2018 IEEE Conference on Technologies for Sustainability (SusTech)最新文献_第3页

Priority Model for Public-Private Partnership Investment in Energy Projects 能源项目公私合作投资优先模式

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671372

E. Elwakil, M. Hegab

引用次数: 0

Visual Analytics to Support the Service Design for Sustainable Mobility 可视化分析支持可持续移动的服务设计

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671353

Didem Gürdür, Liridona Sopjani

{"title":"Visual Analytics to Support the Service Design for Sustainable Mobility","authors":"Didem Gürdür, Liridona Sopjani","doi":"10.1109/SUSTECH.2018.8671353","DOIUrl":"https://doi.org/10.1109/SUSTECH.2018.8671353","url":null,"abstract":"Intelligent transport system is a general term for the combined application of communication technologies, control and information processing for transport systems. Intelligent transport system covers all modes of transportation—including public transport—and all elements of the transportation system, such as the vehicle, infrastructure, and the driver. Integrated transport system allows a series of new unconventional solutions to improve the safety of the traffic and to satisfy transport requirements using new technologies. The service design of these systems, however, brings along different challenges.The process of service design requires the designers to engage with user behavior and understand the usage patterns related to the intelligent transport systems. Today, there are no well-developed methods to support this engagement. This paper suggests a data-oriented visual analytics approach to support designers in their decision-making processes, the implementation of successful services for sustainable, shared mobility service systems, and data-oriented approaches. Moreover, this paper discusses visual analytics as a tool to aid service designers by enabling real-time data analytics support.To this end, this paper summarizes the current literature on system innovation, challenges related to the design of these systems for sustainability and presents a shared and connected mobility service case study to illustrate the benefits of having visual analytics platforms for sustainable and intelligent transport systems. The study concludes that intuitive, data-oriented, interactive visual analytics approach has the potential to support service designers to create a coherent picture of the user in the service design process.","PeriodicalId":127111,"journal":{"name":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123855320","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

Neuroevolution Based Optimization of Hybrid Transmission Shift Points 基于神经进化的混合动力变速器换挡点优化

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671374

J. Bower, Masood Shahverdi, David I. Blekhman

引用次数: 2

A Comparative Analysis of GridPIQ’s Fossil Fuel Dispatch Algorithm GridPIQ的化石燃料调度算法比较分析

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671328

Emily L. Barrett, Brandon L. Thayer, Sarah Newman, Seemita Pal, Karen Studarus

引用次数: 0

Definition of Market Performance Metrics to Enable Design and Valuation of Retail Transactive Energy System Markets 市场绩效指标的定义，以实现零售交易能源系统市场的设计和评估

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671375

B. Bhattarai, D. Hammerstrom, Peng Wang

{"title":"Definition of Market Performance Metrics to Enable Design and Valuation of Retail Transactive Energy System Markets","authors":"B. Bhattarai, D. Hammerstrom, Peng Wang","doi":"10.1109/SUSTECH.2018.8671375","DOIUrl":"https://doi.org/10.1109/SUSTECH.2018.8671375","url":null,"abstract":"This paper defines market performance metrics that will be useful for the comparison of alternative retail transactive energy system (TES) designs. Our key focus is to define an appropriate set of market performance metrics such that the metrics are free of bias and should be applicable to all TES designs. First, we categorize market performance into five categories - market efficiency, market power, market volatility, market fairness, and market reliability. Next, metrics that can quantity TES market performance were developed for each market performance category. To ease implementation, each metric is documented with a uniform structure: metric overview, formulation, significance/interpretation, inputs-outputs, and implementation. The paper is focused on comprehensive discussion on theoretical reasoning and applicability of these metrics to retail TES markets. Since TES theory is in its early stages, these market performance metrics will form a base set for market performance evaluation of TES designs. In addition, these metrics will provide not only insights about the effectiveness of alternative TES designs, but also guidance to further improve retail TES market designs.","PeriodicalId":127111,"journal":{"name":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130591852","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

Boosting DC/AC Ratio of PV Plant for BESS Integration on DC side 提高光伏电站直流/交流比，实现BESS直流侧集成

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671354

D. Meneghel, E. Bortoni, A. Karimi

引用次数: 7

Evaluating and Improving the Energy Performance of School Buildings with a Proposed Real-Time Monitoring System 利用实时监测系统评估和改善学校建筑的能源性能

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671347

Yaqing Chen, Xinming Li, Regina Dias Ferreira, M. Gül, I. Nikolaidis, Omid Ardakanian

