E3S Web Conf.
Volume 53, 20182018 3rd International Conference on Advances in Energy and Environment Research (ICAEER 2018)
|Number of page(s)||8|
|Section||Environmental Protection, Pollution and Treatment|
|Published online||14 September 2018|
Design of An Intelligent Hierarchical System for Fingerprint Management of Electricity Loads Based on Operating Characteristics of Household Appliances
Electric Power Research Institute of Guizhou Power Grid Co., Ltd, Guizhou, Guiyang 550002, China
2 Suzhou Huatian Power Technology Co., Ltd, Jiangsu, Suzhou 215000, China
3 Guizhou University, Guizhou, Guiyang 550025, China
* Corresponding author: Lefeng Cheng, email@example.com
In order to facilitate the active identification capability of various types of electrical equipment, so as to enhance the functions such as the behavioural analysis and optimization control of electricity utilization in an automatic demand side management (DSM) system. A definition is given on load fingerprint based on operating characteristics of household appliances, as well as its architecture. In addition, based on the cyber-physical systems (CPS) technology, a hierarchical technical framework for load fingerprint management is proposed. This framework is a two-layer electricity utilization load fingerprint management platform, including local management and cloud-based management. Finally, two hardware prototypes are developed, including a socket-type smart collection terminal and an intelligent interactive concentrator with multiple communication technologies, which can provide strong hardware support for the realization of the hierarchical technical framework proposed in this paper.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.