A Novel Data Management Methodology and Case Study for Monitoring and Performance Analysis of Large-Scale Ground Source Heat Pump (GSHP) and Borehole Thermal Energy Storage (BTES) System

Oleg Todorov,Risto Kosonen,Kari Alanne,Markku Virtanen

doi:10.3390/en14061523

Oleg Todorov, Risto Kosonen + Show 2 more

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https://doi.org/10.3390/en14061523

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Journal: Energies	Publication Date: Mar 10, 2021
Citations: 8	License type: CC BY 4.0

Affiliation: Aalto University, Nanjing Tech University

Abstract

Aalto New Campus Complex (ANCC) is a recently inaugurated educational facility at Aalto University, located in Otaniemi (Espoo), Finland. Within over 40,000 m2, it comprises two faculties, a shopping center, recreational areas, and a metro station. ANCC is also a large-scale application of Ground Source Heat Pump (GSHP)–Borehole Thermal Energy Storage (BTES) in Finland, comprising an irregular BTES field of 74 boreholes with an overall length of roughly 23 km and 4 million m3 of energy storage. Therefore, accurate monitoring of the GSHP–BTES energy system is crucial for sustainable and efficient long-term operation. Due to the fundamental issues affecting the accuracy of all thermal energy meters, a novel methodology adjusting for consistency of the measured data (in order to accomplish daily energy balance on both sides of the GSHP) is developed. The proposed methodology is used also in conjunction with reconstruction of missing relevant data before April/May 2020 by applying linear regression techniques. The developed data management is considered essential due to its capability to handle measured data with high uncertainty (thermal meters) by using highly accurate data regarding the GSHP power demand. Additionally, operational data and relevant GSHP performance indicators for the 18-month period starting from July 2019 is presented and analyzed.

Highlights

The energy footprint of buildings accounted for 29% of overall primary energy consumption globally in 2018, according to BP Energy Outlook 2020 [1]
The aim of the present research is to develop and implement a novel data management methodology to assess the performance of a complex ground source heat pumps (GSHP)–Borehole Thermal Energy Storage (BTES) system, the New Campus Complex of Aalto University, under the conditions of high uncertainty related to measured data
The novelty of this paper is to introduce a developed Data Validation and Reconciliation (DVR) methodology for data management adjusting the measured data for consistency in order to achieve the necessary energy balances on both sides of the GSHP

Summary

Introduction

The energy footprint of buildings accounted for 29% of overall primary energy consumption globally in 2018, according to BP Energy Outlook 2020 [1]. As a result, making heating and cooling more sustainable and efficient is a priority for the EU [2] In this context, ground source heat pumps (GSHP) in tandem with underground thermal energy storage (UTES) is an attractive technological option for efficient dispatching of heating and cooling loads, the integration of renewable energy sources (RES), and waste heat. Ground source heat pumps (GSHP) in tandem with underground thermal energy storage (UTES) is an attractive technological option for efficient dispatching of heating and cooling loads, the integration of renewable energy sources (RES), and waste heat They are interesting when aiming for further decarbonization of the existing heating and cooling networks [3,4] and especially effective when applied in a centralized/shared way in a district level [5]. This has happened especially between 2015 and 2020 when their utilization almost doubled to 167 TWh/year and the installed capacity increased by 54%, reaching 77.5 GWt [6]

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