2017 52nd International Universities Power Engineering Conference (UPEC)最新文献_第4页

Impact of distributed generation on radial distribution network with various load models 不同负荷模式下分布式发电对径向配电网的影响

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231905

Halime Hizarci, B. Turkay

{"title":"Impact of distributed generation on radial distribution network with various load models","authors":"Halime Hizarci, B. Turkay","doi":"10.1109/UPEC.2017.8231905","DOIUrl":"https://doi.org/10.1109/UPEC.2017.8231905","url":null,"abstract":"Distributed generation has become a popular research are with rapid increase on power demand. Optimal size and location of distributed generation are an important optimization problem to satisfy growing power demand. In this study, particle swarm optimization has been used for optimal placement and sizing of distributed generation to minimize power loss in distribution network considering different static load models such as constant power, constant current, constant impedance, residential, commercial, industrial and mixed load models. Results have shown that using this method, voltage profile of the distribution network has been improved and numbers of buses violating voltage limits have been reduced after distributed generation placement. Further power system operating point has been improved and loadability of network increased without violating bus voltage and line current limits. Analysis has been demonstrated on a 12.66 kV 33-bus radial distribution network. Mathematical models of the loads have been considered as voltage dependent exponential load model and practical values of the active and reactive power exponents for load models have been used to represent their influence on real power loss and voltage stability issues. Indices related with voltage stability and power loss presented in literature have been calculated to determine performance of the study. Besides less parameter requirement of particle swarm optimization method, it is easy to implement on large power systems and these characteristics make the method preferable.","PeriodicalId":272049,"journal":{"name":"2017 52nd International Universities Power Engineering Conference (UPEC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127622554","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: 8

Generic dynamic load models using artificial neural networks 基于人工神经网络的通用动态负荷模型

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231937

E. O. Kontis, Ioannis S. Skondrianos, T. Papadopoulos, A. Chrysochos, G. Papagiannis

{"title":"Generic dynamic load models using artificial neural networks","authors":"E. O. Kontis, Ioannis S. Skondrianos, T. Papadopoulos, A. Chrysochos, G. Papagiannis","doi":"10.1109/UPEC.2017.8231937","DOIUrl":"https://doi.org/10.1109/UPEC.2017.8231937","url":null,"abstract":"The increased availability of measurements in modern power systems, due to the advent of smart grids and the installation of phasor measurement units, has favored the development of dynamic load models using online recorded responses. However, load model parameters are significantly affected by loading conditions and change considerably due to the time-varying and weather-dependent composition of load. Therefore, load model parameters obtained from in-situ measurements are valid only for a narrow range of operating conditions. Scope of this paper is to propose a systematic identification procedure to develop generic dynamic load models, valid for a wide range of discrete operating conditions. For this purpose, two different generic modeling approaches are considered. The first approach is based on statistical analysis, while the second employs Artificial Neural Networks (ANNs). Several simulation scenarios are performed using the NEPLAN software to investigate the accuracy of the derived models over a wide range of different loading conditions, while their generalization capabilities are evaluated using the cross-validation technique.","PeriodicalId":272049,"journal":{"name":"2017 52nd International Universities Power Engineering Conference (UPEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127793721","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: 9

Evaluating the effect of wind-hydro hybrid power stations on the operation of Cretan power system 评价风-水电混合电站对克里特岛电力系统运行的影响

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231945

A. Tsikalakis, Y. Katsigiannis, E. Karapidakis, K. Fiorentzis

引用次数: 9

A comprehensive approach for analytical modeling of line commutated converter based multiterminal HVDC systems 基于线路换向变换器的多终端高压直流系统综合分析建模方法

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231912

M. Blechschmidt, C. Hahn, M. Luther

{"title":"A comprehensive approach for analytical modeling of line commutated converter based multiterminal HVDC systems","authors":"M. Blechschmidt, C. Hahn, M. Luther","doi":"10.1109/UPEC.2017.8231912","DOIUrl":"https://doi.org/10.1109/UPEC.2017.8231912","url":null,"abstract":"This paper presents an analytical model of Line Commutated Converter (LCC) based Multiterminal (MT) High-Voltage Direct Current (HVDC) systems. The approach is based on space phasor transformation and provides a modular HVDC model, since every converter of the MT system is carried out as an independent network. For each switching state of the converter — which is either two valve conduction or commutation — the space phasor transformation provides a subsystem in the complex plane; each of this consists of a voltage source, a grid impedance and a transformer impedance. The commutation current of each converter is derived from the imaginary part network of the respective subsystem. A generalization of the real part network leads to a generic subsystem for all switching states of the converter. A succeeding connection with a state space model of the DC network is performed; applying mesh analysis yields a differential equation system in order to derive the DC current. To verify the accuracy of the developed model, a comparison with an electromagnetic transient (EMT) model is carried out, which shows the consistence of the dynamic behavior.","PeriodicalId":272049,"journal":{"name":"2017 52nd International Universities Power Engineering Conference (UPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131107108","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