{"title":"Evaluating and Improving the Energy Performance of School Buildings with a Proposed Real-Time Monitoring System","authors":"Yaqing Chen, Xinming Li, Regina Dias Ferreira, M. Gül, I. Nikolaidis, Omid Ardakanian","doi":"10.1109/SUSTECH.2018.8671347","DOIUrl":"https://doi.org/10.1109/SUSTECH.2018.8671347","url":null,"abstract":"Building energy consumption occupies a significant portion of the final energy consumption, and its trend is increasing. Due to a substantial contribution to the energy use of commercial sector by office buildings, much attention has been brought to them with energy-efficient measures. However, there are only a limited number of studies investigating the school building’s energy consumption performance, especially in Canadian cold climate, which it allows opportunities for improving school building’s energy efficiency. In this study, the historical electricity consumption and energy-related costs of Edmonton Catholic Schools are statistically analyzed. Energy benchmarking methods are applied to evaluate the energy performance of schools and categorize them. With the aim of improving the energy performance of school buildings by discovering energy saving opportunities existed in them, an electrical management program is proposed with the real-time monitoring system. The proposed framework for lowering the electricity consumption of schools can be continually used by school facility operators in the future to identify inefficient school buildings and electricity abusers inside them.","PeriodicalId":127111,"journal":{"name":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133712477","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

YoMoPie: A User-Oriented Energy Monitor to Enhance Energy Efficiency in Households YoMoPie:以用户为导向的能源监测系统，提高家庭能源效率

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671331

Christoph Klemenjak, Stefan Jost, W. Elmenreich

{"title":"YoMoPie: A User-Oriented Energy Monitor to Enhance Energy Efficiency in Households","authors":"Christoph Klemenjak, Stefan Jost, W. Elmenreich","doi":"10.1109/SUSTECH.2018.8671331","DOIUrl":"https://doi.org/10.1109/SUSTECH.2018.8671331","url":null,"abstract":"Computational methods for the enhancement of energy efficiency rely on a measurement process with sufficient accuracy and number of measurements. Networked energy meters, energy monitors, serve as vital link between energy consumption of households and key insights that reveal strategies to achieve significant energy savings. During the design of such an energy monitor, several aspects such as data update rate or variety of measured physical quantities have to be considered. This paper introduces YoMoPie, a user-oriented energy monitor based on the Raspberry Pi platform that aims to enable intelligent energy services in households. YoMoPie measures active as well as apparent power, stores data locally, and integrates an easy to use Python library. Furthermore, the presented energy monitor comes with a Python API enabling the execution of user-designed services to enhance energy efficiency in buildings and households. Along with the presented design, possible applications that could run on top of this system such as residential demand response, immediate user feedback, smart meter data analytics, or energy disaggregation are discussed. Finally, a case study is presented, which compares the measurement accuracy of YoMoPie to a certified energy analyser for a selection of common household appliances.","PeriodicalId":127111,"journal":{"name":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"63 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123445523","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

A Simple Approach for Sustainable Transportation Systems in Smart Cities: A Graph Theory Model 智慧城市可持续交通系统的简单方法:图论模型

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671384

Quinn Nelson, Donald Steffensmeier, Sachin Pawaskar

{"title":"A Simple Approach for Sustainable Transportation Systems in Smart Cities: A Graph Theory Model","authors":"Quinn Nelson, Donald Steffensmeier, Sachin Pawaskar","doi":"10.1109/SUSTECH.2018.8671384","DOIUrl":"https://doi.org/10.1109/SUSTECH.2018.8671384","url":null,"abstract":"The idea of public transportation is supported by most in theory but often heavily criticized by users when put into application. There are common tensions that are related to public transportation, as described by frequent users: unreliable, too crowded, and slow. The University of Nebraska-Omaha (UNO) is a growing metropolitan institution that uses a shuttle system to transport students among their three campuses daily. As of 2015, the current total student enrollment is approximately 16,000; UNO plans to enroll 20,000 students by 2020. The expected student growth is also reflected by the current construction of new buildings and expansion of UNO’s campus. Like most metropolitan universities, space and parking on a college campus is a limited resource, and UNO’s shuttle transportation system plays a vital role in ensuring student mobility between campuses. With growing pressure from the UNO community to improve kinesis there is a need to optimize intra-campus transportation in an environmentally sustainable manner. To alleviate the tensions involved with the UNO shuttle system, we have created an algorithm to model shuttle routes using graph theory. Once modeled, our program chooses an optimized route based on various conditions: time, volume of students anticipated to use the shuttle, and fuel cost. The algorithm created can be used to optimize transportation routes, alleviate user tension, and decrease the carbon footprint of transportation networks. Our project thus charts the future by improving student transportation methods and people movement between urban campuses in an environmentally friendly and efficient way.","PeriodicalId":127111,"journal":{"name":"2018 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"501 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124452894","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: 11

Artificial Neural Network Based Short Term Power Demand Forecast for Smart Grid 基于人工神经网络的智能电网短期电力需求预测

2018 IEEE Conference on Technologies for Sustainability (SusTech) Pub Date : 2018-11-01 DOI: 10.1109/SUSTECH.2018.8671340

S. N. Kulkarni, P. Shingare

引用次数: 1