David Andrew Cristina Fordham

• Fordham, David; Llamas-Jansa, Isabel & Ulleberg, Øystein (2025). The cost of simplification: Comparing surrogate electrolyser models in a MILP framework. Energy Conversion and Management: X. 29. doi: 10.1016/j.ecmx.2025.101433. Fulltekst i vitenarkiv Vis sammendrag

  In this work, we investigate how various surrogate models representing an electrolyser’s production curve influence mixed-integer linear programming (MILP) optimisation outcomes. We compare linear, piecewise-linear, and scalable piecewise-linear models, each fitted to a physical electrolyser model, and analyse their effects on hydrogen production overestimation and real revenue in a solar farm/electrolyser array case study. Additionally, we employ a MILP implementation of a rectified linear unit (ReLU) neural network as a surrogate model. The results indicate that using simple linear models can significantly overestimate hydrogen production due to their inability to capture the non-linearity of the component’s efficiency. This overestimation correlates with reduced real revenues. In contrast, the adoption of simple piecewise models can boost returns by up to 14% in this scenario. The findings indicate that simple enhancements to the detail of component models can substantially improve system-level performance and yield more reliable results, without greatly increasing computational demands. While electrolysers were used as a case study, this analysis can be extrapolated and applied to additional components for which surrogate models are required in order to be included in larger energy system models.

• Fordham, David & Lopes, Ilídio (2024). Constraints on the axion-photon coupling using stellar modeling. Physical Review D. ISSN 2470-0010. 109(12). doi: 10.1103/physrevd.109.123007. Fulltekst i vitenarkiv Vis sammendrag

  Asteroseismology has been shown to be, together with stellar modeling, an invaluable tool in constraining properties of novel physics. In this work, we study for the first time the influence of axionic production in the evolution of a late main-sequence star, comparing computational models with observational data in order to constrain the axion-photon 𝑔𝑎⁢𝛾 coupling parameter. We first perform a high-precision calibration of a stellar model to our target star, in order to obtain a benchmark for our other diagnostics. We then apply a two-stage test, first using global quantities and then resorting to precision seismic ratios. We find that seismology allows us to place an independent upper bound of 𝑔𝑎⁢𝛾≤0.98×10−10  GeV−1 at a 68% confidence level (CL), in the same order of magnitude as both the most recent constraints from the observation of globular clusters and previous bounds obtained through stellar modeling, but more stringent than most current direct axion detections. We also suggest a more conservative limit of 𝑔𝑎⁢𝛾 ≤1.38 ×10−10  GeV−1 at a 95% CL. Moreover, this new diagnostic method can be applied to stellar data that will be obtained in future asteroseismic projects.

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• Fordham, David; Hvidsten, Tobias Verheugen; Venegas, Guillermo Andrés Valenzuela & Zeyringer, Marianne (2026).  The Impact of Shortage Risk Tolerance on a Future European Net-Zero Electricity System – A Multi-Objective Optimisation Approach. doi: 10.5194/egusphere-egu26-20904. Fulltekst i vitenarkiv Vis sammendrag

  Energy system models are crucial tools for planning the transition to low-carbon power systems, particularly in the context of increasing renewable energy sources (RES) integration. However, the inherent variability and uncertainty of RES generation pose challenges for ensuring system reliability. As of today, capacity expansion models often enforce strict reliability constraints, leading to conservative investment decisions that may not reflect real-world risk tolerances, ultimately leading to overdimensioned systems. Reframing planning around acceptable risk can therefore have the potential to shift investment decisions from expensive and rarely used capacity to more valuable assets, such as targeted storage or transmission. Here, we implement an allowance for shortage tolerance in an electricity system model at NUTS2 resolution, using a multi-objective optimisation approach that minimises both total system cost and energy shortage risk. We explore the trade-offs between cost and reliability by analysing solutions on the Pareto front, and how they could influence the design of a future European power system with high RES penetration. Our findings expose which regions are most vulnerable to shortages, and allow for policy makers to make informed decisions on how to balance decarbonization, affordability, and local robustness. 

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