MASSIVE: A scalable framework for agent-based scheduling of micro-grids using market mechanisms

Fritz, Jakob M.; Xhonneux, André; Müller, Dirk; Riebesel, Lea

doi:10.1186/s42162-025-00558-w

Typ	Amount	VAT	Currency	Share	Status	Cost centre
APC	934.10	0.00	EUR	100.00 %	(Zahlung erfolgt)	ZB
Sum	934.10	0.00	EUR
Total	934.10

Journal Article

FZJ-2025-03429

MASSIVE: A scalable framework for agent-based scheduling of micro-grids using market mechanisms

Fritz, J. M. (Corresponding author)FZJ* ; Riebesel, L. ; Xhonneux, A.FZJ* ; Müller, D.FZJ*

2025
Springer International Publishing Cham

Energy informatics 8(1), 101 (2025) [10.1186/s42162-025-00558-w]

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Please use a persistent id in citations: doi:10.1186/s42162-025-00558-w doi:10.34734/FZJ-2025-03429

Abstract: With the increasing share of distributed renewable energy sources the need arises to store excess energy and/or to shift demands to match the given supply. To coordinate multiple suppliers and demands in a local energy-system different control approaches can be used. This publication introduces a framework called MASSIVE that aims to coordinate multiple participants in a district energy-system. The energy-system is controlled in a distributed way by using a multiagent approach that is scheduled by a market-mechanism. This market-mechanism allows to coordinate many individual agents with only few restrictions by using pricing mechanisms. This offers an incentive for the agents to adapt their power consumption to best match the forecasted power supply. However, the agents are free to follow this incentive or ignore it depending on the value of the incentive. The individual agents are flexible in the internal approach to forecast power supply or demand, allowing easy development of agents using individual algorithms. The coordination takes place using a market-mechanism that is similar to the day-ahead market. It, however, is run multiple times a day to form a rolling horizon, making it less sensitive to forecasting errors. The market approach furthermore exhibits a nearly linear scalability with regard to the duration of the market clearing. On the used computer, the creation and solving of the linear optimization-problem is performed in less than one minute for approximately 1500 participating agents. Therefore, this approach is capable of real-time use and can be used in real-world applications.

Keyword(s): Energy (1st) ; Others (2nd)

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