Modeling and Management of Short-Term Electricity Markets using Systems and Control

An Economic Circuit Theory Application

Master Thesis (2026)
Author(s)

S.J. Mostert (TU Delft - Mechanical Engineering)

Contributor(s)

M.B. Mendel – Mentor (TU Delft - Mechanical Engineering)

B. De Schutter – Graduation committee member (TU Delft - Mechanical Engineering)

M. Ramdin – Graduation committee member (TU Delft - Mechanical Engineering)

Faculty
Mechanical Engineering
More Info
expand_more
Publication Year
2026
Language
English
Graduation Date
07-04-2026
Awarding Institution
Delft University of Technology
Programme
Mechanical Engineering, Systems and Control
Faculty
Mechanical Engineering
Downloads counter
89
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Decarbonization is structurally changing the electricity generation mix and shifting market operation toward real time. As renewable penetration increases, short-term markets are characterized by higher price volatility and continuous position adjustment.

Two classes of models are commonly used to analyze these markets: fundamental and statistical electricity price forecasting (EPF) models. Both face limitations in representing modern market dynamics. Fundamental models are developed for stable, dispatchable systems and are unable to capture highly dynamic market behavior, while statistical models rely on historical data and lose validity under structural change.

To address these limitations, this thesis develops a dynamical systems model using economic engineering. The day-ahead, intraday, and balancing stages are consolidated into a single formulation, enabling the representation of real-time market dynamics. The model remains
valid under structural change by restricting exogenous inputs to renewable generation forecasts and demand profiles. Price volatility and trading behavior emerge endogenously from the system dynamics.

The dynamical formulation enables real-time market management using control theory. The transmission system operator (TSO) is modeled as an incentive-based feedback controller that steers trading behavior and promotes proactive imbalance resolution. Similarly, generator-level control mitigates the impact of forecast errors.

The resulting closed-loop system is constructed using economic circuit theory. The controllers are shown to reduce reliance on balancing reserves and improve system stability under high renewable penetration and supply shocks. Using dynamic scenario analysis, this thesis further evaluates how system flexibility and sector heterogeneity affect prices and market liquidity
across market stages.

Files

Thesis_final.pdf
(pdf | 2.96 Mb)
License info not available