Regionalized LCA-Based Optimization of Building Energy Supply: Method and Case Study for a Swiss Municipality

Abstract

This paper presents a regionalized LCA-based multiobjective optimization model of building energy demand and supply for the case of a Swiss municipality for the minimization of greenhouse gas emissions and particulate matter formation. The results show that the environmental improvement potential is very large: in the optimal case, greenhouse gas emissions from energy supply could be reduced by more than 75% and particulate emissions by over 50% in the municipality. This scenario supposes a drastic shift of heat supply systems from a fossil fuel dominated portfolio to a portfolio consisting of mainly heat pump and woodchip incineration systems. In addition to a change in heat supply technologies, roofs, windows and walls would need to be refurbished in more than 65% of the municipality's buildings. The full potential of the environmental impact reductions will hardly be achieved in reality, particularly in the short term, for example, because of financial constraints and social acceptance, which were not taken into account in this study. Nevertheless, the results of the optimization model can help policy makers to identify the most effective measures for improvement at the decision making level, for example, at the building level for refurbishment and selection of heating systems or at the municipal level for designing district heating networks. Therefore, this work represents a starting point for designing effective incentives to reduce the environmental impact of buildings. While the results of the optimization model are specific to the municipality studied, the model could readily be adapted to other regions.

RELCA: a REgional Life Cycle inventory for Assessing bioenergy systems within a region

“…The regional boundary denotes the foreground activities relating to the bioenergy systems being assessed [12,29,80,81]. However, such foreground activities also require inputs from outside the region (e.g., fertiliser products, fossil fuels, grid energy), these can be considered as flows from the "non-regional background" (Figs.…”

Streamlining scenario analysis and optimization of key choices in value chains using a modular LCA approach

“…A benefit of using optimization techniques is the possibility of considering additional constraints, such as limited raw material supplies or production capacities. LCA and linear programming have been combined since the 1990s (Azapagic and Clift 1998) for applications ranging from process design (Gassner and Maréchal 2009;Guillén-Gosálbez et al 2007) to regional resource management (Saner et al 2014;) and the optimization of large-scale systems (You et al 2012). A potential advantage of using optimization approaches is also that solutions have been proposed regarding typical LCA problems, e.g., multiple objectives (Azapagic and Clift 1999;Guillén-Gosálbez 2011;Tan et al 2008) and uncertainties (Guillén-Gosálbez and Grossmann 2010;Tan 2008), leading possibly to more robust results than standard LCA.…”

“…Further, building upon work by Saner et al (2014), we show how modules can be used as a direct input to an optimization problem (case study wood). In addition, a tool that enables the creation and linking of modules as well as automated scenario analyses is provided as free open source software (Steubing 2014).…”

GIS-based Life Cycle Assessment of urban building stocks retrofitting- a bottom-up framework applied to Luxembourg

“…Analyses were carried out at different scales, from the urban scale [13,14] to the national [12,15,16] and transnational scale [17]. The archetypes technique [4], originally conceived for building stock energy analysis and successively extended to LCA is commonly used in studies of this kind.…”

“…This method consists in modelling a number of buildings representative of the stock, simulating their environmental performance and then extrapolating the results to the entire building stock. Results delivered include estimation of the environmental improvement potential of building stocks achievable by implementing retrofitting measures [16,17], testing of sustainable energy targets for buildings [13,15] and optimization of the energy supply [14]. One of the limitations in the archetypes approach is the obvious simplification, which does not allow an accurate description of the full variety of geometrical and construction characteristics of buildings.…”