Cost-benefit analysis and multi-criteria optimisation for low-carbon heating strategy options
Lead Research Organisation:
University of Bath
Department Name: Chemical Engineering
Abstract
Demands for space and water heating constitute a significant proportion of the total energy demands in the UK and are currently predominantly satisfied through natural gas, which makes the heat sector a large emitter of carbon dioxide and therefore an important sector to decarbonise.
There are many alternative low-carbon heating strategy options for the UK. The aim of the project is to evaluate the different strategies using cost-benefit analysis as well as multi-criteria optimisation in order to compare different optimal scenarios under different stakeholder preferences, quantify trade-offs between different strategy options and determine a set of value chains for low-carbon heating that have the greatest potential for deployment in the UK.
The 3.5-year PhD project will be carried out as follows:
1. In the first year, a comprehensive literature review and high-level cost-benefit analysis will be performed on the main strategy options identified. An exhaustive list of criteria will be identified in order to construct a cost-benefit model for each of the strategy options.
The costs and benefits of each heating strategy option with respect to each criterion will be identified from academic literature, government, and by conducting stakeholder surveys. The costs and benefits will be calculated for quantitative criteria and qualitative criteria will be assigned rankings. Sensitivity (or "what-if") analyses will be performed to test the robustness of the cost-benefit model to uncertainties in key parameters. The results will be presented as cost-benefit matrices and radar charts in order to compare all of the strategy options and shortlist 2-3 of the best options that will be examined in detail in the next stage of the PhD.
2. In the remaining 2.5 years the 2-3 strategy options will be explored through systems modelling and systematic multi-criteria optimisation approaches.
A value chain modelling and optimisation approach will be used to determine the system-wide impacts of implementing the various strategy options.
The Value Web Model will be adapted to model the integrated value chains for low-carbon heat. The model will account for the spatial dependence of key parameters. Detailed modelling of the temporal aspects will also be considered. The solution of an optimisation problem using the Value Web Model provides the combination of heating strategy options, where and when they are deployed and what the impacts are.
A multi-criteria optimisation will be performed, wherein a series of optimisation runs will be conducted, using combinations of different weightings for the different criteria. This will generate a "Pareto set" of optimal solutions, which encapsulates the trade-off between different strategy options. Specific scenarios extracted from the Pareto sets will be analysed and the most promising value chains for low-carbon heating that have the greatest potential for deployment will be identified. Sensitivity and stochastic analyses will be performed to ensure that the solutions are robust with respect to the uncertainties in the system.
There are many alternative low-carbon heating strategy options for the UK. The aim of the project is to evaluate the different strategies using cost-benefit analysis as well as multi-criteria optimisation in order to compare different optimal scenarios under different stakeholder preferences, quantify trade-offs between different strategy options and determine a set of value chains for low-carbon heating that have the greatest potential for deployment in the UK.
The 3.5-year PhD project will be carried out as follows:
1. In the first year, a comprehensive literature review and high-level cost-benefit analysis will be performed on the main strategy options identified. An exhaustive list of criteria will be identified in order to construct a cost-benefit model for each of the strategy options.
The costs and benefits of each heating strategy option with respect to each criterion will be identified from academic literature, government, and by conducting stakeholder surveys. The costs and benefits will be calculated for quantitative criteria and qualitative criteria will be assigned rankings. Sensitivity (or "what-if") analyses will be performed to test the robustness of the cost-benefit model to uncertainties in key parameters. The results will be presented as cost-benefit matrices and radar charts in order to compare all of the strategy options and shortlist 2-3 of the best options that will be examined in detail in the next stage of the PhD.
2. In the remaining 2.5 years the 2-3 strategy options will be explored through systems modelling and systematic multi-criteria optimisation approaches.
A value chain modelling and optimisation approach will be used to determine the system-wide impacts of implementing the various strategy options.
The Value Web Model will be adapted to model the integrated value chains for low-carbon heat. The model will account for the spatial dependence of key parameters. Detailed modelling of the temporal aspects will also be considered. The solution of an optimisation problem using the Value Web Model provides the combination of heating strategy options, where and when they are deployed and what the impacts are.
A multi-criteria optimisation will be performed, wherein a series of optimisation runs will be conducted, using combinations of different weightings for the different criteria. This will generate a "Pareto set" of optimal solutions, which encapsulates the trade-off between different strategy options. Specific scenarios extracted from the Pareto sets will be analysed and the most promising value chains for low-carbon heating that have the greatest potential for deployment will be identified. Sensitivity and stochastic analyses will be performed to ensure that the solutions are robust with respect to the uncertainties in the system.
