Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation最新文献_第2页

Colloidal Luminaries for Architectural Lighting 建筑照明用胶体灯具

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3361014

Nina M. Lutz, V. Bove

引用次数: 0

BESOS 亲吻

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3360995

Gaëlle Faure, T. Christiaanse, R. Evins, Gaby M. Baasch

引用次数: 7

Monitoring Electric Grid Reliability Using Satellite Data 利用卫星数据监测电网可靠性

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3361010

Zeal Shah, Jay Taneja

引用次数: 0

A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK 使用NILMTK的可重复的最先进的能量分解演示

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3360999

Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, R. Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo C. M. Meira, Oliver Parson

{"title":"A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK","authors":"Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, R. Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo C. M. Meira, Oliver Parson","doi":"10.1145/3360322.3360999","DOIUrl":"https://doi.org/10.1145/3360322.3360999","url":null,"abstract":"Non-intrusive load monitoring (NILM) or energy disaggregation involves separating the household energy measured at the aggregate level into constituent appliances. The NILM toolkit (NILMTK) was introduced in 2014 towards making NILM research reproducible. NILMTK has served as the reference library for data set parsers and reference benchmark algorithm implementations. However, few publications presenting algorithmic contributions within the field went on to contribute implementations back to the toolkit. This work presents a demonstration of a new version of NILMTK [2] which has a rewrite of the disaggregation API and a new experiment API which lower the barrier to entry for algorithm developers and simplify the definition of algorithm comparison experiments. This demo also marks the release of NILMTK-contrib: a new repository containing NILMTK-compatible implementations of 3 benchmarks and 9 recent disaggregation algorithms. The demonstration covers an extensive empirical evaluation using a number of publicly available data sets across three important experiment scenarios to showcase the ease of performing reproducible research in NILMTK.","PeriodicalId":128826,"journal":{"name":"Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117142010","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

Peak Demand Reduction using Energy Storage System for Demand Response 利用储能系统进行需求响应的高峰需求降低

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3360988

Hannie Zang, Sunyong Kim, D. Kang, Hyuk Lim

引用次数: 0

Lightweight, Deep RNNs for Radar Classification 用于雷达分类的轻量级、深度rnn

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3361000

Dhrubojyoti Roy, S. Srivastava, Pranshu Jain, Aditya Kusupati, M. Varma, A. Arora

引用次数: 5

Generative Interior Design using BIM 使用BIM生成室内设计

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3360997

C. Sydora, Eleni Stroulia

引用次数: 3

Towards Class-Balancing Human Comfort Datasets with GANs 基于gan的人体舒适度类平衡数据集研究

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3361016

Matias Quintana, Clayton Miller

引用次数: 11

Development of a clustering-based morning start time estimation algorithm for space heating and cooling 基于聚类的空间供暖和制冷早晨启动时间估计算法的开发

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3360840

Burak Gunay, Zixiao Shi, Araz Ashouri, G. Newsham

{"title":"Development of a clustering-based morning start time estimation algorithm for space heating and cooling","authors":"Burak Gunay, Zixiao Shi, Araz Ashouri, G. Newsham","doi":"10.1145/3360322.3360840","DOIUrl":"https://doi.org/10.1145/3360322.3360840","url":null,"abstract":"The morning start time of heating and cooling equipment plays an important role in the energy and comfort performance of buildings. Existing algorithms to guide this decision require either many data types with a consistent labelling nomenclature or a detailed calibrated model. In this paper, a model-free clustering-based morning start time estimation algorithm is put forward. The algorithm inputs only four types of data: indoor and outdoor temperatures, and heating and cooling energy use, and does not require any information regarding the location of the temperature sensors. The algorithm consists of four steps. The first one employs clustering to form groups of zones with a similar temperature response. The second one searches for inflection points to identify cluster temperature change rates during morning start-up periods. The third one determines the start time based on previous morning start-up temperature change rates. The last one estimates the energy savings potential by using bivariate change point models. The algorithm was developed by using a dataset from a large office building. Through hierarchical clustering, the data from 142 temperature sensors were consolidated to only seven clusters. The median morning start-up temperature change rates in individual clusters were between 0.3°C/h and 0.8°C/h for heating, and between -0.5°C/h and -1.2°C/h for cooling. The savings potential by tuning daily start times based on this information was estimated as 3% and 7% for heating and cooling, respectively.","PeriodicalId":128826,"journal":{"name":"Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133370989","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

Investigating occupancy profiles using convolutional neural networks 用卷积神经网络调查占用情况

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI: 10.1145/3360322.3360989

J. Park, Jianli Chen, Xin Jin, Z. Nagy

引用次数: 3