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2. Financial Directions for Renewable Energy Sources Investments as a Support for Sustainable Development Policy—Examples of Polish Cities. (2025). Dembicka-Niemiec, Agnieszka ; Szafranek-Stefaniuk, Edyta.
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3. Optimization Scheduling of Hydrogen-Integrated Energy Systems Considering Multi-Timescale Carbon Trading Mechanisms. (2025). Fan, Haocheng ; Song, Yangyang ; Zhao, Jingjing.
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4. Proposal of a Model for Improving the Management of the Wind Energy Industry in the Context of Sustainable Development Challenges. (2025). Biliska, Katarzyna ; Pabian, Barbara.
   In: Energies.
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5. A coordinated configuration scheme for hydrogen-electric energy storage based on transient response characteristics. (2025). Wang, Haiyang ; Fan, Hui ; He, Jiawei ; Li, Bin ; Wu, Zhangxi ; Hu, Xinhang ; Zhang, Shouhang.
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6. Autonomy as empowerment: A taxonomic framework for analyzing energy autonomy in local flexibility markets. (2025). Poudineh, Rahmatallah ; Eliassen, Frank ; Bagherpour, Matin ; Foroughi, Mehdi.
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7. Two-layer energy dispatching and collaborative optimization of regional integrated energy system considering stakeholders game and flexible load management. (2025). Li, Ji-Xiang ; Gu, Rui-Zheng ; Liu, Zhi-Feng ; Luo, Xing-Fu ; Zhao, Shi-Xiang ; Huang, Ya-He.
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8. Energy‐saving technologies and energy efficiency in the post‐COVID era. (2024). Strielkowski, Wadim ; Gorina, Larisa ; Kovaleva, Olga ; Korneeva, Elena.
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9. Design of Energy Management Strategy for Integrated Energy System Including Multi-Component Electric–Thermal–Hydrogen Energy Storage. (2024). Peng, BO ; Li, Yunguo ; Liu, Hengyang ; Zhao, Jianyong ; Bai, Yang ; Kang, Ping ; Nian, Heng.
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   RePEc:gam:jeners:v:17:y:2024:i:23:p:6184-:d:1539050.

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10. A preference adjustable capacity configuration optimization method for hydrogen-containing integrated energy system considering dynamic energy efficiency improvement and load fast tracking. (2024). Zhao, Huirong ; Yao, Yuqi ; Peng, Daogang.
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    RePEc:eee:renene:v:235:y:2024:i:c:s096014812401382x.

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11. Human-safe and economic operation of renewable hydrogen-based microgrids under plateau conditions. (2024). Yang, Yuyan ; Luo, Yichen ; Xu, Xiao ; Hu, Weihao ; Liu, Junyong.
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    RePEc:eee:renene:v:231:y:2024:i:c:s0960148124010103.

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12. A techno-economic framework for optimizing multi-area power dispatch in microgrids with tie-line constraints. (2024). Khalid, Muhammad.
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    RePEc:eee:renene:v:231:y:2024:i:c:s0960148124009224.

