Process-to-Market: A Web-Based Evaluation Tool for Electricity Market Participation

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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 languageEnglish
Title of host publicationEnergy Informatics : 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I
EditorsBo Nørregaard Jørgensen, Zheng Grace Ma, Fransisco Danang Wijaya, Roni Irnawan, Sarjiya Sarjiya
PublisherSpringer Science+Business Media
Publication date2025
Pages71-88
ISBN (Print)9783031747373
ISBN (Electronic)978-3-031-74738-0
DOIs
Publication statusPublished - 2025
Event4th Energy Informatics.Academy Conference, EI.A 2024 - Bali, Indonesia
Duration: 23. Oct 202425. Oct 2024

Conference

Conference4th Energy Informatics.Academy Conference, EI.A 2024
Country/TerritoryIndonesia
CityBali
Period23/10/202425/10/2024
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15271 LNCS
ISSN0302-9743

Keywords

  • Demand response
  • Power-to-Hydrogen
  • electricity consumers
  • electricity market
  • flexibility parameters
  • optimization model
  • web-based tool

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