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Optimizing power-to-H2 participation in the Nord Pool electricity market: effects of different bidding strategies on plant operation

Janke, Leandro and McDonagh, Shane and Weinrich, Sören and Murphy, Jerry and Nilsson, Daniel and Nordberg, Åke (2020). Optimizing power-to-H2 participation in the Nord Pool electricity market: effects of different bidding strategies on plant operation. Renewable Energy. 156 , 820-836
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Abstract

The operation of power-to-X systems requires measures to control the cost and sustainability of electricity purchased from spot markets. This study investigated different bidding strategies for the dayahead market with a special focus on Sweden. A price independent order (PIO) strategy was developed assisted by forecasting electricity prices with an artificial neural network. For comparison, a price dependent order (PDO) with fixed bid price was used. The bidding strategies were used to simulate H2 production with both alkaline and proton exchange membrane electrolysers in different years and technological scenarios. Results showed that using PIO to control H2 production helped to avoid the purchase of expensive and carbon intense electricity during peak loads, but it also reduced the total number of operating hours compared to PDO. For this reason, under optimal conditions for both bidding strategies, PDO resulted in an average of 10.9% lower levelised cost of H2, and more attractive cash flows and net present values than PIO. Nevertheless, PIO showed to be a useful strategy to control costs in years with unexpected hourly price behaviour such as 2018. Furthermore, PIO could be successfully demonstrated in a practical case study to fulfil the on-demand requirement of an industrial captive customer.

Authors/Creators:Janke, Leandro and McDonagh, Shane and Weinrich, Sören and Murphy, Jerry and Nilsson, Daniel and Nordberg, Åke
Title:Optimizing power-to-H2 participation in the Nord Pool electricity market: effects of different bidding strategies on plant operation
Year of publishing :2020
Volume:156
Page range:820-836
Number of Pages:17
Publisher:Elsevier
ISSN:0960-1481
Language:English
Publication Type:Journal article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 203 Mechanical Engineering > Energy Engineering
(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Energy Systems
Keywords:Variable renewable electricity, Electrolysis Neural networks, Hydrogen production, Bidding strategy, Economic indicators
URN:NBN:urn:nbn:se:slu:epsilon-p-105953
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-105953
Additional ID:
Type of IDID
DOI10.1016/j.renene.2020.04.080
ID Code:17152
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Energy and Technology
Deposited By: SLUpub Connector
Deposited On:26 Jun 2020 13:21
Metadata Last Modified:26 Jun 2020 13:21

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