Distributed Generation & Alternative Energy Journal最新文献_第4页

Grid-Connected Solar PV Fed BLDC Motor Drive for Water Pumping System 水泵系统的并网太阳能光伏馈电无刷直流电机驱动

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.3856

B. N. Kar, P. Samuel, A. Mallick, J. K. Pradhan

{"title":"Grid-Connected Solar PV Fed BLDC Motor Drive for Water Pumping System","authors":"B. N. Kar, P. Samuel, A. Mallick, J. K. Pradhan","doi":"10.13052/dgaej2156-3306.3856","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3856","url":null,"abstract":"This article proposes a unidirectional power flow of a grid-connected brushless DC motor powered water pumping system fed by a photovoltaic array using a bridgeless power factor corrected (PFC) boost converter. The system consists of a bridgeless PFC converter, a boost converter, and a voltage source inverter to drive a brushless DC motor coupled with a pump. As a backup source, the grid is used. This system allows the water pump to run at maximum capacity regardless of the weather conditions. The grid will provide power if the photovoltaic array is unable to fulfil the required power demand. The unidirectional power flow through a conventional power factor corrected (PFC) boost converter causes conduction loss in the input bridge rectifier, thereby hurting efficiency, power factor, and THD. This paper presents a bridgeless PFC boost converter topology to reduce the conduction losses, thereby increasing the efficiency and obtaining a nearly unity power factor as well as lower total harmonic distortion (THD) of input current. The system is simulated using MATLAB /Simulink. The proposed system’s real-time validation is realized through the OPAL-RT simulator OP5700. The THD results obtained are well within the specified standard of IEC 61000-3-2 and IEEE 519-1992.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85984524","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

Dead-Time Effect and Compensation Technology for an Isolated Dual Active Bridge Converter 隔离型双有源桥式变换器的死区效应及补偿技术

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.3851

Xifeng Xie, Deng Luo, Jiangwei Wang, Xuesong Wu, Tao Chen

引用次数: 0

Artificial Neural Networks-Based Fault Diagnosis Model for Distribution Network 基于人工神经网络的配电网故障诊断模型

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.38513

Zexi Chen, Pu Wang, Bin Li, E. Zhao, Zhigang Hao, Dongqiang Jia

引用次数: 0

Multi-objective Collaborative Planning Method for Micro-energy Systems Considering Thermoelectric Coupling Clusters 考虑热电耦合簇的微能源系统多目标协同规划方法

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.38514

Han Jinglin, Hu Ping, Zhao Hui, He Chunguang, Hou Ruosong, Li Bo

引用次数: 0

Optimal Power Dispatch of Multiple DGs Using a Hybrid Algorithm for Mitigating Voltage Deviations and Losses in a Radial Distribution System with Economic Benefits 基于混合算法的径向配电系统电压偏差和损耗优化调度，具有经济效益

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.3858

Ankeshwarapu Sunil, C. Venkaiah, D. Kumar

引用次数: 0

Improved DCGAN for Solar Cell Defect Enhancement 改进的DCGAN用于太阳能电池缺陷增强

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.3852

Deng Hao, Yilihamu Yaermaimaiti

引用次数: 0

Real-time Monitoring Technology of Voltage Sag Disturbance in Distribution Network Based on TCN-Attention Neural Network and Flink Flow Computing 基于tcn -注意力神经网络和Flink流计算的配电网电压暂降扰动实时监测技术

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.38512

Zexi Chen, Li Yang, J. Tian, Zeng Chen, Xiaoye Xu, E. Zhao

{"title":"Real-time Monitoring Technology of Voltage Sag Disturbance in Distribution Network Based on TCN-Attention Neural Network and Flink Flow Computing","authors":"Zexi Chen, Li Yang, J. Tian, Zeng Chen, Xiaoye Xu, E. Zhao","doi":"10.13052/dgaej2156-3306.38512","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38512","url":null,"abstract":"In the face of the challenges brought by the complexity of power grid, diversification of disturbance factors, isolation of monitoring points and other issues to the cause identification of voltage sag disturbance, this paper proposes a real-time monitoring technology for voltage sag disturbance in distribution network based on TCN-Attention neural network and Flink flow calculation, which has important practical significance for controlling voltage sag and reducing economic losses. This method uses Temporal Convolutional Network (TCN) to extract the cross time nonlinear characteristics of voltage sag time series data, which effectively solves the problems of long-term dependence on time series and low training output efficiency of existing time series models. In order to further improve the recognition accuracy of the model, Attention mechanism is introduced to mine the duration relationship in voltage sag data. At the same time, the method also constructs a parallel real-time monitoring platform based on Flink streaming computing framework, embeds the TCN-Attention voltage sag cause identification model generated by training, so as to realize real-time identification and monitoring analysis of voltage sag disturbances at each monitoring point of the distribution network. In this paper, various voltage sags are simulated on IEEE 14 bus system using PSCAD software, and the proposed method is verified and tested. The deep learning fusion model has high recognition accuracy for the cause of voltage sag, and the flow computing platform has excellent performance in time delay and throughput indicators, and can realize the parallel real-time monitoring and analysis of voltage sag causes in distribution network.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75861242","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

