Enabling demand side management : heat demand forecasting at city level
|Author:||Hietaharju, Petri1; Ruusunen, Mika1; Leiviskä, Kauko1|
1Control Engineering, Environmental and Chemical Engineering, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201902044001
Multidisciplinary Digital Publishing Institute,
|Publish Date:|| 2019-02-04
Implementation of new energy efficiency measures for the heating and building sectors is of utmost importance. Demand side management offers means to involve individual buildings in the optimization of the heat demand at city level to improve energy efficiency. In this work, two models were applied to forecast the heat demand from individual buildings up to a city-wide area. District heating data at the city level from more than 4000 different buildings was utilized in the validation of the forecast models. Forecast simulations with the applied models and measured data showed that, during the heating season, the relative error of the city level heat demand forecast for 48 h was 4% on average. In individual buildings, the accuracy of the models varied based on the building type and heat demand pattern. The forecasting accuracy, the limited amount of measurement information and the short time required for model calibration enable the models to be applied to the whole building stock. This should enable demand side management and lead to the predictive optimization of heat demand at city level, leading to increased energy efficiency.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research was funded by the Finnish Funding Agency for Innovation, TEKES through the project KLEI (40267/13) and the Academy of Finland through the project SEN2050 (287748).
|Academy of Finland Grant Number:||
287748 (Academy of Finland Funding decision)
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).