| dc.description.abstract | This thesis examines the techno-economic evaluation of market-based congestion management
mechanisms in the Goor Business Park. With grid congestion emerging as a major challenge due to
increasing electricity demand and the limited capacity of existing infrastructure, this research
investigates alternatives to grid expansion. The primary focus is identifying an optimal market-based
congestion management mechanism to alleviate grid congestion in a business park environment, which
is critical to advancing the energy transition. Using the Python for Power System Analysis (PyPSA)
software, three congestion management scenarios were modeled: a scenario with storage units for
each company, a scenario with a group transport agreement, and a scenario with a capacity market.
The performance of each scenario was evaluated based on several critical indicators, including grid
dispatch, storage and photovoltaic (PV) capacity, solar curtailment, load shifting, load shedding, and
associated financial costs. The comparative analysis revealed that Scenario 3, which introduced a
capacity market and limited storage units, emerged as the optimal solution. This scenario balanced
operational efficiency and congestion reduction and minimized the need for costly infrastructure
upgrades by dynamically allocating grid resources and integrating targeted storage and load-shifting
mechanisms. In contrast, Scenario 1, while minimizing annual costs, required high initial investments
due to the extensive use of storage units. Scenario 2, which relied on load shedding and shifting, had
the highest operating costs due to frequent load shedding, making it the least feasible. The results
suggest that market-based mechanisms, particularly capacity markets, offer a sustainable and cost-
effective approach to managing grid congestion, especially in business parks where electrification is
increasing. The study highlights the potential for these mechanisms to serve as an alternative to grid
expansion, in line with EU directives to increase grid flexibility. This research contributes valuable
insights into the practical application of market-based congestion management and provides a
framework for its implementation in similar settings. | |
