The Meso level in CHEETAH
The Meso level in CHEETAH refers to the energy-demand/energy-system level (see project overview here). At at the energy-demand level the aim of the project is to implement the findings from the micro-level regarding consumer-decision-making in energy demand models and to provide European energy demand scenarios until 2030. These scenarios will take the great variety of consumers, countries and policies into account.
Energy demand models are used widely in energy efficiency policy decision-making. Projecting long-term energy demand is an essential component in designing policies to increase energy efficiency. In order to be a useful tool, energy demand models have to provide the possibility of analyzing the impact of energy efficiency strategies and policy measures.
One of the main aims of energy efficiency policy is to reduce the barriers to the adoption of energy efficient technologies and services. Currently, a so-called energy efficiency gap is observed between the actual uptake of energy efficiency innovations and the economically optimal level (both at the individual and societal level). A variety of market imperfections and other barriers that prevent the uptake of energy efficiency innovations have been discussed and include information asymmetries, split incentives, lack of interaction between user and producer, lack of awareness, lack of upfront capital. In order to effectively support a transformation of the market, it is essential to design policies that address these barriers.
In recent years, a variety of energy efficiency policies have emerged and it becomes crucial for energy demand models to take account of these policies as well as the barriers they address in a more realistic way. Most energy demand models only partly take into account barriers and the policy measures addressing these. The state-of-the-art bottom-up model is based on an explicit representation of the technology stock and considers the costs of energy efficiency options in detail. But with regard to barriers, most models only make use of an aggregated approach, like an adjusted discount rate. Such implicit discount rates provide a highly aggregated picture of the consumers’ time and risk preferences as well as all barriers to the adoption of energy efficiency measures. Unsurprisingly, these implicit discount rates largely exceed market discount rates.
As an example, the PRIMES model used by the European Commission for their energy planning, uses a standard discount rate of 17.5 % for households, where in its most recent projections (Reference Scenario 2013) the discount rates are assumed to decline reflecting policy implementation. The discount rates decline from the standard discount rates in 2010 to the 2020 levels linearly in response to the energy efficiency directive and remain at those levels throughout the remaining projection period.
While the declining discount rates constitute an improvement compared to policy-invariant rates, there is much room for improvement. It is clear that applying a single discount rate and a single decline rate for all households in all the EU member states does not reflect the richness and variety of decision-makers as well as policy approaches. Energy demand models largely increase their usefulness if policy impact can be modelled in a more disaggregated way.
The aim of CHEETAH at the energy-demand-level is to implement the findings of the micro-level regarding consumer-decision-making in the energy demand models FORECAST and Invert/EE-Lab and to provide energy demand scenarios until 2030 taking into account the heterogeneity of consumers, countries and policies.