Market-based Congestion Management in Power Systems : With a focus on distribution grids

Abstract

Congestion in power grids occurs when the grid’s operational constraints are exceeded. These constraints arise from established standards (e.g., EN50160 [1]), such as permissible voltage limits and the physical limitations of grid components, like ampacity. When these thresholds are violated, the grid enters a state of congestion, which is undesirable and must be mitigated because it can reduce the quality of electricity supply to grid customers or potentially damage grid infrastructure. Although congestion is not a new phenomenon in power systems, its frequency and intensity have recently increased due to transformations in the electricity sector. Key drivers of this transformation include the electrification of the heating, cooling, and transport sectors and the rise in power generation from renewable resources, driven primarily by the urgent need for decarbonization. Most existing grids were not designed to accommodate these developments, as they were designed before the advent of technologies such as electric vehicles (EVs) and renewable energy sources (RES) like wind and solar power.

Today, system operators (SOs), responsible for grid operation and planning, primarily rely on congestion management (CM) strategies centered around grid reinforcement. This traditional approach involves investing in new transmission lines or upgrading components (e.g., cables, transformers) to increase grid capacity. However, grid reinforcement is both capital-intensive and time-consuming, often failing to keep pace with the rapid electricity demand and generation growth. As a result, SOs need new solutions that can complement traditional CM strategies to manage increasing grid stress more efficiently and cost-effectively. One solution that has been explored for over a decade involves leveraging flexibility from generation, demand, or storage units. For instance, demand-side flexibility allows households to shift electricity use (e.g., washing machines or EV charging) to periods of lower grid congestion, helping align consumption with grid capacity. This approach gives Sos greater control over grid operations, enabling them to implement predictive or corrective measures to prevent or mitigate congestion. While utilizing flexibility for grid management may seem straightforward in theory, it is a complex challenge in practice. It requires a shared understanding and coordinated actions among diverse stakeholders, each with its own objectives and responsibilities—ranging from grid customers and flexibility service providers (FSPs) to SOs and regulators. As such, ongoing research in the field is focused on making the entire system viable and efficient.

One approach to utilizing flexibility is through a market mechanism where flexibility as a service is traded on a market platform. From the perspective of SOs, this is known as market-based CM, and it forms the core focus of this thesis. However, for this solution to be viable, SOs must first access flexibility via a market (e.g., a local flexibility market (LFM)) and then utilize it effectively. Therefore, the accessibility of flexibility (AoF) and the effectiveness of flexibility (EoF) are central themes in the thesis. The thesis examines solutions to enhance SOs' access to flexibility and improve their effectiveness in managing congestion.

Concerning AoF, the thesis presents strategies, including market integration, visibility improvement of flexibility-related data to SOs, and market design, all aimed at improving AoF. One key approach to market integration is bid forwarding, which allows bids from one market to be exchanged with another, thereby expanding SOs' access to these bids. Additionally, the visibility of flexibility-related data is crucial for SOs' decision-making processes, as higher data transparency improves their ability to access and analyze the necessary information when managing congestion. Examples of relevant flexibility data include the location and capacity of flexible resources, the responsible FSP, and qualification data. Regarding the LFM design, the thesis emphasizes several factors that play a critical role. These include CM services, the timing and frequency of market operations, governance over market operations, coordination among market participants, and market entry barriers.

Regarding EoF, the thesis presents strategies to mitigate the adverse impacts of flexibility on the grid since flexibility utilization under certain conditions could cause more harm than good to the grid. Specifically, the thesis highlights that coordination between transmission and distribution system operators and a better understanding of the rebound phenomenon can significantly mitigate these adverse effects. Additionally, the size of the bidding area (BA) in LFM is identified as a crucial factor that can influence the effectiveness of flexibility in alleviating congestion issues.