A Cloud-Based Energy Management System for Building Managers

被引：3

作者：

Marmaras, Charalampos ^{[1
]}

Javed, Amir ^{[2
]}

Rana, Omer ^{[2
]}

Cipcigan, Liana M. ^{[1
]}

机构：

[1] Cardiff Univ, Sch Engn, Cardiff, Wales

[2] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, Wales

来源：

ICPE'17: COMPANION OF THE 2017 ACM/SPEC INTERNATIONAL CONFERENCE ON PERFORMANCE ENGINEERING | 2017年

基金：

英国工程与自然科学研究理事会;

关键词：

Electric Vehicles; Energy Storage; Energy Management System; Cloud computing; Triad Peak Estimation; CONSUMPTION; SMART; CLASSIFICATION; ALGORITHM; COMFORT;

D O I：

10.1145/3053600.3053613

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A Local Energy Management System (LEMS) is described to control Electric Vehicle charging and Energy Storage Units within built environments. To this end, the LEMS predicts the most probable half hours for a triad peak, and forecasts the electricity demand of a building facility at those times. Three operational algorithms were designed, enabling the LEMS to (i) flatten the demand profile of the building facility and reduce its peak, (ii) reduce the demand of the building facility during triad peaks in order to reduce the Transmission Network Use of System (TNUoS) charges, and (iii) enable the participation of the building manager in the grid balancing services market through demand side response. The LEMS was deployed on over a cloud-based system and demonstrated on a real building facility in Manchester, UK.

引用

页码：61 / 66

页数：6

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