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Assessing power-to-heat technologies for industrial electrification: A multi-criteria decision analysis approach

Authors: Ashabi, Arman; Mostafa, Mohamed; Hryshchenko, Andriy; Bruton, Ken; T.J. O'Sullivan, Dominic;

Assessing power-to-heat technologies for industrial electrification: A multi-criteria decision analysis approach

Abstract

Transitioning industrial heat systems from fossil fuels to electric-based solutions is crucial to mitigate climate change. This research identifies and evaluates various power-to-heat technologies, each technology contributes uniquely to the overarching goal of industrial electrification. Through a rigorous methodology involving categorisation based on technology readiness level (TRL), electrification stage, carbon emission per each kWh of heat delivery, energy efficiency, installation complexity, and life span, a Multi-Criteria Decision Analysis (MCDA) is conducted to assess the performance of each technology. To validate the proposed ranking, the weighted sum method (WSM) was compared to the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In addition to prioritizing each criterion, six scenarios were investigated using sensitivity analysis to determine the performance of each criterion and ranking of technologies using a scenario based weighting technique. The study indicates Heat Pump and Mechanical Vapor Recompression as the most dependable and high-performing technologies, continuously giving top marks and serving as the finest solutions for a wide range of applications. In contrast, Plasma Technology and Microwave and Radio frequency heaters are regarded as the least effective, with continuously low ratings, making them less desirable alternatives. By synthesizing the results and defining different scenarios, this detailed analysis provides decision-makers, industry stakeholders, and researchers with useful insights into the many alternatives for direct electrification of heat supply. Finally, the MCDA in this study is designed for current and future scenarios, allowing new technologies to be analyzed and ranked with the proposed algorithm.

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Keywords

Electrification, Energy efficiency, Power-to-heat, TA1-2040, Engineering (General). Civil engineering (General), Scenario analysis, Decision support

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
Green
gold