ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2018
    Description: 〈p〉Publication date: 25 February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Thermal Engineering, Volume 149〈/p〉 〈p〉Author(s): Afshin Najafi-Ghalelou, Sayyad Nojavan, Kazem Zare, Behnam Mohammadi-Ivatloo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Multi-carrier hub energy system (MCHES) satisfies different energy demands such as heating, cooling, and energy demand by using different energy sources simultaneously. In this paper, a robust optimization approach (ROA) is provided for robust scheduling of MCHES considering economic and environmental constraints in the presence of market price uncertainty and multi-demand response programs (DRPs). In ROA, lower and upper levels of market price are considered instead of forecasted market price which guarantees the robust scheduling of the MCHES. The time-of-use (TOU) and real-time-pricing (RTP) rates of DRPs play a vital role in flattening the load curve with the aim of reducing the total operation cost and CO〈sub〉2〈/sub〉 emission. The proposed model is formulated as robust mixed integer linear programming (RMILP) and solved by General Algebraic Modeling System (GAMS) platform which has a great advantage in solving the linear programming models. Finally, to assess the effects of assumed DRPs on robust scheduling of MCHES, three case studies are utilized, and significant results were obtained.〈/p〉〈/div〉 〈/div〉
    Print ISSN: 1359-4311
    Electronic ISSN: 1873-5606
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Elsevier
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...