Overview of Natural Gas Boiler Optimization Technologies and Potential Applications on Gas Load Balancing Services
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- Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
- Yue Xin & Ke Wang & Yindi Zhang & Fanjin Zeng & Xiang He & Shadrack Adjei Takyi & Paitoon Tontiwachwuthikul, 2021. "Numerical Simulation of Combustion of Natural Gas Mixed with Hydrogen in Gas Boilers," Energies, MDPI, vol. 14(21), pages 1-15, October.
- Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Chatzis, Georgios V. & Biskas, Pandelis N. & Keranidis, Stratos D., 2021. "Minimization of natural gas consumption of domestic boilers with convolutional, long-short term memory neural networks and genetic algorithm," Applied Energy, Elsevier, vol. 299(C).
- Smarra, Francesco & Jain, Achin & de Rubeis, Tullio & Ambrosini, Dario & D’Innocenzo, Alessandro & Mangharam, Rahul, 2018. "Data-driven model predictive control using random forests for building energy optimization and climate control," Applied Energy, Elsevier, vol. 226(C), pages 1252-1272.
- Liu, Peiyun & Ding, Tao & Zou, Zhixiang & Yang, Yongheng, 2019. "Integrated demand response for a load serving entity in multi-energy market considering network constraints," Applied Energy, Elsevier, vol. 250(C), pages 512-529.
- Liu, Fengguo & Zheng, Longfeng & Zhang, Rui, 2020. "Emissions and thermal efficiency for premixed burners in a condensing gas boiler," Energy, Elsevier, vol. 202(C).
- Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Biskas, Pandelis N. & Keranidis, Stratos D. & Symeonidis, Polychronis A. & Voulgarakis, Dimitrios K., 2022. "A novel system for providing explicit demand response from domestic natural gas boilers," Applied Energy, Elsevier, vol. 317(C).
- Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
- Szoplik, Jolanta, 2015. "Forecasting of natural gas consumption with artificial neural networks," Energy, Elsevier, vol. 85(C), pages 208-220.
- Brkić, Dejan & Tanasković, Toma I., 2008. "Systematic approach to natural gas usage for domestic heating in urban areas," Energy, Elsevier, vol. 33(12), pages 1738-1753.
- Lina Montuori & Manuel Alcázar-Ortega, 2021. "District Heating as Demand Response Aggregator: Estimation of the Flexible Potential in the Italian Peninsula," Energies, MDPI, vol. 14(21), pages 1-19, October.
- Andrew Speake & Paul Donohoo-Vallett & Eric Wilson & Emily Chen & Craig Christensen, 2020. "Residential Natural Gas Demand Response Potential during Extreme Cold Events in Electricity-Gas Coupled Energy Systems," Energies, MDPI, vol. 13(19), pages 1-19, October.
- Konstantinos Papageorgiou & Elpiniki I. Papageorgiou & Katarzyna Poczeta & Dionysis Bochtis & George Stamoulis, 2020. "Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 13(9), pages 1-32, May.
- Sheikhi, Aras & Bahrami, Shahab & Ranjbar, Ali Mohammad, 2015. "An autonomous demand response program for electricity and natural gas networks in smart energy hubs," Energy, Elsevier, vol. 89(C), pages 490-499.
- Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
- Cauchi, Nathalie & Macek, Karel & Abate, Alessandro, 2017. "Model-based predictive maintenance in building automation systems with user discomfort," Energy, Elsevier, vol. 138(C), pages 306-315.
- Montuori, Lina & Alcázar-Ortega, Manuel, 2021. "Demand response strategies for the balancing of natural gas systems: Application to a local network located in The Marches (Italy)," Energy, Elsevier, vol. 225(C).
- Aste, Niccolò & Adhikari, R.S. & Compostella, Junia & Pero, Claudio Del, 2013. "Energy and environmental impact of domestic heating in Italy: Evaluation of national NOx emissions," Energy Policy, Elsevier, vol. 53(C), pages 353-360.
- Mustafa Akpinar & M. Fatih Adak & Nejat Yumusak, 2017. "Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey," Energies, MDPI, vol. 10(6), pages 1-20, June.
- Harriet Thomson & Carolyn Snell & Stefan Bouzarovski, 2017. "Health, Well-Being and Energy Poverty in Europe: A Comparative Study of 32 European Countries," IJERPH, MDPI, vol. 14(6), pages 1-20, May.
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- Marcin Trojan & Piotr Dzierwa & Jan Taler & Mariusz Granda & Karol Kaczmarski & Dawid Taler & Tomasz Sobota, 2023. "Analysis of the Causes of the Emergency Shutdown of Natural Gas-Fired Water Peak Boilers at the Large Municipal Combined Heat and Power Plant," Energies, MDPI, vol. 16(17), pages 1-21, August.
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Keywords
domestic gas boiler; energy efficiency; consumption minimization; demand response; gas balancing; integrated demand response;All these keywords.
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