A successive linearization based optimal power-gas flow method

•A linearized OPGF model considering power loss, gas loss, reactive power, and voltage is constructed.•A successive mixed-integer QP method is developed to ensure the solution accuracy.•The proposed OPGF method can offer a high-accuracy and computationally efficient solution. Optimal power-gas flow...

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Veröffentlicht in:International journal of electrical power & energy systems Jg. 149; S. 109011
Hauptverfasser: Dai, Wei, Luo, Ceheng, Xu, Zheng, Zhao, Yaxue, Goh, HuiHwang, Liu, Zining
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.07.2023
Schlagworte:
Mixed-integer quadratic programming
Nonconvexity
Optimal power-gas flow
Successive linearization
Nonconvexity
Optimal power-gas flow
Successive linearization
Mixed-integer quadratic programming
ISSN:0142-0615, 1879-3517
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Zusammenfassung:•A linearized OPGF model considering power loss, gas loss, reactive power, and voltage is constructed.•A successive mixed-integer QP method is developed to ensure the solution accuracy.•The proposed OPGF method can offer a high-accuracy and computationally efficient solution. Optimal power-gas flow (OPGF) problem is a fundamental coordinated operation problem. However, the nonlinear AC power flow model and nonconvex gas flow model pose a huge challenge to OPGF calculation. The common treatments in the existing literature adopt simplified modeling of power and gas systems to obtain a relatively tractable model, which may produce an inaccurate and insecure solution (e.g., violation of voltage limits). Therefore, this paper considers the nonlinear AC power flow modeling and nonconvex gas flow modeling in the OPGF problem. To address the nonconvexities arising from the nonlinear AC power flow model, nonconvex Weymouth equations, and compressors’ gas consumption equations, the concept of successive linearization is introduced and then a successive mixed-integer quadratic programming (SMIQP) method is developed to solve the nonconvex OPGF problem. Numerical results demonstrate the effectiveness of the proposed SMIQP-based OPGF method in terms of high accuracy and high computational efficiency.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2023.109011