EconPapers    
Economics at your fingertips  
 

A robust bi-level optimization framework for participation of multi-energy service providers in integrated power and natural gas markets

Nima Nasiri, Amin Mansour Saatloo, Mohammad Amin Mirzaei, Sajad Najafi Ravadanegh, Kazem Zare, Behnam Mohammadi-ivatloo and Mousa Marzband

Applied Energy, 2023, vol. 340, issue C, No S0306261923004117

Abstract: This paper presents a bi-level scheduling model for a new energy system under the concept of multi-energy service providers (MESPs) to participate in the integrated power and natural gas market (IPNGM). While the presented bi-level model takes full consideration of the unit commitment constraints of the power network and line pack constraints of the gas network into consideration at the lower level, the MESPs minimize the cost of purchasing power and natural gas by operating energy storage systems as well as the demand response program (DRP) as flexible technologies at the upper level. In order to solve the bi-level problem, an iterative-based two-step algorithm is developed. Moreover, since the MESPs cannot accurately predict other participants in the IPNGM, especially renewable energy sources (RESs), the power price determined by IPNGM is considered an uncertain parameter, and a robust optimization (RO) method is employed to capture this uncertainty. The proposal is formulated as a mixed-integer linear programming (MILP) and carried out on the IEEE 6-bus power system integrated with the 6-node natural gas network and considering one MES using the CPLEX solver in the general algebraic modeling system (GAMS) environment. Further, to show the model flexibility, simulation results are extended to the IEEE 118-bus power system integrated with the 10-node natural gas network by considering six MESs. The obtained results verified the effectiveness of the model by reducing the cost of the purchased power and natural gas up to 4.39% by employing flexible energy sources.

Keywords: Market-clearing; Multi-energy systems; Integrated electricity and natural gas networks; Energy storage systems; Demand response program; Line pack system; Robust optimization (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261923004117
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:340:y:2023:i:c:s0306261923004117

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2023.121047

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:340:y:2023:i:c:s0306261923004117