Akbari, SaeedHashemi-Dezaki, HamedMartins, João2025-02-062025-02-062024-122352-4847PURE: 107499703PURE UUID: 9fc20de6-189f-4c7f-8afd-c287aa794839Scopus: 85200220259WOS: 001286731400001http://hdl.handle.net/10362/178558Publisher Copyright: © 2024 The AuthorsEnergy hubs (EHs) aim to increase the flexibility of energy systems by adopting different energy carriers and sources. This paper presents a cooperative stochastic framework for managing networked EHs (NEHs) from an economic-environmental perspective. Scenario preparation techniques, such as Monte Carlo simulation (MCS) and the k-means clustering algorithm, are used to develop scenarios for different sources of uncertainty. Furthermore, the Shapley value is used to allocate coalition gains among NEHs based on their contributions and performance. To distinguish the proposed model from existing literature, several case studies have been conducted to assess its effectiveness. Conducted simulations show that through cooperation, the total cost of EHs and CO2 emissions is reduced by approximately 3 % and 1.8 %, respectively. Moreover, the performed sensitivity analyses indicate the robustness and reliability of the model against input parameters.1713929317engCooperative energy management frameworkEconomic-environmental concernsK-means clustering algorithmNetworked energy hubsShapley valueGeneral EnergySDG 13 - Climate Actionjournal article10.1016/j.egyr.2024.07.015https://www.scopus.com/pages/publications/85200220259