Long-term planning of connected industrial microgrids Towards tractable decisions by game theory and energy exchanges management
Promotor: Prof. O. Deblecker Co-promotor: Prof. F. Vallée
This work falls within the context of energy transition that is getting more and more attention
since several years. The main goal of this energy transition is to ensure a decarbonisation and
denuclearisation of the generation fleet to advance towards a greener and safer new one. In this
context, recent years have witnessed a change of paradigm within the electrical system. In order
to manage the stress linked to the decentralised and intermittent generation systems such as
photovoltaic panels or wind turbines, the latter has to become smart, with active stakeholders.
One additional way to integrate Renewable Energy Systems (RESs) and Energy Storage
Systems (ESSs) and to take advantage at best of them is to form microgrids. Indeed, as the time
of return on investments in RESs and ESSs is often over several years, some companies may
be reluctant to invest in such installations. Without being part of a microgrid, this time mainly
depends on their own self-consumption as the local generation excess is generally sold at the
market price which is lower than the buying price including all taxes. With a microgrid, the
investment is performed by the company but the energy management is taken over by a
microgrid manager. Therefore, in order to increase the self-consumption rate and decrease the
time of return on investment, such companies could take advantage of the complementarity of
their load profiles inside a so-called Industrial MicroGrid (IMG).
The main objective of this thesis was to develop a tool for IMGs planning in order to promote
the development of such structures and to provide advices about a new regulatory framework
for microgrids. For that purpose, this work focuses on the investments planning inside IMGs
with connection to the main grid, while considering a proper internal and external energy
management. Long-term (regarding investments) and short-term decisions (regarding the daily
trends of the price decisions, including the energy exchanges management by the MGEM) are
co-managed via game theory.
Results have shown that the IMG concept is interesting for the companies, the Distribution
System Operator (DSO) and the Industrial Estate Operator (IEO). Concerning the companies,
the benefits linked to the investments are increased thanks to the IMG. Regarding the DSO, the
potential losses that would occur if the companies were only investing (without the IMG
structure) are decreased in all cases or even changed in benefits when the DSO is the MGEM.
In order to discuss the benefits linked to the role of MGEM, the IEO has been considered as
MGEM for some simulations. In the latter case, financial losses have been observed for the
DSO while the IEO makes benefits, which testifies that the role of MGEM is advantageous.
The benefits of the IEO could be invested in the IMG or used to provide financial aids to the
companies to further promote the IMG concept.
The developed tool also allowed to consider load management inside the IMG and the
possibility of sharing investments in RESs and ESSs in order to extend the IMG analysis. The
simulations can be performed according to different scenarios gathering different long-term
evolutions of the load and price profiles as well as different long-term pricing plans and levels
of RESs penetration. This allows the tool to be as complete and generic as possible.