A cyber‐secure model to decentralized co‐expansion planning of gas and electricity networks

Summary Flexibilities offered by gas‐fired power plants have strongly increased their usage in power systems. Increasing the penetration rate of gas‐fired power plants has made it necessary to coordinate gas network expansion planning with electricity network expansion planning. In this paper, a dec...

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Bibliographic Details
Published in:International journal of energy research Vol. 45; no. 9; pp. 13414 - 13428
Main Authors: Ghezelbash, Azam, Khaligh, Vahid, Anvari‐Moghaddam, Amjad
Format: Journal Article
Language:English
Published: Chichester, UK John Wiley & Sons, Inc 01.07.2021
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ISSN:0363-907X, 1099-114X
Online Access:Get full text
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Summary:Summary Flexibilities offered by gas‐fired power plants have strongly increased their usage in power systems. Increasing the penetration rate of gas‐fired power plants has made it necessary to coordinate gas network expansion planning with electricity network expansion planning. In this paper, a decentralized model for expansion of gas and electricity networks is introduced that coordinates investment in these networks while taking into account their privacy. Alternating direction method of multipliers is used to decompose the centralized gas and electricity expansion problem into two separate expansion problems. The proposed method aims to minimize the investment and operation cost of interconnected gas and electricity networks during the planning period. The resultant problems are mixed‐integer nonlinear programs, which are then linearized and transformed into mixed‐integer linear programming models to facilitate the optimality conditions. Distributed optimization provides a cyber‐physical system in which gas and electricity networks are managed separately while a coordination link is provided through the cloud computing layer. However, coordinated operation through a cloud layer keeps the control‐loop subject to cyber‐attacks. In this paper, the standard form of the proposed decentralized model is modified to secure it against cyber‐attacks. Finally, the effectiveness and applicability of the proposed method are tested and verified over a real case study that has a high penetration level of gas consuming generation units. The proposed cyber secure model not only converges faster than a standard model (ie, computationally more efficient than conventional methods) but also keeps optimality of found solution in a secure fashion. The satisfactory performance of the proposed model is also demonstrated against centralized, leader‐follower, and independent expansion planning models.
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ISSN:0363-907X
1099-114X
DOI:10.1002/er.6670