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Title: The impacts of project scale, scope and risk allocation on financial returns for clients and contractors in Energy Performance Contracts : a stochastic modelling analysis
Author: Fennell, Pamela J.
ISNI:       0000 0004 7230 9998
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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With a projected annual value of £1bn, the UK energy performance contracting market has the potential to unlock a large number of energy efficiency projects by reducing risk of investing in energy efficiency upgrades in industry applications and in buildings. However, market development to date has been slow and little analysis has been undertaken to understand the characteristics of successful projects. A better understanding of the impact of project scale, scope and risk allocation on outcomes for building owners and their contracting partners, known as Energy Service Companies (ESCOs), would enable investment programmes to be targeted more effectively. This study uses probabilistic energy modelling of hypothetical case studies in the UK schools sector to assess the scale of possible energy savings from a range of retrofit measures. Samples from these distributions of energy savings are used as inputs to an economic model which allows the impact of different approaches to measurement and verification of the energy savings to be explored, along with the impact of energy price assumptions, project scale and scope and different guarantee mechanisms. The case study projects are based on hypothetical school buildings and combine 3 different scales of project with 2 different groups of retrofit measures. Despite evidence from previous work that transaction costs are critical to financial outcomes of projects there is an absence of data on the scale of transaction costs in the current literature. This study uses semi-structured interviews with building owners and ESCOs to elicit transaction cost information for the case study projects which form another set of inputs to the economic model. Global sensitivity analysis is used to screen for non-influential parameters in the energy model (modified Morris method), enabling a significant reduction in computational burden. Global sensitivity analysis is also used with the economic model to rank inputs in order of their influence on financial outcomes for clients and ESCOs, providing insight into the areas of uncertainty which have the largest impact. The results of this study suggest that • not all of these projects are well-suited to this form of procurement. In particular, cases with a small number of energy conservation measures perform less well than those with a more diverse set of measures • more effective monitoring methods are needed, but crucially, these must be focused on the collection of data which facilitates the allocation of responsibilities between the parties. • steps to increase market competition must take an holistic view of transaction costs to avoid reducing market testing of costs in competition which will result in increasing policing and enforcement costs • bundling smaller projects together cannot reduce risks for the ESCO unless there is a mechanism for balancing returns between individual projects.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available