2022 IEEE Conference on Technologies for Sustainability (SusTech)最新文献

{"title":"Modeling and Optimization of Energy Performance for a Water-Cooled Chiller Plant deployed in Multi-story Office Building","authors":"Yesaswini Chilukuri, Samit Bhowmick, P. Dubey, Adil Usman","doi":"10.1109/SusTech53338.2022.9794231","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794231","url":null,"abstract":"This study presents an approach to calibrate energy performance model and optimization in control methods of HVAC to influence the annual energy consumption and operating cost savings. Calibration involves iterative improvements to bring model outputs in line with that of the measured date of an existing building. These models provide a means of understanding building operation as well as optimizing performance. Therefore, the study focuses to provide lessons learned and recommends best practices for effective calibration and optimization of water- cooled chiller for an office building located in Bangalore, India. The chiller size is of capacity 425TR with annual cooling energy consumption of 260 MWh. After carrying out 30 iterations in the model the resulted CVRMSE is 5% and NMBE of 1% are achieved. This calibrated model is further taken to find the optimized chiller outlet water temperature on the evaporator side. It is found that by an increase in outlet water temperature to 9°C, the energy savings were found to be 1.2% annually.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124810107","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}

{"title":"Using Smart Meter Data and Machine Learning to Identify Residential Light-duty Electric Vehicles","authors":"Alec Zhixiao Lin, A. James","doi":"10.1109/SusTech53338.2022.9794221","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794221","url":null,"abstract":"The growing adoption of electric vehicles (EVs) poses new challenges to power grids. To upgrade the grids with the increasing demand from charging EVs and from the change in customers consumption behaviors, utilities need to know where EV customers are. However, ownerships of EVs are not always known to utilities. This paper presents a methodology on how to use advanced metering infrastructure (AMI) data and apply machine learning to identify residential customers with EVs. It focuses on such aspects as how to perform sampling to reduce effects of external factors associated with other high-usage home appliances, how to create and evaluate variables for enhancing modeling, and how to apply the ensemble method to arrive at the estimation or forecasting needed for grid enhancement.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121034557","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}

{"title":"Sustainable Aviation Forum","authors":"J. Debauche","doi":"10.1109/sustech53338.2022.9794275","DOIUrl":"https://doi.org/10.1109/sustech53338.2022.9794275","url":null,"abstract":": We are now seeing a fundamental paradigm shift in the way the aviation sector is embracing a net-zero emissions target by 2050, with a common understanding that it will take multiple stakeholders Abstract: Electrification in aerospace is currently driven by developments in the Advanced Air Mobility segment. Hybrid and all-electric Commuter and eVTOL aircraft will transform existing markets or even create completely new markets. The technology to make this happen is there and the route to certification is getting more and more defined. This is the time to think about the next steps and upcoming challenges: How do we maintain these aircraft? How can we deploy the required charging infrastructure? And what role will digitally-enabled services and new business model play? electrification the Rolls-Royce team in 2019 acquisition of Siemens eAircraft where he previously as innovation manager. He holds master’s degree and PhD in engineering. Abstract: The Aviation industry has been on a journey to reach the future of carbon-neutral air transportation across the globe for four decades and has already made significant achievements through technological advancement and improvements in operations and infrastructure. Now as the aviation industry has committed to Net Zero Carbon emissions by 2050, it will require a fundamental change in how the industry comes together as an Ecosystem of stakeholders to deploy the technological advancements necessary to reach the net zero targets in the given timeframe. This paper will present a case study to establish a Sustainable Aviation EcoSystem Model for a Regional Airport whose primary objective is to address some key challenges around a rapidly evolving energy supply and distribution system, airport infrastructure and different types of aircraft technology deployment. Bio: Abstract: Aviation is moving into a very special, bright era. The speaker will talk about the challenges and opportunities that Aviation has been facing, and the new roadmap necessary to overcome these challenges and to be ready and successful over this bright era. The speaker will then go through some key perspectives of aviation electrification, which include Electrical Engineering Technology perspective, Additive Manufacturing perspective, WBG perspective, advanced digital perspective, and Gg CO 2 equivalent minimization perspective that electrical and electronics engineers need to be aware of, prepared for, and contribute to. Dr. Huang is a NAE Member, IEEE fellow, and SAE fellow. He received his Ph.D. Degree in Electrical Engineering from the University of Colorado at Boulder, Boulder, Colorado, USA in 1987. He has 35 years of experience in Aircraft Electrical Power Systems, Power Generations, Engine Starting, Power Electronics and Controls, and Electric Vehicle Drives. He has had US 80 patents including pending and multiple technical publications in the above-mentioned areas. Dr. Hao Huang is the winner of 2019 IEEE Transportation Technologi","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131571441","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}

{"title":"SusTech 2022 Cover Page","authors":"","doi":"10.1109/sustech53338.2022.9794214","DOIUrl":"https://doi.org/10.1109/sustech53338.2022.9794214","url":null,"abstract":"","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125140104","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}