Enhancement of Weighting Coefficient Selection using Grey Relational Analysis for Model Predictive Torque Control of PMSM Drive: Analysis and Experiments 利用灰色关系分析改进 PMSM 驱动器模型预测转矩控制的加权系数选择：分析与实验

Distributed Generation & Alternative Energy Journal Pub Date : 2023-07-12 DOI: 10.13052/dgaej2156-3306.3854

Avinash Vujji, R. Dahiya

{"title":"Enhancement of Weighting Coefficient Selection using Grey Relational Analysis for Model Predictive Torque Control of PMSM Drive: Analysis and Experiments","authors":"Avinash Vujji, R. Dahiya","doi":"10.13052/dgaej2156-3306.3854","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3854","url":null,"abstract":"Permanent magnet synchronous motor (PMSM) with model predictive torque control (MPTC) is popular for its simplified control structure and adaptable in incorporating control parameters into the control algorithm. However, in control technique the primary concern for objective function (OF) depends on the selection of appropriate weighting coefficient (WC). Basically, for weighting coefficient selection, empirical methods are used but it takes additional time and heuristic process. In this paper, Grey Relational Analysis (GRA) technique is introduced in optimization of objective function for selection of appropriate weighting coefficient. In this methodology, stator flux and torque having individual OF are modified from single-OF. This ensures that in each sampling period, selection of grey relational optimal control action is dependent on the preference given to the control parameters in OF. For each sampling, a Grey Relational Grade (GRG) is employed to determine the appropriate control action. The models for two-level inverter fed PMSM are developed in MATLAB/Simulink to test the various operations of PMSM drive and the results are validated on the experimental test bench using dSPACE-1104 R&D controller. In order to highlight the effectiveness of the proposed technique, the results are compared with DTFC and MPTC approach.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139360042","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

Levelized Cost of Energy-Based Economic Analysis of Microgrid Equipped with Multi Energy Storage System 配置多储能系统的微电网均等化成本能源经济分析

Distributed Generation & Alternative Energy Journal Pub Date : 2023-05-18 DOI: 10.13052/dgaej2156-3306.38411

P. Kumar, V. Das, Ashutosh Kumar Singh, P. Karuppanan

引用次数: 0

Policies and Economic Efficiency for Distributed Photovoltaic and Energy Storage Industry 分布式光伏与储能产业的政策与经济效益

Distributed Generation & Alternative Energy Journal Pub Date : 2023-05-18 DOI: 10.13052/dgaej2156-3306.3846

Xiuming Niu, Xu-feng Luo

{"title":"Policies and Economic Efficiency for Distributed Photovoltaic and Energy Storage Industry","authors":"Xiuming Niu, Xu-feng Luo","doi":"10.13052/dgaej2156-3306.3846","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3846","url":null,"abstract":"The technique of directly converting solar energy into electricity using PV modules is distributed photovoltaic (PV) power generation. It is frequently used in a system and is referred to as a distributed PV power system. The system generates power in the surrounding areas and connects to the neighbouring utility grid. A distributed energy storage (DES) system is a bundled solution that stores energy for future use. In the short term, one of the most significant problems with solar power storage is that the batteries utilized for the application are still costly and giant. The more power requires the bigger battery must be. Further research revealed that maximizing solar and wind energies minimizes greenhouse gas emissions and lower the total cost of energy. The ability to store energy is crucial in balancing because it makes the grid more adaptable and stable. The mission of energy conservation and energy storage (ECES) aims to help integrate energy-storage technology research, production, deployment, and integration to improve the energy efficiency of all energy systems and enable the increased use of renewable energy in place of fossil fuels. Storage benefits are examined in terms of distribution transformer loads and storage support during energy fluctuations from renewable energy. However, the results show that the methodology’s recommended framework is successful and obtained with enhanced performance with a reliability of 95.6%. The proposed technique improves the Reliability analysis ratio of 95.4%, Performance analysis comparison ratio of 98.6%, accuracy analysis ratio of 91.3%, ECES model’s efficiency is estimated at 95.6%.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83678440","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

Distributed Generation &amp; Alternative Energy Journal最新文献

Distributed Generation & Alternative Energy Journal最新文献