2015 IEEE Green Energy and Systems Conference (IGESC)最新文献

Siting and sizing dispersed energy storage in power transmission networks 输电网络中分散储能的选址和规模

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359388

M. Moreira da Silva, R. Pastor, T. Shi, L. Zhao, J. Ye

引用次数: 2

Thermal behavior of aged lithium-ion batteries: calorimetric observations 老化锂离子电池的热行为:量热观察

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359386

Jan Geder, R. Arunachala, Shishir Jairam, A. Jossen

引用次数: 8

A distributed framework for frequency regulation in large-scale prosumer-based power systems 大型产用电力系统中频率调节的分布式框架

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359391

M. Nazari

引用次数: 4

Economics of residential energy arbitrage in california using a PV system with directly connected energy storage 加州住宅能源套利的经济学使用光伏系统与直接连接的能源存储

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359453

Richard K. Lam, Duc H. Tran, H. Yeh

引用次数: 19

The optimal planning and dynamic operation of distributed generation method based on modified multiobjective optimization in power distribution system 基于修正多目标优化的配电系统分布式发电优化规划与动态运行

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359390

Tairen Chen, O. Lavrova, Jane Lehr

{"title":"The optimal planning and dynamic operation of distributed generation method based on modified multiobjective optimization in power distribution system","authors":"Tairen Chen, O. Lavrova, Jane Lehr","doi":"10.1109/IGESC.2015.7359390","DOIUrl":"https://doi.org/10.1109/IGESC.2015.7359390","url":null,"abstract":"This paper proposes an optimal method to plan and dynamically operate the distributed generation (DG) based on the modified nondominated sorting genetic algorithm II (NSGA-II). First, the uncertainty of load and DG (photovoltaic panels) output are considered. Daily summer load data and ideal photovoltaic (PV) panels output data are taken from a local electrical company in Albuquerque. To model the uncertainty of load, the daily load is randomized to each bus for every time interval (15 minutes), but with their sum equal to the daily load. The uncertainty of PV output is modeled by adding the cloudy index and frequency factor to the ideal PV output. Second, the placement of a DG is defined by voltage sensitivity analysis. The bus with high voltage sensitivity is considered to have priority for the installation of DG. To find the optimal daily operation of DG, a multiobjective problem is formulated that focuses on the minimization of a circuit's voltage deviations, active and reactive power losses. To solve the problem, the traditional NSGA II is modified by incorporating a fuzzy logic decision model. The fuzzy logic model selects an optimally compromised solution from the Pareto front by analyzing its weights of voltage deviations, active and reactive power losses. The selected solution includes the optimal outputs for every generator, synchronous compensator, capacitor bank, and PV panels for each time interval. Furthermore, to operate DG optimally and dynamically, the method's computation speed is crucial. To increase the modified NSGA II computation speed, the population initialization space is reduced and the population is selected and saved for the next generation based on load analysis and experiments. The method is tested on the IEEE 14 bus and a local residential circuit. The results on reducing the power losses, voltage deviations, and increasing the algorithm speed demonstrate the effectiveness of this method.","PeriodicalId":193746,"journal":{"name":"2015 IEEE Green Energy and Systems Conference (IGESC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114818093","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

Development of a nonlinear wind-turbine simulator for LPV control design 用于LPV控制设计的非线性风力机模拟器的开发

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359389

Xiangming Xue, Yiming Bu, B. Lu

引用次数: 3

A review of AC/DC microgrid-developments, technologies, and challenges 交流/直流微电网的发展、技术和挑战综述

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359384

R. Sabzehgar

引用次数: 33

Power flow optimization methods for distribution systems 配电系统潮流优化方法

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359385

Paula Quintana-Quiros, H. Yeh

{"title":"Power flow optimization methods for distribution systems","authors":"Paula Quintana-Quiros, H. Yeh","doi":"10.1109/IGESC.2015.7359385","DOIUrl":"https://doi.org/10.1109/IGESC.2015.7359385","url":null,"abstract":"Two power flow optimization methods for distribution systems are presented. Both methods provide local and global Volt-Ampere Reactive (VAR) control approaches to minimize the power loss in a single branch radial distribution system while maintaining the voltage variation in the line within constrained values. The first one referred to as Optimum uses all data required to produce optimum results, under the assumption that a Supervisory Control and Data Acquisition (SCADA) is fully available. Given that some power distribution systems lack the proper SCADA communication infrastructure to support the monitoring of large amounts of data; the second one referred to as Simplified excludes one of the optimization variables reducing the amount of data required to operate. The performance of these two optimization methods is compared in terms of power savings and voltage variation. In terms of power savings, simulation results indicate that the Optimum method performs better than the Simplified method by approximately 1%; this result observed for both global and local approaches. Simulation results also indicate that the voltage variation can be kept within the same margins regardless of the approach used.","PeriodicalId":193746,"journal":{"name":"2015 IEEE Green Energy and Systems Conference (IGESC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116786428","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

A comprehensive economic optimization plan for microgrids considering grid interconnection and line congestion 考虑并网和线路拥塞的微电网综合经济优化方案

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359382

Somayeh Abbasi, A. Jamehbozorg

引用次数: 1

Defining techniques for developing an energy analysis services on a middleware for technical optimism of green buildings 定义了在中间件上开发绿色建筑技术乐观主义能源分析服务的技术

2015 IEEE Green Energy and Systems Conference (IGESC) Pub Date : 2015-11-09 DOI: 10.1109/IGESC.2015.7359392

Alan D. Redmond, Peno Pan

{"title":"Defining techniques for developing an energy analysis services on a middleware for technical optimism of green buildings","authors":"Alan D. Redmond, Peno Pan","doi":"10.1109/IGESC.2015.7359392","DOIUrl":"https://doi.org/10.1109/IGESC.2015.7359392","url":null,"abstract":"This papers content is about evaluating how to utilise hybridisation of digital communications in order to secure sustainable approaches based on green buildings and infrastructure. The challenges associated with environmental and social impacts of building designs have created socio-economic impacts on our communities. There is an extensive push for “technical optimism” while engaging the communities that work and live in these environments. Smart grids and intelligent buildings require networked infrastructures. However, due to technical complexity relating to the lack of integration architecture (software) and the indication of social exclusion (referring to `exclusion-environment-architecture'), there is a real need for virtual multidisciplinary information systems. This paper studies the associated problems while investigating the issues relating to; i) BIM collaboration, and ii) BIM analytical modeling for energy analysis. The research strategy is based on inductive reasoning (bottom-up approach) were patterns and ideas are formed through a general review of new and existing technologies. The methodology focuses on presenting techniques used for developing an analytical energy web-based BIM model. The results of these theories contain measurable impacts relating to end user requirements and produce a mash-up diagram of process flow content for potential implementation within a virtual model.","PeriodicalId":193746,"journal":{"name":"2015 IEEE Green Energy and Systems Conference (IGESC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128119857","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