Assessing power-to-heat technologies for industrial electrification: A multi-criteria decision analysis approach - Arman Ashabi; Mohamed Mostafa; Andriy Hryshchenko; Ken Bruton; Dominic T.J. O’sullivan (Energy Conversion and Management: X, 2025)
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.