Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment

Journal article

Francis, C., Hansen, P., Guðlaugsson, B., Ingram, D.M. and Thomson, C.R. (2022). Weighting Key Performance Indicators of Smart Local Energy Systems: A Discrete Choice Experiment. Energies. 15 (24), p. 9305. https://doi.org/10.3390/en15249305
AuthorsFrancis, C., Hansen, P., Guðlaugsson, B., Ingram, D.M. and Thomson, C.R.
Abstract

The development of Smart Local Energy Systems (SLES) in the UK is part of the energy transition tackling the energy trilemma and contributing to achieving the Sustainable Development Goals (SDGs). Project developers and other stakeholders need to independently assess the performance of these systems: how well they meet their aims to successfully deliver multiple benefits and objectives. This article describes a step undertaken by the EnergyREV Research Consortium in developing a standardised Multi-Criteria Assessment (MCA) tool—specifically a discrete choice experiment (DCE) to determine the weighting of key performance indicators (KPIs). The MCA tool will use a technology-agnostic framework to assess SLES projects, track system performance and monitor benefit realisation. In order to understand the perceived relative importance of KPIs across different stakeholders, seven DCEs were conducted via online surveys (using 1000minds software). The main survey (with 234 responses) revealed that Environment was considered the most important criterion, with a mean weight of 21.6%. This was followed by People and Living (18.9%), Technical Performance (17.8%) and Data Management (14.7%), with Business and Economics and Governance ranked the least important (13.9% and 13.1%, respectively). These results are applied as weightings to calculate overall scores in the EnergyREV MCA-SLES tool.

Keywords multi-criteria assessment; MCA; key performance indicators; KPI; Smart Local Energy Systems; SLES; discrete choice experiments
Year2022
JournalEnergies
Journal citation15 (24), p. 9305
PublisherMDPI
ISSN1996-1073
Digital Object Identifier (DOI)https://doi.org/10.3390/en15249305
Web address (URL)https://www.mdpi.com/1996-1073/15/24/9305
Publication dates
Print08 Dec 2022
Publication process dates
Accepted19 Nov 2022
Deposited10 Jan 2023
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File Access Level
Open
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