Optimal scheduling of hybrid power and natural gas systems considering N-1 contingencies and gas thermodynamics

With the advancement of gas power generation technology, the coupling relationship of the electricity and gas system is gradually increasing. Gas thermodynamics is an important mechanism in the process of gas transport, which has not been fully studied in the scheduling of hybrid power and gas syste...

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Bibliographic Details
Main Authors: Dawei Chen, Jinyu Chen, Weijun Zhang, Zhicheng Li, Chaoping Deng, Zhaojing Cao, Hongxu Zheng
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484723004511
Description
Summary:With the advancement of gas power generation technology, the coupling relationship of the electricity and gas system is gradually increasing. Gas thermodynamics is an important mechanism in the process of gas transport, which has not been fully studied in the scheduling of hybrid power and gas systems (HPGS). Moreover, considering the N-1 contingency in HPGS operation can make systems robust to defend the single transmission line and pipe contingency. This paper establishes a novel optimal scheduling of HPGS considering N-1 contingencies and gas thermodynamics to promote the system reliability as well as model accuracy. The partial differential equation (PDE) depicting the heat power loss is established to model the temperature change, which effectively avoids the mathematical complexity of traditional pipeline thermal model. The finite difference scheme is utilized to discretize the PDE, thereby establishing an algebraic pipe model considering gas thermodynamics. The big-M approach is applied to integrate the N-1 criterion of both power and gas systems into the model of HPGS. Finally, the optimal scheduling of HPGS considering N-1 contingencies and gas thermodynamics can be obtained by coupling the power and gas network model. Case study validates the superiority of the proposed optimal scheduling model of HPGS with respect to model accuracy and system reliability.
ISSN:2352-4847