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13. Predicting calorific value and ash content of sand shrub using Vis-NIR spectra and various chemometrics. (2024). Lan, Xiaozhen ; Bai, Xiaoping ; Su, Xiaoming ; Wang, Jixuan ; Xu, Haokai ; Via, Brian K ; Pei, Zhiyong ; Li, Ying.
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14. Optimal planning and operation for a grid-connected solar–wind–hydro energy system in wastewater treatment plants. (2024). Ostergaard, Poul Alberg ; Xu, Jiuping ; Wang, Fengjuan ; Zhao, Chuandang ; Tan, Cheng.
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15. Distributionally robust planning method for expressway hydrogen refueling station powered by a wind-PV system. (2024). Yang, Yuyan ; Luo, Yichen ; Xu, Xiao ; Hu, Weihao ; Liu, Junyong.
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16. Optimizing energy efficiency and emission reduction: Leveraging the power of machine learning in an integrated compressed air energy storage-solid oxide fuel cell system. (2024). Khan, Mohammad Nadeem ; Ali, Elhosiny H ; Wang, Yongfeng ; Bu, Zainab Ali ; Ghandour, Raymond.
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2. Input-output model for forecasting economic and environmental effects of smart meters deployment in Poland. (2025). Brzoza-Zajcka, Ada ; Kisiel-Dorohinicki, Marek ; Adamiec, Ewa ; Zyk, Janusz ; Lach, Ukasz ; Kope, Sawomir ; Heller, Krzysztof ; Gaska, Krzysztof.
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4. Energy in Smart Cities: Technological Trends and Prospects. (2024). Lzroiu, George ; Rzepka, Agnieszka ; Budna, Klaudia ; Nica, Elvira ; Fernando, Xavier ; Szpilko, Danuta.
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5. Towards energy freedom: Exploring sustainable solutions for energy independence and self-sufficiency using integrated renewable energy-driven hydrogen system. (2024). Yusaf, T ; Laimon, M.
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10. Using an artificial neural network model for natural gas compositions forecasting. (2023). Muchel, Paulina ; Szoplik, Jolanta.
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15. Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks. (2021). Tiong, Sieh Kiong ; Amin, Nowshad ; Shakeri, Mohammad ; Hasan, Mohammad Kamrul ; Rahman, Md Mijanur ; Pasupuleti, Jagadeesh ; Khatun, Fatema.
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23. Online big data-driven oil consumption forecasting with Google trends. (2019). Yu, Lean ; Yang, Zebin ; Zhao, Yaqing ; Tang, Ling.
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24. Modeling electricity consumption using nighttime light images and artificial neural networks. (2019). Jasiński, Tomasz ; Jasiski, Tomasz.
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27. Automatic generation of models for energy demand estimation using Grammatical Evolution. (2018). Salcedo-Sanz, S ; Colmenar, J M ; Hidalgo, J I.
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28. Forecasting energy demand, wind generation and carbon dioxide emissions in Ireland using evolutionary neural networks. (2018). Mason, Karl ; Duggan, Jim ; Howley, Enda.
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29. Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey. (2017). Yumusak, Nejat ; Akpinar, Mustafa ; Adak, Fatih M.
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30. Forecasting of Chinese Primary Energy Consumption in 2021 with GRU Artificial Neural Network. (2017). Liu, Yan Quan ; Fu, Chuanchuan ; Bielefield, Arlene.
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31. Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network. (2017). Zeng, Yu-Rong ; Wang, Lin ; Choi, Beomjin.
    In: Energy.
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32. Forecasting of Turkey s Sectoral Energy Demand by Using Fuzzy Grey Regression Model. (2017). Gezen, Mesliha ; Karaaslan, Abdulkerim.
    In: International Journal of Energy Economics and Policy.
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33. Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey. (2016). Gunay, Merdem .
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34. Forecasting Fossil Fuel Energy Consumption for Power Generation Using QHSA-Based LSSVM Model. (2015). He, Yujun ; Sun, Wei ; Chang, Hong.
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35. A comparative study on prediction methods for Chinas medium- and long-term coal demand. (2015). Liang, Qiao-Mei ; Wang, Jin-Cheng.
    In: Energy.
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36. Forecasting of natural gas consumption with artificial neural networks. (2015). Szoplik, Jolanta.
    In: Energy.
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37. Can China achieve its carbon intensity target by 2020 while sustaining economic growth?. (2015). Wei, Yi-Ming ; Chevallier, Julien ; Wang, Ping ; Zhu, Bangzhu.
    In: Ecological Economics.
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38. Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting in China. (2015). Zhang, Qiang ; Shao, Zhen ; Yang, Shan-Lin ; Gao, Fei.
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39. Building Behavior Simulation by Means of Artificial Neural Network in Summer Conditions. (2014). Vergoni, Marco ; Lascaro, Elisa ; Palladino, Domenico ; Buratti, Cinzia.
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40. Review of energy models to the development of an efficient industrial energy model. (2014). Olanrewaju, O. A, ; Jimoh, A. A, .
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41. Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States. (2014). Reisel, John R. ; Kialashaki, Arash .
    In: Energy.
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42. Estimates of energy consumption in Turkey using neural networks with the teaching–learning-based optimization algorithm. (2014). Dede, Tayfun ; Kankal, Murat ; Uzlu, Ergun ; Akpnar, Adem .
    In: Energy.
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43. How much CO2 emissions will be reduced through industrial structure change if China focuses on domestic rather than international welfare?. (2014). Wang, Zheng ; Zhu, Yongbin ; Shi, Yajuan.
    In: Energy.
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44. An estimation model for determining the annual energy cost budget in educational facilities using SARIMA (seasonal autoregressive integrated moving average) and ANN (artificial neural network). (2014). Hong, Taehoon ; Jeong, Kwangbok ; Koo, Choongwan.
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45. Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey. (2014). Nacar, Sinan ; Kankal, Murat ; ozturk, Hasan Tahsin ; Uzlu, Ergun ; Akpnar, Adem .
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46. DEMAND, CUSTOMER BASE-LINE AND DEMAND RESPONSE IN THE ELECTRICITY MARKET: A SURVEY. (2014). Heshmati, Almas.
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47. Modeling of the energy demand of the residential sector in the United States using regression models and artificial neural networks. (2013). Reisel, John R. ; Kialashaki, Arash .
    In: Applied Energy.
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48. Survey of Models on Demand, Customer Base-Line and Demand Response and Their Relationships in the Power Market. (2012). Heshmati, Almas.
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49. Energy models for demand forecasting—A review. (2012). Suganthi, L. ; Samuel, Anand A..
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50. Research on the evolution model of an energy supply–demand network. (2012). Wang, Xiao-Fang ; Shan, Tian-Hua ; Zhang, Pei-Pei ; Sun, Mei ; Tian, Li-Xin ; Fang, Cui-Cui .
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51. A hybrid procedure for energy demand forecasting in China. (2012). Yu, Shi-Wei ; Zhu, Ke-Jun .
    In: Energy.
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52. A PSO–GA optimal model to estimate primary energy demand of China. (2012). YU, Shiwei ; Wei, Yi-Ming ; Wang, Ke.
    In: Energy Policy.
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53. Energy resources demand-supply system analysis and empirical research based on non-linear approach. (2011). Chen, Ying ; Wang, Xiaofang ; Sun, Mei ; Tian, Lixin.
    In: Energy.
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54. Transport energy demand modeling of South Korea using artificial neural network. (2011). Geem, Zong Woo.
    In: Energy Policy.
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55. Modeling and forecasting natural gas demand in Bangladesh. (2011). Wadud, Zia ; Khan, Shahidul I. ; Kabir, Md. Ashfanoor, ; Dey, Himadri S..
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56. Modeling and forecasting of Turkeys energy consumption using socio-economic and demographic variables. (2011). zsahin, Talat Sukru ; Kankal, Murat ; Komurcu, Murat Ihsan ; Akpinar, Adem.
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