Accurate modeling of a profit-driven power to hydrogen and methane plant toward strategic bidding within multi-type markets

Pan, Guangsheng, Gu, Wei, Lu, Yuping, Qiu, Haifeng, Lu, Shuai and Yao, Shuai ORCID: https://orcid.org/0000-0002-7202-7961 2021. Accurate modeling of a profit-driven power to hydrogen and methane plant toward strategic bidding within multi-type markets. IEEE Transactions on Smart Grid 12 (1) , pp. 338-349. 10.1109/TSG.2020.3019043

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Abstract

A power to hydrogen and methane (P2HM) plant can couple three different energy sectors including electricity, natural gas, and hydrogen, showing great potentials in supporting the penetration of renewable energy sources. This article develops a bi-level strategic bidding model of a profit-driven P2HM plant from both market and technology perspectives. In the upper-level model, the P2HM plant submits day-ahead bids of energy prices and quantities to the power, natural gas, and hydrogen markets, respectively, with the objective to maximize its benefit; Moreover, the technical problems for operating this P2HM plant are also considered. In the lower-level model, multi-type markets are handled using different approaches based on market characteristics, to achieve an appropriate framework for multi-type markets. Specifically, the power and natural gas markets are characterized by the widely used optimal power and gas flows (OPGF) with network constraints, and the quantity-based competition Cournot model is employed to represent the emerging hydrogen market. In model solving, the bi-level optimization model is reformulated into a mathematical program with equilibrium constraints (MPEC) model. Subsequently, the strong-duality theory is applied to linearize the nonlinear terms of the model. Two case studies are performed to show the effectiveness of this model.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	1949-3053
Date of Acceptance:	20 August 2020
Last Modified:	14 Sep 2023 11:00
URI:	https://orca.cardiff.ac.uk/id/eprint/161944

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