ArticlePloS one2025
Capacity optimization configuration and multi-dimensional value evaluation of integrated energy system with power-to-hydrogen.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Development of an entropy-weighted evaluation system for optometric education quality in vocational colleges of Yunnan Province.BMC medical education · 2026Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The research on the value evaluation system of power-to-hydrogen (P2H) equipment configuration in integrated energy systems is of great value for optimizing resource allocation, improving energy utilization efficiency, and promoting clean energy technology development. However, there is no comprehensive evaluation system for evaluating P2H equipment configuration in integrated energy systems. Therefore, a multi-dimensional value evaluation system is proposed to realize the thorough evaluation of P2H equipment with different capacity configurations in the integrated energy system. Initially, a mathematical model considering flexibility benefit, new energy consumption benefit, economic benefit, and environmental benefit is established to maximize the comprehensive benefits brought by P2H equipment to the integrated energy system, and the model is solved using an improved backbone particle swarm optimization (IBBPSO) algorithm; subsequently, a multi-dimensional value evaluation system based on the analytic hierarchy process (AHP) -entropy weight method is constructed, and the value of P2H equipment with different capacity configurations in the integrated energy system is compared and analyzed when the comprehensive benefit is optimal. The experimental results show that the IBBPSO algorithm exhibits better performance in solving the optimization model. Compared to PSO, IBBPSO, GWO, and WOA algorithms, it improves by 9.8%, 11.09%, 33.57%, and 17.7%, respectively. The optimal solution is achieved when the P2H equipment is configured to 50 MW.
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