2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)最新文献_第3页

Clustering and Previous Visit Dependency Technique for Electric Vehicle Station Visits 电动汽车站点访问的聚类与既往访问依赖技术

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571874

W. Infante, Jin Ma

引用次数: 0

A Scenario-Based Framework for Technical Validation of Demand Response 需求响应技术验证的基于场景的框架

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571424

Martina Bucciarelli, S. Paoletti, A. Vicino

引用次数: 0

Extended Kalman filter for voltage dips detection in grid with distributed energy resources 基于扩展卡尔曼滤波的分布式电网电压骤降检测

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571857

V. Katić, Aleksandar M. Stanisavljević, R. Turovic, B. Dumnic, B. Popadic

引用次数: 4

Definition and Calculation of Power Limit Values for Distribution Grids - Basics of Comprehensive Demand Side Managemen 配电网功率限值的定义和计算。需求侧综合管理的基础

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571848

Tobias Heß, P. Schegner

引用次数: 0

A N4SID-Based Strategy to Estimate the Parameters of Disturbances in Power Systems 基于n4sid的电力系统扰动参数估计策略

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571689

M. Mansouri, D. Westwick, A. Knight

{"title":"A N4SID-Based Strategy to Estimate the Parameters of Disturbances in Power Systems","authors":"M. Mansouri, D. Westwick, A. Knight","doi":"10.1109/ISGTEurope.2018.8571689","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571689","url":null,"abstract":"A blind identification method based on Subspace State Space System IDentification (N4SID) is proposed to identify the parameters of disturbances, such as electromechanical modes and harmonics, in a power system. The challenge, however, is how to identify the disturbances without the knowledge of systems' inputs. The disturbances are only measured by Phasor Measurement Units (PMUs) in the power system as signals representing the system's outputs; the system's parameters and inputs have to be estimated only from the measured outputs. This leads to a blind identification problem; therefore, N4SID, categorized as blind identification, is employed to address the problem. To solve the problem, the output data is formulated in the N4SID terminology, system matrices are calculated in 6 steps, and finally, the forward stochastic model of the system is derived. The proposed method has some advantages such as robustness and no need to know the parameters of the power system for design. To evaluate the performance of the proposed method, simulation studies are carried out on two practical power systems. The simulations show that the proposed method has a desirable performance.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132638505","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

Data Analytics to Support Operational Distribution Network Monitoring 数据分析支持运营配电网监控

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571550

Eleni Tsioumpri, B. Stephen, Neil Dunn-Birch, S. Mcarthur

{"title":"Data Analytics to Support Operational Distribution Network Monitoring","authors":"Eleni Tsioumpri, B. Stephen, Neil Dunn-Birch, S. Mcarthur","doi":"10.1109/ISGTEurope.2018.8571550","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571550","url":null,"abstract":"The operation of distribution networks has become more challenging in recent years with increasing levels of embedded generation and other low carbon technologies pushing these towards their design limits. To identify the nature and extent of these challenges, network operators are deploying monitoring equipment on low voltage feeders, leading to new insights into fault behaviour and usage characterisation. With this heightened level of observability comes the additional challenge of finding models that translate raw data streams into outputs on which operational decisions can be based or supported. In this paper, operational low voltage substation and feeder monitoring data from a UK distribution network is used to identify fault occurrence relations to localised meteorological data, characterise the localised network sensitivities of demand dynamics and infer the effects of embedded generation not visible to the network operator. These case studies are then used to show how additional operational context can be provided to the network operator through the application of analytics.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134605215","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

$k$-means based identification of common supply tasks for low voltage grids -基于均值的低压电网常见供电任务识别

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571658

C. Kittl, Dzanan Sarajlic, C. Rehtanz

引用次数: 8

Evaluation of Voltage Regulation Functions of Smart Inverters Based on Penetration Level and Curtailment in Photovoltaic Systems 基于光伏系统渗透水平和截流的智能逆变器调压功能评价

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571799

Yuta Takasawa, Satoru Akagi, S. Yoshizawa, H. Ishii, Y. Hayashi

引用次数: 4

Day-Ahead Optimal Reserve Capacity Planning Based on Stochastic RE and DR Models 基于随机RE和DR模型的日前最优备用容量规划

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571523

Wen-jun Tang, Sin-Yi Shih, Hong-Tzer Yang

{"title":"Day-Ahead Optimal Reserve Capacity Planning Based on Stochastic RE and DR Models","authors":"Wen-jun Tang, Sin-Yi Shih, Hong-Tzer Yang","doi":"10.1109/ISGTEurope.2018.8571523","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571523","url":null,"abstract":"Renewable energy (RE) is commonly used nowadays not only to fulfill the increasing power demand but also to reduce global warming and environmental pollution. However, the uncertain characteristics of renewable energy heavily affect the capacity planning of operating reserve and thus reduce the reliability and security of power system. Appropriate planning of reserve capacity is, therefore, needed to solve these problems while maintaining cost minimization and power system stability. The proposed planning is performed based on a day-ahead market with the reserve providers including external grid, automatic generation control, demand response (DR) program and RE curtailment. Stochastic models including independent uncertainty-related factors of RE generation and load are constructed in Monte Carlo simulations. To keep the dynamic reserve adequate and solve the aforementioned risk and cost balance problem, a chance-constrained optimal power flow is employed as a probabilistic constraint to enforce operating reserve to offer a certain extent backup capacity and risk tolerance. Moreover, the effectiveness of DR is also imitated with cross-elasticity and self-elasticity for the amount and price a consumer will bid in DR market. To verify the proposed approach for reserve capacity planning, the proposed method is tested in a modified IEEE 30-bus system with high RE penetration. The result shows a day-ahead arrangement of operating reserve with good efficiency and economy.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114758626","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

Experimental Assessment of the Prediction Performance of Dynamic Equivalent Circuit Models of Grid-Connected Battery Energy Storage Systems 并网蓄电池储能系统动态等效电路模型预测性能的实验评估

2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) Pub Date : 2018-10-01 DOI: 10.1109/ISGTEurope.2018.8571787

Emil Namor, F. Sossan, E. Scolari, R. Cherkaoui, M. Paolone

{"title":"Experimental Assessment of the Prediction Performance of Dynamic Equivalent Circuit Models of Grid-Connected Battery Energy Storage Systems","authors":"Emil Namor, F. Sossan, E. Scolari, R. Cherkaoui, M. Paolone","doi":"10.1109/ISGTEurope.2018.8571787","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571787","url":null,"abstract":"The paper discusses the model identification, validation and experimental testing of current-to-voltage dynamic circuit models for a grid-connected MW-class battery. The model refers to an utility-scale 720 kVA/560 kWh battery energy storage system (BESS) and is used in a model predictive control framework to forecast the evolution of the battery DC voltage as a function of the current trajectory. The model is identified using measurements from a dedicated experimental session where the BESS is controlled with a pseudo random binary signal (PRBS) to excite the system on a broad spectrum. The identified model relies on the assumption that the battery is a single cell. To test this assumption and assess the quality of predictions, we test the model performance by using a second data set coming from a real-life power system application, where the BESS is used to dispatch the operation of a group of stochastic prosumers (demand and PV generation). Experimental results show that the root mean square voltage prediction error of the best performing model (i.e. two time constant model, TTC) is less than 0.55 % for look-ahead times in the range 10 seconds-l0 minutes and better than persistence for all considered forecasting horizons.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114969540","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: 7