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access icon openaccess Modelling and evaluation of the Baseline Energy Consumption and the Key Performance Indicators in Technical University of Cluj-Napoca buildings within a Demand Response programme: a case study

This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Received 27/01/2020, Accepted 14/08/2020, Revised 05/08/2020, Published 27/10/2020

Demand response (DR) programmes offer to customers the opportunity to reduce the power peak and the energy consumption in response to a price signal or financial incentive. Typically, the request to reduce peak demands is made for a specific time period on a specific day, which is referred to as a DR event. To predict a reference energy consumption level in case of different buildings or blocks of buildings within the Technical University of Cluj-Napoca, this study proposes an artificial intelligence enhanced energy profiling method and a more intuitive yet simple method for baseline determination, easy to understand, which allows all the interested parties to estimate the energy and economy savings after a DR event. Once the baseline electric load profile is established, the aim of this study is to calculate some predefined key performance indicators. The two baseline detection methods are compared with each other as a measure of DR event effectiveness. The study has been conducted to clearly demonstrate the economic and environmental benefits of controlling the aggregated load curve in blocks of buildings within several effectively applied DR programmes.

Inspec keywords: demand side management; educational institutions; pricing; energy consumption; building management systems

Other keywords: DR event effectiveness; baseline determination; baseline electric load profile; Technical University of Cluj-Napoca buildings; baseline energy consumption; baseline detection methods; specific time period; aggregated load curve; reference energy consumption level; economy savings; artificial intelligence enhanced energy profiling method; price signal; predefined key performance indicators; DR programmes; financial incentive; demand response programme

Subjects: Power system management, operation and economics; Buildings (energy utilisation)

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