The evaluation of Smart Grid (SG) efficiency requires a value-based perspective that incorporates decision-maker preferences alongside technical metrics. This study develops an integrated framework combining Data Envelopment Analysis (DEA) with the Flexible and Interactive Tradeoff (FITradeoff) method to assess SG efficiency. The approach begins with standardized DEA to identify an initial set of efficient DMUs, followed by an iterative preference elicitation process in which decision-makers provide pairwise comparisons of weight ratios. These preferences are translated into linear constraints that progressively contract the weight space through a robust optimization procedure with baseline weight restrictions. The algorithm systematically reduces the efficient set, terminating when a unique DMU is identified or the candidate set becomes sufficiently narrow. This framework offers a structured, transparent, and mathematically rigorous tool for identifying SG alternatives that align with strategic priorities and support preference-driven decision making.
A VALUE-BASED DECISION FRAMEWORK FOR EVALUATING THE INTEGRATED EFFICIENCY OF SMART GRIDS / Zhao, Qian; Balugani, Elia; Gamberini, Rita; Lolli, Francesco. - In: ANNALS OF DAAAM FOR ... & PROCEEDINGS OF THE ... INTERNATIONAL DAAAM SYMPOSIUM .... - ISSN 1726-9679. - 36(2025), pp. 131-140. ( 36th International DAAAM Symposium on Intelligent Manufacturing and Automation, DAAAM 2025 Vienna, Austria, online 30/10/2025 - 31/10/2025) [10.2507/36th.daaam.proceedings.017].
A VALUE-BASED DECISION FRAMEWORK FOR EVALUATING THE INTEGRATED EFFICIENCY OF SMART GRIDS
Qian Zhao;Elia Balugani
;Rita Gamberini;Francesco Lolli
2025
Abstract
The evaluation of Smart Grid (SG) efficiency requires a value-based perspective that incorporates decision-maker preferences alongside technical metrics. This study develops an integrated framework combining Data Envelopment Analysis (DEA) with the Flexible and Interactive Tradeoff (FITradeoff) method to assess SG efficiency. The approach begins with standardized DEA to identify an initial set of efficient DMUs, followed by an iterative preference elicitation process in which decision-makers provide pairwise comparisons of weight ratios. These preferences are translated into linear constraints that progressively contract the weight space through a robust optimization procedure with baseline weight restrictions. The algorithm systematically reduces the efficient set, terminating when a unique DMU is identified or the candidate set becomes sufficiently narrow. This framework offers a structured, transparent, and mathematically rigorous tool for identifying SG alternatives that align with strategic priorities and support preference-driven decision making.| File | Dimensione | Formato | |
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