Researchers from the French transmission system operator RTE, including Camila Martinez Parra, Michel de Lara, Jean-Philippe Chancelier, Pierre Carpentier, and Jean-Marc Janin, have developed a new method to evaluate the opportunity cost of stored energy in large-scale energy systems, which is crucial for integrating more renewable energy sources. Their work was published in the journal “Energy Economics.”
As renewable energy sources like wind and solar become more prevalent, managing the intermittency of these resources becomes increasingly important. Storage facilities, such as hydroelectric dams, can help balance supply and demand, but determining the value of stored energy is complex. The researchers aimed to compute these usage values for each market zone in the interconnected European electricity system.
The energy system was modeled as a directed graph, with nodes representing market zones and arcs representing interconnection links. The system’s complexity arises from temporal factors (a one-year horizon with hourly time steps), spatial factors (thirty nodes, each with up to one aggregated storage unit), and stochastic factors (uncertainty in net demand, dispatchable generation, and inflows).
To tackle this complexity, the researchers incorporated a spatio-temporal decomposition scheme and applied Dual Approximate Dynamic Programming (DADP). This approach allows for tractable decomposition across both time and space, yielding nodal usage values that depend solely on the local state of each node. The researchers conducted numerical studies on a realistic system composed of thirty nodes, modeling part of Europe, and found that DADP obtained competitive results when compared to traditional methods like Stochastic Dual Dynamic Programming (SDDP).
This research has practical applications for the energy sector, particularly for transmission system operators and energy market regulators. By providing a method to accurately compute the usage values of stored energy, it can help optimize the use of storage facilities and improve the overall efficiency of the energy system. This is particularly relevant as the energy sector transitions towards a more decentralized and renewable-based system.
Source: Martinez Parra, C., de Lara, M., Chancelier, J.P., Carpentier, P., & Janin, J.M. (2023). Temporal and Spatial Decomposition for Prospective Studies in Energy Systems under Uncertainty. Energy Economics.
This article is based on research available at arXiv.