2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)最新文献

{"title":"Wind Turbine Performance: Consideration the Execution of Power Performance Verification","authors":"Thoa Le Thanh, Dieu Vo Ngoc, E. Muljadi, Van Pham Thi Hai, Minh Nguyen Le Uyen","doi":"10.1109/CPEEE56777.2023.10217381","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217381","url":null,"abstract":"Wind turbines operate at design performance to ensure project financial efficiency, and fairness in the Turbine Supply Agreement and achieve project commitments related to operating permits. Proving turbine performance is only possible through power performance testing, with a complex and rigorous process that complies with IEC standards. This paper evaluates possible impacts on turbine operating efficiency by analyzing data collected through the SCADA system. Due to the complicated implementation process, timing, and cost, the goal of the work is to provide more useful information to make an effective decision to implement a power performance verification. The paper is especially useful for the practical application of turbine performance analysis for the first stage of operation. Even during turbine commissioning, a turnkey contract is obligated to prove the turbine is working properly before taking over certificate and transferring the risk to the project.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126963909","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}

{"title":"An Enhanced Deep Forest Rolling Bearing Fault Diagnosis Method","authors":"Meng Xu, Aidong Deng, Dongchuan Liu, Yaowei Shi","doi":"10.1109/CPEEE56777.2023.10217451","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217451","url":null,"abstract":"Deep forest(DF), as a new deep learning model, has superior performance in model tuning and training time and has been widely studied in recent years. However, there are still considerable challenges in reducing the disadvantages of the multi-granularity scanning process and cascading forest stitching. To this end, this paper proposes a novel deep forest-based rolling bearing fault diagnosis method, which enhances feature learning using the developed multi-scale-self-attentive strategy. The highlight of this method is the designed multi-scale self-attentive reinforced feature extractor and low-dimensional self-encoder. It significantly mitigates the feature swamping caused by interference signal features and cascading forest dimensional splicing, thus effectively learnings the bearing fault features. Benefiting from it, the proposed method can perform better. Diagnostic tasks built on the rolling bearing dataset validate the proposed method’s effectiveness and superiority.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115431941","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}

{"title":"The Impact of Weather Conditions on the Harmonic Behaviour of Grid-Connected Photovoltaic Systems","authors":"Ahmad Awadh Althobiti, Faisal Almalki, A. Alhussainy, Sultan Alghamdi, M. Rawa, Y. Al-Turki","doi":"10.1109/CPEEE56777.2023.10217711","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217711","url":null,"abstract":"The utilization of solar photovoltaic systems has seen a marked uptick in recent years. Research efforts have been geared towards improving efficiency and reducing the cost of solar PV plants. In light of concerns over the potential consequences of high penetration of PV systems, governments have been implementing renewable energy programs. This study presents a time-domain model for analyzing harmonic effects in utility-scale PV plants under varying levels of irradiance and temperature conditions.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116353527","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}

{"title":"Research on Response Characteristics of the Load","authors":"Lei Wang, G. Wang, Gang Ma, Qingguang Yu, Le Li, Xiaoyu Li, M. Guo, Yuan Gao","doi":"10.1109/CPEEE56777.2023.10217638","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217638","url":null,"abstract":"Electric load forecasting plays an important role in the safe dispatch of power systems and improving the economy of power system operation. With the development of demand response, electric vehicles, electric heating, and some industrial loads become excellent response resources and require more accurate load forecasting methods. Electric load parameters are influenced by multi-dimensional factors. In order to fully exploit the time-series features in electric load data and improve the accuracy of electric load forecasting, this paper proposes a method for load forecasting based on LightGBM feature selection and improved Transformer model. Using the electricity load data from the Tianjin Smart Energy Service Platform as the data set, the input features of the load are firstly divided into temporal features, historical features, weather features and input load features, and then the features are multi-optimally filtered using the LightGBM model to select the features with higher relevance, and finally the improved Transformer model is used for load forecasting. The method is compared with commonly used forecasting models using actual arithmetic examples, and the results of the arithmetic examples prove that the method can improve the forecasting accuracy of electricity load data.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129702706","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}

