A Portfolio Selection Model for Planning Natural Gas Smart Energy Hubs with a Multicriteria Benefit-to-Cost Ratio-Based Approach

• This paper proposes a portfolio selection model called ROCSPort for planning natural gas smart energy hubs. • The ROCSPort model is based on a benefit-to-cost ratio approach with surrogate weights and swing elicitation. • The multicriteria model can be replicated in other decision problems to enhance portfolio selection. • A realistic application for selecting energy hubs with ROCSPort produced greater assertiveness. In the context of advancing energy infrastructure, the planning and development of natural gas smart energy hubs have gained importance as essential components of sustainable energy systems. Thus, this paper introduces a portfolio selection model designed to improve the planning process for natural gas smart energy hubs. The proposed model integrates a multicriteria benefit-to-cost ratio-based (BCR) heuristic approach with surrogate weights and swing elicitation procedure, providing a robust framework for decision-makers to assess and prioritize investment options. The methodology encompasses a diverse set of criteria, including economic, environmental, and social factors, ensuring a holistic evaluation of candidate projects. A Decision Support System (DSS) called ROCSPort was proposed to operationalize and validate the proposed methodology, with a view to providing a streamlined preference modeling process for the decision-maker. The DSS also performs a sensitivity analysis based on a Monte-Carlo simulation approach, and statistical tests can be performed to verify the stability of the results. The model’s applicability is demonstrated through a numerical application in a Brazilian energy company, illustrating its capacity to improve the selection of projects based on predefined objectives and constraints. The findings contribute to the energy planning context by offering a systematic and adaptable approach and tool for portfolio selection, aiding decision-makers involved in determining a sustainable energy infrastructure.