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Espinoza-Vasquez AP, Galatro D, Manzano P, Choez-Guaranda I, Cevallos JM, Salas SD, Gonzalez Y. Tray dryer design under feed uncertainty: A case study on a nutraceutical beverage. J FOOD ENG 2022. [DOI: 10.1016/j.jfoodeng.2022.111341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Li Y, Rao Z, Liu Z, Zeng J, Bao W, Wang Z, Li J, Yu F, Dai B, Zhou Y. Photo‐assisted CO/CO2 methanation over Ni/TiO2 catalyst: experiment and density functional theory calculation. ChemCatChem 2022. [DOI: 10.1002/cctc.202200182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Yangyang Li
- Shihezi University School of Chemistry and Chemical Engineering CHINA
| | - Zhiqiang Rao
- Southwest Petroleum University School of Chemistry and Chemical Engineering CHINA
| | - Zhisong Liu
- Shihezi University School of Chemistry and Chemical Engineering CHINA
| | - Junming Zeng
- Shihezi University School of Chemistry and Chemical Engineering CHINA
| | - Wentao Bao
- Shihezi University chool of Chemistry and Chemical Engineering CHINA
| | - Zijun Wang
- Shihezi University School of Chemistry and Chemical Engineering CHINA
| | - Jiangbing Li
- Shihezi University School of Chemistry and Chemical Engineering CHINA
| | - Feng Yu
- Shihezi University School of Chemistry and Chemical Engineering No 4 Road 832000 Shihezi CHINA
| | - Bin Dai
- Shihezi University School of Chemistry and Chemical Engineering CHINA
| | - Ying Zhou
- Shihezi University School of Chemistry and Chemical Engineering CHINA
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Baratsas SG, Niziolek AM, Onel O, Matthews LR, Floudas CA, Hallermann DR, Sorescu SM, Pistikopoulos EN. A framework to predict the price of energy for the end-users with applications to monetary and energy policies. Nat Commun 2021; 12:18. [PMID: 33398000 PMCID: PMC7782726 DOI: 10.1038/s41467-020-20203-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 11/09/2020] [Indexed: 11/21/2022] Open
Abstract
Energy affects every single individual and entity in the world. Therefore, it is crucial to precisely quantify the “price of energy” and study how it evolves through time, through major political and social events, and through changes in energy and monetary policies. Here, we develop a predictive framework, an index to calculate the average price of energy in the United States. The complex energy landscape is thoroughly analysed to accurately determine the two key factors of this framework: the total demand of the energy products directed to the end-use sectors, and the corresponding price of each product. A rolling horizon predictive methodology is introduced to estimate future energy demands, with excellent predictive capability, shown over a period of 174 months. The effectiveness of the framework is demonstrated by addressing two policy questions of significant public interest. Global energy transformation requires quantifying the "price of energy" and studying its evolution. Here the authors present a predictive framework that calculates the average US price of energy, estimating future energy demands for up to four years with excellent accuracy, designing and optimizing energy and monetary policies.
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Affiliation(s)
- Stefanos G Baratsas
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA.,Texas A&M Energy Institute, Texas A&M University, College Station, TX, 77843, USA
| | - Alexander M Niziolek
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA.,Texas A&M Energy Institute, Texas A&M University, College Station, TX, 77843, USA
| | - Onur Onel
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA.,Texas A&M Energy Institute, Texas A&M University, College Station, TX, 77843, USA
| | - Logan R Matthews
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA.,Texas A&M Energy Institute, Texas A&M University, College Station, TX, 77843, USA
| | - Christodoulos A Floudas
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA.,Texas A&M Energy Institute, Texas A&M University, College Station, TX, 77843, USA
| | - Detlef R Hallermann
- Department of Finance, Mays Business School, Texas A&M University, College Station, TX, 77843, USA
| | - Sorin M Sorescu
- Department of Finance, Mays Business School, Texas A&M University, College Station, TX, 77843, USA
| | - Efstratios N Pistikopoulos
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, 77843, USA. .,Texas A&M Energy Institute, Texas A&M University, College Station, TX, 77843, USA.
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Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources. MATHEMATICS 2020. [DOI: 10.3390/math8071100] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This paper presents a multi-objective economic-environmental dispatch (MOEED) model for integrated thermal, natural gas, and renewable energy systems considering both pollutant emission levels and total fuel or generation cost aspects. Two cases are carried out with the IEEE 30-bus system by replacing thermal generation units into natural gas units to minimize the amount of toxin emission and fuel cost. Equality, inequality like active, reactive powers, prohibited operating zones (POZs) which represents poor operation in the generation cost function, and security constraints are considered as system constraints. Natural gas units (NGUs) are modeled in detail. Therefore, the flow velocity of gas and pressure pipelines are also considered as system constraints. Multi-objective optimization algorithms, namely multi-objective Harris hawks optimization (MOHHO) and multi-objective flower pollination algorithm (MOFPA) are employed to find Pareto optimal solutions of fuel or generation cost and emission together. Furthermore, the technique for order preference by similarity to ideal solution (TOPSIS) is proposed to obtain the best value of Pareto optimal solutions. Three scenarios are investigated to validate the effectiveness of the proposed model applied to the IEEE 30-bus system with the integration of variable renewable energy sources (VRESs) and natural gas units. The results obtained from Scenario III with NGUs installed instead of two thermal units reveal that the economic dispatching approach presented in this work can greatly minimize emission levels as 0.421 t/h and achieve lower fuel cost as 796.35 $/h. Finally, the results obtained show that the MOHHO outperforms the MOFPA in solving the MOEED problem.
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