{"title":"Dynamic Partitioning Modeling Based on Adjustable Capability of Electric Vehicles","authors":"Qingguang Yu, Xiaoyu Li, Yong Li, Yu Lei, Mingmei Zhang, Weihua Luo, Rui Ou, Qiang Lan, Yuqing Zhou, M. Guo, Le Li, Leidong Yuan","doi":"10.1109/CPEEE56777.2023.10217613","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217613","url":null,"abstract":"In this paper, we develop a power system dynamic partitioning model that includes electric vehicles and takes into account a significant amount of electric vehicle load access by integrating the following dynamic partitioning techniques: The Jacobi matrix is first calculated using the tide, followed by the augmentation method to obtain the sensitivity matrix with all node coupling information and the electrical distance matrix, the cluster to obtain the preliminary partitioning, the power reserve verification and correction to obtain the When the power changes, the partitioning result is modified to alter the partitioning immediately. The computation was also confirmed by the IEEE 14 node system, which can be shown to play a part in controlling power distribution, enhancing grid tide, and being able to respond to different scenarios. The model and computation method have certain drawbacks, though, so it still could not be perfect.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126126078","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}

{"title":"Thermal Model for Single-Phase Dual Active Bridge Converter for Future Smart Transformer in Indonesia","authors":"M. Ridwan, Yohan Fajar Sidik, Sriyono, Kevin Gausultan, Rifka Widyastuti, F. D. Wijaya, R. Irnawan, M. Ahmad","doi":"10.1109/CPEEE56777.2023.10217537","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217537","url":null,"abstract":"The future smart transformer in Indonesia is designed to be efficient by using the dual-active bridge (DAB) converter for its DC-DC converter. A DAB converter has capability of zero-voltage switching (ZVS), which has lower losses than other DC-DC converter design. However, thermal model becomes the key process to calculate the losses of a DAB converter for future smart transformer in Indonesia. This research uses Foster thermal model and PLECS software to estimate and simulate the thermal model to find the thermal losses. Two types of switching devices, IGBT and SiC MOSFET, are used in the DAB converter and then the thermal losses are compared. The simulation model is used to validate that the analytical model of a DAB converter can be used to calculate the total losses of a DAB converter. The results show that the design of future smart transformer in Indonesia with a DAB converter using SiC MOSFET has lower losses than using IGBT as switching in the same switching frequency.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122095572","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}

{"title":"Simulated Characteristics of a PV Module with Low-Resistance Defects","authors":"Zhangyin Hong, K. Itako, Yupeng Qiu","doi":"10.1109/CPEEE56777.2023.10217490","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217490","url":null,"abstract":"To provide guidance on coping with the problem of low resistance defective hot-spots in solar panels, this paper simulates the characteristics of module with hot-spots under different conditions for solar cells with low-resistance defects. Hot spots are formed in shaded locations, and low-resistance defective cells under reverse bias generate heating power. Through simulated module analysis, I-V and P-V characteristic trends can be predicted for PV module with low-resistance defects under different temperatures and solar intensities. And the effect of shunt resistance on the heat generation of hot-spot was analyzed. The maximum power point under the premise of zero heat generation in the simulation is proposed as the safe operating point. It is possible to predict the maximum safe operating power for PV module with low-resistance defects. The power of the safe operating point and the maximum power point power were evaluated for different shadow sizes, providing guidance for practical use.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130454350","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}

{"title":"The Limitations of Arc Detection Using Semiconductive Light Sensing Elements Inside the Transformer Tank","authors":"A. Sharifi, M. Kuhnke, P. Werle, A. Akbari","doi":"10.1109/CPEEE56777.2023.10217559","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217559","url":null,"abstract":"Transformer explosions and fires are the most dangerous consequences of transformer faults. As protection each transformer is equipped with a Buchholz relay (BHR), which identifies the faults, thus a circuit breaker (CB) can trip the transformer. However, in some cases, the tripping of the transformer is not fast enough in order to prevent a tank rupture and the damages. Therefore, faster arc detection systems are under an investigation like the use of photo sensitive semiconductors inside the transformer tank to detect the light emission from an arc and to trigger the circuit breaker. In this paper, the characteristics of different light sensitive semiconductors, such as light dependent resistors (LDRs), and photodiodes are compared in regard to their possible application inside oil filled power transformers. Moreover, the performance of certain measuring circuits with the different semiconductors is presented and compared at different distances to an arc with temperature variation. It is experimentally observed that the photosensitive semiconductors have serious limitations to operate at an elevated temperature closer to $100^{circ} C$ in oil and the environment of electromagnetic fields. Finally, the advantages and disadvantages of the different semiconductor types and their limitations of arc sensing with light sensors are concluded.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116258643","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}

