Day-ahead prediction of hourly electric demand in non-stationary operated commercial buildings: A clustering-based hybrid approach-Reference-Cited by-同舟云学术

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Day-ahead prediction of hourly electric demand in non-stationary operated commercial buildings: A clustering-based hybrid approach

Published:2017-08 Issue: Volume:148 Page:228-237
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Chen Yibo,Tan Hongwei,Berardi Umberto

Funder

Zhejiang Zhengling New Energy Technology Co. Ltd

China Intelligent Urbanization Co-creation for High Density Region

NSERC DG project

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Building and Construction,Civil and Structural Engineering

Reference37 articles.

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2. Demand flexibility versus physical network expansions in distribution grids;Spiliotis;Appl. Energy,2017

3. A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems;Nosratabadi;Renew. Sustain. Energy Rev.,2017

4. Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques;Fan;Appl. Energy,2014

5. Demand-side management and optimal operation of industrial electricity consumers: an example of an energy-intensive chemical plant;Xenos;Appl. Energy,2016

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