Prediction of DHW energy use in a hotel in Norway

Ivanko Dmytro,Harald Taxt Walnum,Sørensen Åse Lekang,Plesser Thale Sofie Wester,Nord Natasa,Sartori Igor

doi:10.1088/1757-899x/609/5/052018

Abstract

Domestic hot water (DHW) systems are significant consumers of energy in buildings. This article is dedicated to hourly and daily DHW energy use modeling, with the aim of achieving energy savings in buildings. The methods investigated in the article were tested using statistical data obtained from a hotel located in Oslo, Norway. For better modeling, the influence of various factors on DHW energy use in the hotel was studied. For this purpose, the wrapper approach was used. The analysis indicates that the most important variable that should be used in the model is number of guests. There are also other factors that can be taken in account, even though they do not have such strong influence. Traditionally, only daily data about number of guests are available in the hotels. These data do not allow us to develop accurate hourly model of DHW energy. The article therefore proposes a method which, based on introduction of artificial variables, improve accuracy of the hourly DHW model. Eight models are compered, based on criteria of their adequacy. The Support vector machine model shows the best results for daily modeling and the Partial least squares (PLS) regression for hourly modeling.

Highlights

Buildings are responsible for approximately one third of the energy use in the world [1]
Despite the higher computational time comparing to correlation matrix analysis, the application of wrapper algorithms is a powerful instrument for assessing the impact of different combinations of variables on Domestic hot water (DHW) energy use and development of accurate prediction models
The wrapper approach shows its high efficiency for determining variables affecting DHW energy use in the hotel

Summary

Introduction

Buildings are responsible for approximately one third of the energy use in the world [1]. Efficient use of energy in buildings is a topical issue from both an environmental and economic point of view. A domestic hot water (DHW) system is an essential part of most buildings, and contribute to 25-35% of the total energy use [2]. Many studies claim that a large potential for future energy savings in buildings lies in improving operation and design of DHW systems [3]. Mathematical modeling of energy use is a powerful tool for achieving energy saving in buildings. Prediction, data recovery, monitoring of energy use and other important tasks could be solved via accurate and physically valid mathematical modeling

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Results

Conclusion