based on Python programming language with Mixed Integer Linear Programming (MILP) approach. The new algorithm is used to determine the optimal time for coal delivery and maintenance of power plants according to coal inventory. The results showed that the addition of this new algorithm provides 5.57% cheaper and more optimal power plants operation cost.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124304760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structure and DC Breakdown Properties of Polypropylene/Elastomer Blends 聚丙烯/弹性体共混物的结构和直流击穿性能

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI: 10.1109/ICPEA56918.2023.10093160

S. Kamarudin, K. Y. Lau, N. A. Ahmad, N. Azrin, C. W. Tan, K. Y. Ching

引用次数: 0