Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection
With increasing penetration of renewable energy, it is important to source adequate system flexibility to maintain security of supply and minimize renewable generation curtailment. Power to hydrogen (P2H) plays an important role in the low-carbon renewable dominated energy systems. By blending green...
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Frontiers Media S.A.
2022-04-01
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Series: | Frontiers in Energy Research |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2022.845637/full |
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author | Jinpeng Wang Jinpeng Wang Pingliang Zeng Yalou Li Jia Liu |
author_facet | Jinpeng Wang Jinpeng Wang Pingliang Zeng Yalou Li Jia Liu |
author_sort | Jinpeng Wang |
collection | DOAJ |
description | With increasing penetration of renewable energy, it is important to source adequate system flexibility to maintain security of supply and minimize renewable generation curtailment. Power to hydrogen (P2H) plays an important role in the low-carbon renewable dominated energy systems. By blending green hydrogen produced from renewable power into the natural gas pipelines, it is possible to help integrate large-scale intermittent generation and smooth the variability of renewable power output through the interconnection of the natural gas network, hydrogen energy network, and electric network. A two-stage stochastic mixed-integer nonlinear planning framework for P2H sizing and siting is proposed in this paper, considering system flexibility requirements. The problem is then reduced to a mixed-integer second-order cone (MISOC) model through convex transformation techniques in order to reduce the computation burden. Then, a distributed algorithm based on Bender’s decomposition is applied to obtain the optimal solution. A modified hybrid IEEE 33-node and Gas 20-node system is then used for simulation tests. The results showed that investment of P2H can significantly reduce the total capital and operational costs with lower renewable generation curtailment and electricity demand shedding. Numerical tests demonstrated to demonstrate the validity of the proposed MISOC model. |
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issn | 2296-598X |
language | English |
last_indexed | 2024-04-12T22:40:53Z |
publishDate | 2022-04-01 |
publisher | Frontiers Media S.A. |
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spelling | doaj.art-dc8da119fd1a477aa2156ec94211ccb62022-12-22T03:13:43ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2022-04-011010.3389/fenrg.2022.845637845637Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen InjectionJinpeng Wang0Jinpeng Wang1Pingliang Zeng2Yalou Li3Jia Liu4Department of Automation, Hangzhou Dianzi University, Hangzhou, ChinaSchool of Electrical and Control Engineering, Henan University of Urban Construction, Pingdingshan, ChinaDepartment of Automation, Hangzhou Dianzi University, Hangzhou, ChinaElectric Power Research Institute, Beijing, ChinaDepartment of Automation, Hangzhou Dianzi University, Hangzhou, ChinaWith increasing penetration of renewable energy, it is important to source adequate system flexibility to maintain security of supply and minimize renewable generation curtailment. Power to hydrogen (P2H) plays an important role in the low-carbon renewable dominated energy systems. By blending green hydrogen produced from renewable power into the natural gas pipelines, it is possible to help integrate large-scale intermittent generation and smooth the variability of renewable power output through the interconnection of the natural gas network, hydrogen energy network, and electric network. A two-stage stochastic mixed-integer nonlinear planning framework for P2H sizing and siting is proposed in this paper, considering system flexibility requirements. The problem is then reduced to a mixed-integer second-order cone (MISOC) model through convex transformation techniques in order to reduce the computation burden. Then, a distributed algorithm based on Bender’s decomposition is applied to obtain the optimal solution. A modified hybrid IEEE 33-node and Gas 20-node system is then used for simulation tests. The results showed that investment of P2H can significantly reduce the total capital and operational costs with lower renewable generation curtailment and electricity demand shedding. Numerical tests demonstrated to demonstrate the validity of the proposed MISOC model.https://www.frontiersin.org/articles/10.3389/fenrg.2022.845637/fullpower to hydrogen (P2H)hydrogen injectionssystem flexibilitylow carbonbenders decomposition |
spellingShingle | Jinpeng Wang Jinpeng Wang Pingliang Zeng Yalou Li Jia Liu Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection Frontiers in Energy Research power to hydrogen (P2H) hydrogen injections system flexibility low carbon benders decomposition |
title | Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection |
title_full | Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection |
title_fullStr | Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection |
title_full_unstemmed | Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection |
title_short | Optimal Capacity Planning of Power to Hydrogen in Integrated Electricity–Hydrogen–Gas Energy Systems Considering Flexibility and Hydrogen Injection |
title_sort | optimal capacity planning of power to hydrogen in integrated electricity hydrogen gas energy systems considering flexibility and hydrogen injection |
topic | power to hydrogen (P2H) hydrogen injections system flexibility low carbon benders decomposition |
url | https://www.frontiersin.org/articles/10.3389/fenrg.2022.845637/full |
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