2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)最新文献_第9页

Capacity Determination of the DC-side Battery for Hybrid Batteries in PV Generation System 光伏发电系统中混合电池直流侧容量的确定

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881162

Shinya Hashimoto, Toshikazu Yamamoto, K. Nara, Nozomi Tobaru

{"title":"Capacity Determination of the DC-side Battery for Hybrid Batteries in PV Generation System","authors":"Shinya Hashimoto, Toshikazu Yamamoto, K. Nara, Nozomi Tobaru","doi":"10.1109/ISGT-Asia.2019.8881162","DOIUrl":"https://doi.org/10.1109/ISGT-Asia.2019.8881162","url":null,"abstract":"Lots of studies are published to mitigate the photovoltaic (PV) power output fluctuation by using batteries. Especially, under the islanding operation of the microgrid, the PV output fluctuation causes the instability of the system. Although batteries are installed to mitigate the instability, a control delay of the batteries affects the frequency and voltage of the micro-grid extensively. Generally, a control delay inevitably exists since the PV output is measured at every designated discrete time period and the control signal is sent to the batteries after calculating the difference between load and PV power output. Therefore, so as to reduce this time delay influences, the authors have proposed so called \"PV system with hybrid batteries\" which has two types of the batteries (AC side battery and DC side battery). In this system, since the DC side battery absorbs only the power fluctuation caused by the control delay of the AC side battery, the size of the DC side battery seems to be very small. The purpose of this paper is to develop a method to estimate the size of the DC side battery. Through the qualitative discussions, the maximum necessary capacity can be estimated from the amount of charge or discharge of the DC side battery when the PV output fluctuation cycle is the same as the one of the PV output measurement. The size of the DC side battery calculated by the developed method is verified through the real system applications.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114592125","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: 2

STATCOM Based Network Voltage Unbalance Mitigation for Sub-Transmission Networks 基于STATCOM的子输电网电压不平衡缓解

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881411

T. D. Kahingala, S. Perera, A. Agalgaonkar, U. Jayatunga

引用次数: 1

Optimization of Artificial Bee Colony Algorithm Based Load Balancing in Smart Grid Cloud 基于人工蜂群算法的智能电网云负载均衡优化

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881232

Luocheng Shen, Jiazhou Li, Yan Wu, Zhenyu Tang, Yi Wang

引用次数: 19

Model Predictive control of dual-active-bridge based fast battery charger for plug-in hybrid electric vehicle in the future grid

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881457

Dehao Qin, Qiuye Sun, Dazhong Ma, Jiazheng Sun

{"title":"Model Predictive control of dual-active-bridge based fast battery charger for plug-in hybrid electric vehicle in the future grid","authors":"Dehao Qin, Qiuye Sun, Dazhong Ma, Jiazheng Sun","doi":"10.1109/ISGT-Asia.2019.8881457","DOIUrl":"https://doi.org/10.1109/ISGT-Asia.2019.8881457","url":null,"abstract":"The popularity of the plug-in hybrid electric vehicle (PHEV) in the future grid encourages the demand for fast battery charging technology with bidirectional power flow capacity to realize V2G. In order to improve the performance of charging process, many charging methods have been proposed, such as multi-stage charging, pulse charging method, reflex charging method, etc. Such methods all need the corresponding battery charger to provide variable DC voltage or current to charge for the battery. Therefore, the DC-DC converter with fast dynamic performance can improve the performance of the different charging methods. However, traditional dual-active-bridge (T-DAB) based battery charger does not have a relatively fast dynamic performance. Therefore, this paper proposes a model predictive control for dual-active-bridge (MPC-DAB) based battery charger under dual-phase-shift (DPS) control with the Thevenin model for battery. Compared with the T-DAB based battery charger, MPC-DAB based battery charger possesses faster dynamic performance and lower overshoot.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128450797","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: 5

Research on Establishment and Method of Performance Evaluation Index System of smart grid Distribution Network 智能配电网性能评价指标体系的建立与方法研究

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881747

Di Wang, Lin Lv, Jie Tang, Xinda He

{"title":"Research on Establishment and Method of Performance Evaluation Index System of smart grid Distribution Network","authors":"Di Wang, Lin Lv, Jie Tang, Xinda He","doi":"10.1109/ISGT-Asia.2019.8881747","DOIUrl":"https://doi.org/10.1109/ISGT-Asia.2019.8881747","url":null,"abstract":"It is an important requirement for the operators to control the power grid to evaluate the operation performance of the smart power distribution network reasonably and accurately. This paper from the perspective of the smart grid efficiency, effect and benefit, build up a set of evaluation index of the performance of the smart grid distribution network state system. First, through the expert method, experts from the perspective of three index system screen the center index and the non-central index, next using the improved fuzzy clustering method to correct the center index and the non-central index again, and then using the analytic hierarchy process (AHP) to improve the group gray correlation method to correct the rest of the center again and eliminate redundant indicators. The mixed weight obtained by analytic hierarchy process and entropy weight method is used to evaluate the final determined evaluation system. Finally, an example of a regional power grid is used to verify that the evaluation system and method proposed in this paper can easily and accurately reflect the smart power grid efficiency status.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128371546","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: 2

