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Sara Hastings-Simon

Publications and source records attributed to Sara Hastings-Simon.

2 recordsLinked to original sources

Energy systems models are diagnostic tools, not projection machines

Energy systems models (ESMs) are a leading tool to guide the energy transition. They have been influential in supporting national decarbonisation strategies and regional system planning, but these complex models can be opaque. Their results are often presented predictively or prescriptively, with little exploration of uncertainty and without clear discussion of limitations. Consequently, projections of ESMs have often been given more authority than their evidence can bear, undermining their contributions to energy transition policy. We argue that ESMs should instead be applied as explanatory, diagnostic tools. Model studies should explore uncertainty to find robust insights and define limitations, interrogate model behaviour to find testable real-world explanations, and communicate these explanations plainly and responsibly. This approach shifts the evidentiary burden from plausible projections to real-world insights that can be broadly understood and debated, and considered alongside other forms of evidence. Used this way, ESMs can support robust, justifiable, and pluralistic decision-making.

physics.soc-ph↗

A Static Mean Field Game for Optimal Renewable Energy Investment

We develop a static mean field game formulation for optimal wind energy capacity siting in Alberta, Canada. The revenue model for agents is based on the expected wind resource at a location and the covariance of this wind resource with other locations. Agents choose locations to maximize long-run revenue while accounting for spatial correlations in wind resource availability. Spatial wind dependence is incorporated through an empirically calibrated covariance structure, combining a PCA-based component estimated from historical weather station data with a parametric residual kernel, to capture variability across locations. The equilibrium investment problem can be formulated as a quadratic program, which we solve for four policy scenarios that progressively restrict the feasible siting area, incorporating viewscape and transmission constraints beyond a baseline of minimal siting restrictions. These policy and infrastructure-driven land use restrictions are represented as constraints on the agents' action space, allowing us to examine their economic implications through a comparison of the MFG equilibria across policy scenarios.Our findings highlight the trade-off between regulatory land use objectives and economic efficiency in the use of renewable energy resources in the short and long term, and provide quantitative insights into how policy design shapes the spatial distribution and financial performance of wind investments. The static MFG formulation could be used to inform electricity system planning including, transmission planning and renewable energy development planning.

math.OC↗