Introduction to Building Stock Optimization and Sequential Pareto Optimization

<p>Building stock optimization aims to find the design or refurbishment solutions that lie on the trade-off between conflicting design objectives (such as between carbon emissions and the capital cost of refurbishment). Each solution on the trade-off consists of several houses with each of the houses being associated with one combination of refurbishment options – the number of refurbished houses, their archetype, and the refurbishment option applied, vary along the trade-off. Stock-level trade-offs are useful in policy development, in that an analysis of the trade-off provides information on, say, what is the minimum cost to achieve a target reduction in energy demand. The analysis also provides information on the number and type of houses to be targeted for refurbishment, and which refurbishment strategies should be applied.</p><p><br></p> <p>The simultaneous optimization of many buildings results in an exceptionally large and difficult optimization problem to solve. Our research has led to a sequential approach that solves the problem and provides information about the trade-off’s achievable for individual houses as well as the building stock. This repository provides an introduction to the research in the form of: a short video; a copy of the slides used in the video; and a brief written summary of the optimization concepts.</p>