Distributionally Robust Hydrogen Optimization with Ensured Security and Multi-Energy Couplings

Pengfei Zhao, Chenghong Gu, Zechun Hu, Da Xie, Ignacio Hernando-Gil, Yichen Shen

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Abstract

Power-to-gas (P2G) can convert excessive renewable energy into hydrogen via electrolysis, which can then be transported by natural gas systems to bypass constrained electricity systems. However, the injection of hydrogen could impact gas security since gas composition fundamentally changes, adversely effecting the combustion, safety and lifespan of appliances. This paper develops a new gas security management scheme for hydrogen injection into natural gas systems produced from excessive wind power. It introduces four gas security indices for the integrated electricity and gas system (IEGS) measuring gas security, considering the coordinated operation of tightly coupled infrastructures. To maintain gas security under an acceptable range, the gas mixture of nitrogen and liquid petroleum gas with hydrogen is adopted to address the gas security violation caused by hydrogen injection. A distributionally robust optimization (DRO) modelled by Kullback-Leibler (KL) divergence-based ambiguity set is applied to flexibly control the robustness to capture wind uncertainty. The KL divergence-based ambiguity set defines uncertainties within a measured space which limits the shape of probability distributions. Case studies illustrate that wind power is maximally utilized and gas mixture is effectively managed, thus improving gas security and performance of IEGS. This work can bring many benefits: i) ensured gas security under hydrogen injection ii) low system operation cost and iii) high renewable energy penetration. It can be easily extended to manage injections of other green gases into IEGS.
Original languageEnglish
Article number9130030
Pages (from-to)504-513
JournalIEEE Transactions on Power Systems
Volume36
Issue number1
Early online date30 Jun 2020
DOIs
Publication statusPublished - 31 Jan 2021

Funding

Manuscript received April 4, 2020; revised May 12, 2020; accepted June 15, 2020. Date of publication June 30, 2020; date of current version January 6, 2021. This work was supported by British Council ‘The alliance Huber urine Programme 2020’ under Project 5157619151. Paper no. TPWRS-00542-2020. (Corresponding author: Chenghong Gu.) Pengfei Zhao, Chenghong Gu, and Yichen Shen are with the Department of Electronic & Electrical Engineering, University of Bath, Bath BA2 7AY, U.K. (e-mail: [email protected]; [email protected]; [email protected]). Zechun Hu is with the Department of Electrical Engineering, Tsinghua University, Beijing 100084, China (e-mail: [email protected]). Da Xie is with the Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China (e-mail: [email protected]). Ignacio Hernando-Gil is with the ESTIA Institute of Technology, Bidart F 64210, France (e-mail: [email protected]). Color versions of one or more of the figures in this article are available online at https://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TPWRS.2020.3005991

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