Fault detection using probabilistic prediction and data fusion on a bulk good system 基于概率预测和数据融合的大宗货物系统故障检测

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231878

Fernando Arévalo, Tariq Mohammed, Andreas Schwung

{"title":"Fault detection using probabilistic prediction and data fusion on a bulk good system","authors":"Fernando Arévalo, Tariq Mohammed, Andreas Schwung","doi":"10.1109/UPEC.2017.8231878","DOIUrl":"https://doi.org/10.1109/UPEC.2017.8231878","url":null,"abstract":"Industrial companies worldwide want to keep a steady performance of their processes. In order to ensure this, a company usually implements a continuous condition monitoring for their machines. Ideally, the company analyzes the resulting data and obtains an insight on the failure causes of the machines. Unfortunately, the data itself cannot always discover the hidden causes for a fault in the machine, due either to the big amount of data or its complexity. This paper applies probabilistic prediction and data fusion techniques for fault detection on a bulk good system. The data acquisition from the bulk good system is implemented using the OPC Unified Architecture (OPC-UA) Machine-to-Machine Communication Protocol. OPC-UA collects data from the automation platform, and stores it in batches. Each batch contains all system features. Firstly, the system data is analyzed by means of a centralized approach. For that purpose, the probabilistic methods Naïve Bayes and Full Bayes are implemented. Furthermore, a decentralized approach is implemented using a two-step method. The first step gathers the health status of the main components by means of a local analysis. The second step fuses the results of each component, in order to obtain an overall status. The results show that the data fusion approach improves the performance of the fault detection algorithm.","PeriodicalId":272049,"journal":{"name":"2017 52nd International Universities Power Engineering Conference (UPEC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133492774","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: 4

Power tracking in a MMC-multi-terminal HVDC system with centralized and decentralized MPC using a black box modeling approach 基于黑盒建模方法的集中式和分散式MPC的mmc -多终端高压直流系统功率跟踪

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8232017

T. Nowak, M. Suriyah, T. Leibfried

引用次数: 4

Addressing the conflict of interest between aggregators and DSOs in deregulated energy markets 在解除管制的能源市场中，解决集成商和dso之间的利益冲突

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231901

C. Heinrich, C. Ziras, S. You, H. Bindner

引用次数: 1

Energy storage for enhanced frequency response services 用于增强频率响应服务的能量存储

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231914

Alexander Cooke, D. Strickland, K. Forkasiewicz

引用次数: 17

Optimal voltage control in distribution feeders with large penetration of wind 大穿透风配电馈线电压最优控制

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231936

Seyhan Tural, O. Ceylan, S. Paudyal

引用次数: 0

Feasibility study of microgrid village with renewable energy sources 可再生能源微电网村可行性研究

2017 52nd International Universities Power Engineering Conference (UPEC) Pub Date : 2017-08-01 DOI: 10.1109/UPEC.2017.8231889

E. Loukakis, E. Karapidakis

{"title":"Feasibility study of microgrid village with renewable energy sources","authors":"E. Loukakis, E. Karapidakis","doi":"10.1109/UPEC.2017.8231889","DOIUrl":"https://doi.org/10.1109/UPEC.2017.8231889","url":null,"abstract":"The exploitation of distributed energy resources and problems associated with islanded energy grids are important in optimizing sustainability of electricity supply, where microgrids play a major role in the decentralized and dispersed production. As defined, a microgrid is a group of interconnected loads and distributed energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid. Can connect and disconnect from the grid to enable it to operate in both grid-connected or island mode (remoted). The main focus of this study is the evaluation of a remoted microgrid of Vorias village, located in the inland of Crete island. Considering the household, agricultural and industrial loads of the village, were chosen RESs, such as wind turbines, photovoltaic panels and occasionally, small storage units in case of excess production. Energy Storage and small biomass generators are proposed. The co-production of RESs aims the 100% energy independence, considering economic and environmental impact boundaries. To maintain the highest degree of reliability and security of the operating system, the designed potential project is also represented through Geographical Information Systems (GIS) in map forms (wind and solar energy potential maps). The region of Vorias village presents intense relief that justifies the installation of both wind and solar parks, regardless of the possibility of individual RESs installation in the settlements of the region.","PeriodicalId":272049,"journal":{"name":"2017 52nd International Universities Power Engineering Conference (UPEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128650359","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