Abstract
In deregulated electricity markets, large industrial consumers face significant challenges in participating effectively due to complexities in market regulations and diverse flexibility requirements. This paper introduces “Process2Market,” a web-based evaluation tool designed to assist large electricity consumers in the Nordics by leveraging the Process-to-Market Matrix Mapping (P2MM) model. The tool employs a Python-based optimization program integrated with a comprehensive questionnaire and market data analysis to evaluate market participation feasibility. By providing an accessible online interface, Process2Market facilitates broader engagement and understanding among stakeholders, including researchers and electricity consumers. A case study involving a hypothetical Power-to-Hydrogen (PtH) facility demonstrates the tool’s practical application, highlighting its potential to enhance grid stability through increased demand-side flexibility and optimized market participation. This paper contributes to the field by presenting a detailed methodology for developing a web-based tool, offering a practical application in a case study, and providing insights into the integration of industrial processes into electricity markets.
Original language | English |
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Title of host publication | Energy Informatics : 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I |
Editors | Bo Nørregaard Jørgensen, Zheng Grace Ma, Fransisco Danang Wijaya, Roni Irnawan, Sarjiya Sarjiya |
Number of pages | 18 |
Publisher | Springer Science+Business Media |
Publication date | 2025 |
Pages | 71-88 |
ISBN (Print) | 9783031747373 |
DOIs | |
Publication status | Published - 2025 |
Event | 4th Energy Informatics.Academy Conference, EI.A 2024 - Bali, Indonesia Duration: 23. Oct 2024 → 25. Oct 2024 |
Conference
Conference | 4th Energy Informatics.Academy Conference, EI.A 2024 |
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Country/Territory | Indonesia |
City | Bali |
Period | 23/10/2024 → 25/10/2024 |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 15271 LNCS |
ISSN | 0302-9743 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Keywords
- Demand response
- electricity consumers
- electricity market
- flexibility parameters
- optimization model
- Power-to-Hydrogen
- web-based tool