{"title":"Implementation of the Robust MRAC Adaptive Control for a DC Motor: A Method Based on the Lyapunov’s Quadratic Functional","authors":"Nzanzu Lukogho Luckson, Gueye Samba, Ndiaye Mouhamadou Falilou","doi":"10.1109/CPEEE56777.2023.10217506","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217506","url":null,"abstract":"This paper proposes a robust model reference adaptive controller (MRAC) based on the approach of Lyapunov’s quadratic functional to control the speed of a DC motor and to guarantee the desired performances of the motor under critical operating conditions such as varying working conditions due to changing environment, temperature increase or process aging. In this paper, the parameters armature’s resistance Ra, armature’s inductance La and moment of inertia J of the machine were varied from 10% to 100% of their nominal values. To achieve this, the methodological approach is as follows. The first step is to present the system, DC motor; then make its modeling. Then, a Lyapunov’s quadratic functional is chosen. It allows to guarantee the global stability of the system and in which (this function) derives the mechanism of adaptation of the motor parameters. The implemented parameter adjustment mechanism into the Matlab / Simulink environment gives the following results: a settling time of 13.6 milliseconds, a system rise time of 10.25 milliseconds, a final value of 0.165 for a step input. For the reference model this final value is 0.166, hence a tracking error of 0.001004. The overall relative uncertainty of the system is 0.6%; and the measurement uncertainty on the speed at the motor output is 0.000234% by applying a variation of 10% to 100% on its nominal parameters. Compared to the results obtained by implementing an MRAC controller based on the MIT rule and those of the classical PID controller, the results obtained from the analysis of the Lyapunov’s quadratic candidate function meet the objectives set and correct the shortcomings and inadequacy of the PID and the MIT controller in the face of the problems of varying working conditions, hence a robust MRAC-Lyapunov controller. These simulation results also show and prove the effectiveness of this controller based on the Lyapunov’s quadratic function, as it ensures the global stability of the controlled system and a judicious choice of the adaptation gain coefficients of this controller improves the output performances of the controlled system by cancelling the deviation between the two processes, DC motor and reference model, in presence or not of the parametric variations.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114494359","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}

{"title":"Unsupervised Remaining Useful Life Prediction for Bearings with Virtual Health Index","authors":"Gilbert Cheng, Sean Lau, Nicholas Tam, Zekai Wu, Adah Hu, Y. Law, E. Lai, Ming Ge","doi":"10.1109/CPEEE56777.2023.10217714","DOIUrl":"https://doi.org/10.1109/CPEEE56777.2023.10217714","url":null,"abstract":"A particular interest in achieving Prognostics Health Management (PHM) for bearings has been developed in the scientific community and the industry, as they are critical components in generators and turbines. Majority of state-of-the-art methods used in prediction of Remaining Useful Life (RUL) require large amounts of run-to-failure data for training. While these methods offer accurate prediction, the usage barrier is particularly high to small-scale, downstream sector companies due to the significant amount of data needed. The goal of this paper is to demonstrate a novel unsupervised method to address this problem. The algorithm takes advantage of Convolution Neural Network (CNN) encoder-decoder to infer Virtual Health Indices (VHI) which are representative of the degradation pattern. Additionally, thresholds for these indices are determined with only End-of-Life (EOL) data, removing the need for run-to-failure experiments. The RUL is then obtained through the inference of the VHI. The suggested method is tested on various benchmark datasets, particularly the XJTU-SY bearing dataset, offering promising prediction results to reduce the barrier of usage for RUL algorithms.","PeriodicalId":364883,"journal":{"name":"2023 13th International Conference on Power, Energy and Electrical Engineering (CPEEE)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114890844","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}