Long-Term Electricity Price Forecast Using Machine Learning Techniques 利用机器学习技术预测长期电价

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881604

A. Yousefi, Omid Ameri Sianaki, D. Sharafi

{"title":"Long-Term Electricity Price Forecast Using Machine Learning Techniques","authors":"A. Yousefi, Omid Ameri Sianaki, D. Sharafi","doi":"10.1109/ISGT-Asia.2019.8881604","DOIUrl":"https://doi.org/10.1109/ISGT-Asia.2019.8881604","url":null,"abstract":"Predicting the performance of energy commodities has long been a global priority for researchers and investors in the Energy sector. Large green field and brown field projects (often exceeding 1bn USD) are financed with locked in capital from the start, and typically take decades to return. Despite being one of the most important aspects of investment decision making, the prediction methodologies used widely today are not sophisticated enough to provide accurate insights for the investors. The new approach was proposed in this research to provide data analytics backed analysis for the performance of energy related commodities using innovative feature discovery methods and machine learning tools. In the presented research, a machine learning model was trained to predict the average monthly price of electricity in the next 5 years with focus on the California State energy market. Data points from 2001 to 2017 were collected and 78 data points are considered for analyses to select the highly-correlated features which could potentially affect the electricity price in the medium to long term. An economic case study is undertaken to understand the correlation of the features, and to avoid multicollinearity. In the next step, the selected features are applied into an S-ARIMA time series prediction algorithm. In addition, several feature-based machine learning algorithms are applied to the data and the results analysed and compared to find the effective forcasting approach. The findings demonstrated promising results for three years future price prediction horizon. Further studies are required to get more accurate electricity results beyond three years horizon.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124629091","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: 5

A Two-Stage Improved Droop Control Method for Economic Operation of Islanded DC Microgrids 孤岛直流微电网经济运行的两级改进下垂控制方法

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881374

Fengzhou Sun, Pengcheng Yang, Jie Zhu, He Zhao, Miao Yu, Wei Wei

引用次数: 1

Impact of Frequency-Responsive Wind Turbines on Power System Stability 频率响应型风力发电机对电力系统稳定性的影响

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881412

Li Sun, Yanfeng Ge, Dong Wang, Yunhe Hou

引用次数: 0

A Decompositon Method for Weekly Unit Commitment Considering Hydro Power Characteristics 考虑水电特性的周机组负荷分解方法

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8880876

Chenjia Feng, Chengcheng Shao, S. Zhang, Yanan Wang, Ding Li

引用次数: 0

An Optimization Method Based on Time-Sharing Energy Complementation to Determine Transmission Capacity of Wind-CSP Plants Combined System 基于分时能量互补的风电-光热联合系统输电容量优化方法

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) Pub Date : 2019-05-01 DOI: 10.1109/ISGT-Asia.2019.8881230

Yang Cui, Huiquan Zhang, Siyu Huang, Bo Xu

{"title":"An Optimization Method Based on Time-Sharing Energy Complementation to Determine Transmission Capacity of Wind-CSP Plants Combined System","authors":"Yang Cui, Huiquan Zhang, Siyu Huang, Bo Xu","doi":"10.1109/ISGT-Asia.2019.8881230","DOIUrl":"https://doi.org/10.1109/ISGT-Asia.2019.8881230","url":null,"abstract":"Since northwest China has abundant wind and solar resources, constructing the concentrating solar power (CSP) plant near to the wind-generated electricity factory tend to a common form of energy exploiting. How to size for the capacity of the transmission line to meet the demand of delivery of the wind-concentrated solar power (CSP) plant system becomes an intensive problem. Based on the theory of time-sharing energy complementarity, this paper proposes a mathematical optimization model of the integrated output of Wind farm and CSP plant to suppress the power fluctuations. Then, by independently considering the impacts of the thermal storage capacity of CSP plant, the capacity optimization model of transmission line of wind power-CSP combined system is established. The case result demonstrates that the proposed method can reduce the investment cost of transmission line by reasonably configuring the thermal storage capacity of CSP. Moreover, the proposed strategy significantly improves the utilization rate of the transmission line and increases the comprehensive income of the joint generation system.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123358827","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