LAUSR

Abstract The dynamic integration of building energy models and power system models is essential to analyse the potential supply-side benefits of adopting Energy Conservation Measures (ECM) at the national, regional scale. The integration of these models requires the development of linear building energy models which are numerically compatible with linear power systems models. Ensemble Calibration is an automated model calibration methodology which identifies a cluster of lumped parameter building energy models (denoted Ensemble models) using an archetype building energy model. Each lumped parameter building energy model represents an ECM configuration (i.e., a combination of ECMs). The current paper introduces a novel mechanism by which Ensemble models are integrated with power systems models in a manner such that cost-optimal retrofit decision-making problems and power systems optimisation problems can be simultaneously solved. To achieve this objective, Ensemble models are reformulated as bi-linear models, which are then co-optimised with power systems models using a multi-stage optimisation algorithm. The methodology is tested using two building energy archetypes: a detached house archetype and a mid-floor apartment archetype. The archetypes are representative of the Irish residential stock built prior to 1970. The results show that the proposed multi-stage optimisation algorithm provides computational advantages to the solution of the equivalent problem using a brute force approach (i.e., solving building-to-grid models for each ECM configuration). The proposed method is 4.73 times faster than the brute force approach when the archetypes are decoupled and 73 times faster when the models are deemed to be coupled via a power systems model.