{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T11:57:11Z","timestamp":1767182231129,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T00:00:00Z","timestamp":1761782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072363"],"award-info":[{"award-number":["62072363"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Natural gas plays a key role in the low-carbon energy transition due to its clean and efficient characteristics, yet challenges remain in balancing economic efficiency, user behavior, and carbon emission constraints in demand-side scheduling. This study proposes a low-carbon economic operation model for terminal natural gas systems, integrating price elasticity and differentiated user behavior with carbon emission management strategies. To capture diverse demand patterns, dynamic time warping k-medoids clustering is employed, while scheduling optimization is achieved through a multi-objective framework combining NSGA-III, the entropy weight (EW) method, and the VIKOR decision-making approach. Using real-world data from a gas station in Xi\u2019an, simulation results show that the model reduces gas supply costs by 3.45% for residential users and 6.82% for non-residential users, increases user welfare by 4.64% and 88.87%, and decreases carbon emissions by 115.18 kg and 2156.8 kg, respectively. Moreover, non-residential users achieve an additional reduction in carbon trading costs of 183.85 CNY. The findings demonstrate the effectiveness of integrating dynamic price signals, user behavior modeling, and carbon constraints into a unified optimization framework, offering decision support for sustainable and flexible natural gas scheduling.<\/jats:p>","DOI":"10.3390\/e27111120","type":"journal-article","created":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T01:23:59Z","timestamp":1761873839000},"page":"1120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Low-Carbon Economic Operation of Natural Gas Demand Side Integrating Dynamic Pricing Signals and User Behavior Modeling"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7903-4928","authenticated-orcid":false,"given":"Ning","family":"Tian","sequence":"first","affiliation":[{"name":"School of Management, Xi\u2019an University of Architecture and Technology, Xi\u2019an 710055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bilin","family":"Shao","sequence":"additional","affiliation":[{"name":"School of Management, Xi\u2019an University of Architecture and Technology, Xi\u2019an 710055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5499-9217","authenticated-orcid":false,"given":"Huibin","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Chongqing Normal University, Chongqing 401333, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xue","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Management, Xi\u2019an University of Architecture and Technology, Xi\u2019an 710055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9300-5495","authenticated-orcid":false,"given":"Wei","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Management, Xi\u2019an University of Architecture and Technology, Xi\u2019an 710055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"140393","DOI":"10.1016\/j.jclepro.2023.140393","article-title":"Optimal scheduling of zero-carbon integrated energy system considering long-and short-term energy storages, demand response, and uncertainty","volume":"435","author":"Song","year":"2024","journal-title":"J. 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