In a groundbreaking study published in the journal *Systems*, a team of researchers, led by Jose M. Rivero-Iglesias from the Department of Customized Projects at EDP Clientes in Oviedo, Spain, has developed a novel approach to evaluating power generation technologies. The study introduces a combined hybrid group Multi-Criteria Decision-Making (MCDM) model that could significantly impact how energy sector professionals assess and select technologies for future projects.
The research team, which included six experts from the electricity sector, evaluated ten alternatives, comprising nine power generation technologies and Battery Energy Storage Systems (BESS). The study employed a hierarchical decision model that considered four main criteria: economic, environmental, technical, and social, along with 13 subcriteria. The team used the Analytic Hierarchy Process (AHP) to determine criteria weights and fuzzy VIKOR for ranking the alternatives.
One of the key innovations in this study is the use of a consensus technique to mitigate subjectivity in criteria weights stemming from diverse expert backgrounds. “This approach allows for a more collaborative and interactive evaluation process,” explained Rivero-Iglesias. “It fosters a more democratic and inclusive decision-making environment, which is crucial in the energy sector where stakeholders have varying perspectives and priorities.”
The findings revealed a significant preference towards renewable technologies, with Photovoltaic (PV) and Wind at the forefront. “Renewable technologies have consistently shown their potential in terms of sustainability and cost-effectiveness,” said Rivero-Iglesias. “Our study underscores the importance of transitioning towards a more sustainable energy mix.”
The study also evaluated three emerging energy technologies: BESS, Small Modular Nuclear Reactors (SMRs), and Hydrogen. These technologies, while still in the early stages of development, show great promise in the evolving energy landscape. The research team used fuzzy TOPSIS and the Best-Worst Method (BWM) for validation, ensuring the robustness and reliability of their findings.
The implications of this research are far-reaching. By providing a structured and collaborative approach to technology evaluation, the study could shape future developments in the energy sector. “This hybrid soft computing method offers a modular design that allows for the sequential determination of criteria weights and the calculation of alternative rankings,” said Rivero-Iglesias. “This could be a game-changer in how energy sector professionals approach technology selection and project planning.”
The study’s innovative approach and comprehensive evaluation of power generation technologies make it a significant contribution to the field. As the energy sector continues to evolve, such research will be crucial in guiding decision-makers towards sustainable and efficient energy solutions. The study was published in the journal *Systems*, a testament to its rigorous methodology and valuable insights.