{"title":"A sensor selection optimization framework for tracking CO2 flow movements in carbonates","authors":"Klemens Katterbauer, Abdallah Al Shehri, A. Qasim, A. Yousif","doi":"10.1109/SusTech53338.2022.9794198","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794198","url":null,"abstract":"4th Industrial Revolution (4IR) technologies have assumed critical importance in the oil and gas industry, enabling data analysis and automation at unprecedented levels. Formation evaluation and reservoir monitoring are crucial areas for optimizing reservoir production, maximizing sweep efficiency and characterizing the reservoirs. Automation, robotics and artificial intelligence (AI) have led to tremendous transformations in these domains in subsurface sensing, in particular. In this work, we present a novel 4IR inspired framework for the real-time sensor selection for subsurface pressure and temperature monitoring, as well as reservoir evaluation. The framework encompasses a deep learning technique for uncertain estimation of sensor data, which is then integrated into an integer programming framework for the optimal selection of sensors to monitor the reservoir formation. The results are promising, showing that a relatively small numbers of sensors can be utilized to properly monitor the fractured reservoir structure.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130579662","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}

{"title":"Harnessing the Power of Ocean Waves to Make Electric Energy","authors":"R. Kamali-Sarvestani, H. Nademi","doi":"10.1109/SusTech53338.2022.9794259","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794259","url":null,"abstract":"Power electronic converters are an enabling technology for the emerging marine energy applications such as Ocean Waves to produce electricity. This paper outlines the key components comprising the conceptual wave energy converter with modularity and scalability features into consideration to generate power efficiently. The studied wave converter could be deployed for several key functionalities, notably to supply electricity to coastal communities and for producing drinking clean water. The preliminary modeling and simulation results verify the design objectives, and some selected results are discussed in this paper.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131638776","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}

{"title":"Proposed Application for an Entity Component System in an Energy Services Interface","authors":"Tylor E. Slay, Grace B. Spitzer, R. Bass","doi":"10.1109/SusTech53338.2022.9794252","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794252","url":null,"abstract":"An Entity Component System is a data-oriented architecture originally developed to streamline video game performance. Despite being quite new, Entity Component Systems are relatively well established within the video game industry due to the cutting edge nature of research into performance, especially around graphics. However, Entity Component Systems have not been widely examined or adopted outside of that industry. We propose adopting an Entity Component Systems framework to serve the needs of an Energy Service Interfaces. We examine the needs of an Energy Service Interface, give an overview of open-source Entity Component Systems (ECSs) libraries, examine some preliminary performance results for ECSs, and explore the traditional approach to fulfilling the needs of an Energy Service Interface (ESI) with database architectures.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132224420","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}

{"title":"Deterioration Modeling and Failure Analysis of Water Distribution Networks","authors":"T. Dawood, E. Elwakil, H. Novoa, J. Delgado","doi":"10.1109/SusTech53338.2022.9794138","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794138","url":null,"abstract":"This paper presents a novel framework for the deterioration modeling in conjunction with quantifying the water network’s failure index. It involves developing a method and an intelligent model using Monte Carlo Simulation to estimate the deterioration indices (DIs) of watermains through intricate iterative simulations. The developed method is implemented on the water system of the City of El Pedregal in Peru. The efficacy of this framework has been verified against the multiple linear regression (MLR) method and proved to be sound. The developed framework provides insights for infrastructure managers in the aspects of, when to intervene, what to maintain, replace, or rehabilitate.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116122302","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}

{"title":"Non-intrusive Electric-vehicle Load Disaggregation Algorithm for a Data-driven EV Integration Strategy","authors":"A. James, Alec Zhixiao Lin","doi":"10.1109/SusTech53338.2022.9794150","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794150","url":null,"abstract":"Electric vehicle (EV) charger demand has increased from 1.44 kW to between 3.3 kW and 17.2/19.2 kW [1] in the past 10 years – a 3 to 17/19 times the average consumption from a single home. By 2045 EV penetration will on average grow by 34 times (GWh) from today in Southern California Edison’s (SCE) territory [2]. To develop a data-driven utility EV grid integration strategy, EV customer charging behaviors need to be well understood. The ability to disaggregate EV loads, or segregate EV loads from household loads, is very useful in supporting enterprise forecasting and distribution planning, developing distribution standards, and capital request justification for a utility general rate case. EV telemetry and individual metered EV loads are not always available to the utility. In this paper, we present a lightweight efficient EV disaggregation methodology, with several advantages using real power measurements from advanced meter infrastructure (AMI) meters and demonstrated the algorithm and utility applications at scale (approximately 62,000 customers), and showed how the results can support utilities’ strategic need to develop a reliable, affordable, and safe EV integration strategy.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"27 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128966584","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}

{"title":"System Design and PV Sizing of a Micro Solar Electric Vehicle for Pakistan","authors":"A. Husnain, M. Iqbal","doi":"10.1109/SusTech53338.2022.9794247","DOIUrl":"https://doi.org/10.1109/SusTech53338.2022.9794247","url":null,"abstract":"Transport sector is the third largest contributor of GHG emissions globally. To counter this, global EV adoption has been increasing at a rapid rate. However, Pakistan has been left far behind in this race and is very slow to EV adoption, due to a number of factors including energy shortfall, lack of purchase power and absence of charging infrastructure to name a few. Therefore, a design for simple yet economical micro solar electric vehicle has been proposed. This paper covers the sizing and system design for the solar PV system for a solar electric vehicle on HOMER Pro. It also gives an economic analysis of all the components involved.","PeriodicalId":434652,"journal":{"name":"2022 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124510975","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}