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Optimal Scheduling of Gas and Electricity Distribution Networks in Microgrids : A Decomposition Approach

Shahbazbegian, Vahid; Ameli, Hossein; Shafie-khah, Miadreza; Laaksonen, Hannu; Ameli, Mohamad Taghi; Strbac, Goran (2022-08-19)

 
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Tiedosto avautuu julkiseksi:
: 19.08.2024
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https://doi.org/10.1109/EEEIC/ICPSEurope54979.2022.9854624

Shahbazbegian, Vahid
Ameli, Hossein
Shafie-khah, Miadreza
Laaksonen, Hannu
Ameli, Mohamad Taghi
Strbac, Goran
IEEE
19.08.2022
doi:10.1109/EEEIC/ICPSEurope54979.2022.9854624
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https://urn.fi/URN:NBN:fi-fe202301193902

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©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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The transition towards increasingly renewables-based energy system is ongoing. During this transition microgrids are seen as a key concept and sub-system which can enable the transition and improve the security of supply at distribution network level. From generation perspective, flexible and rapidly controllable gas-based generation units can be utilized to deal with the variable output of weather-dependent renewable energy resources. Due to these complementary characteristics, it is of interest to study the integrated operation of gas and electricity distribution networks also in future microgrids. In this paper, the optimized scheduling of resources in a microgrid with gas and electricity distribution networks is studied. For this purpose, a mathematical model is first determined. After that, due to the complexity of this model, a decomposition method is developed to solve the optimization problem. This method splits the original problem into two subproblems, which reduces the complexity of solving. In order to validate the efficacy of the proposed model, a case study is derived based on a 15-node gas distribution network and a 13-node electricity distribution network. Based on the results, integrated scheduling improves the costs compared to separated scheduling, and the decomposition method reduces the solving time considerably.
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