Using the TIMES model in energy efficiency policy analysis

By Christian Calvillo, CXC Research Fellow, University of Strathclyde

Decision makers rely on models to assist them in taking the right decision on complex issues. The Scottish Government is using the TIMES model to inform the Scottish Climate Change plan (Scottish Government, 2017a) and the Scottish Energy Strategy (Scottish Government, 2017b).

TIMES is an energy system model, which is typically used for the exploration of possible energy futures based on contrasted scenarios (Loulou et al., 2005). It’s a well-known modelling tool, with many national and regional versions in the world (“IEA-ETSAP | Energy Systems Analysis Applications,” 2017).

In the Scottish context, TIMES is used to find the least cost energy system under the ambitious decarbonisation scenarios in Scotland. In other words, TIMES shows what the Scottish energy system would look like (the energy mix, technologies and required investments) if the decarbonisation targets for 2050 (set in the climate change plan) are to be achieved.

Having the full picture

One of the most important characteristics of TIMES is that it considers the whole energy system and a great number of different technologies. This means it considers all sectors, and all the process involved in the energy system. Traditionally, energy models focused mostly on the power system (power plants, transmission and distribution network, etc.) or in particular sectors (for instance, a transport energy system model), paying little attention to other areas of the energy system. However, TIMES covers all the energy system, including the processes that extract, transform, transport, distribute and convert energy to supply energy services.

This energy system-wide approach is very relevant for policy making, as a global view of the system permits to understand better all the possible implications of the policies. For instance, a carbon tax policy implemented will create a change in the energy mix (generation side) due to the increased cost of fossil fuels (such as gas or coal). However, the end-users are also impacted. For instance, there could changes on technology in the residential sector due to higher gas costs, substituting gas boilers for electric ones and heat pumps. Similarly, the transport sector could present important changes due to the more expensive fuels. Therefore, it is important to use an energy system-wide model, so the impact in all sectors can be assessed and policies are better informed.

How does TIMES work?

TIMES is a mathematical model with a very large number of variables, parameters and constraints. The inputs, driving all the energy system, are the data of the supply (resource availability and imports) and demand side (energy service demands). The annual energy required for space heating, cooking or for entertainment in each household are examples of the energy service demands that are input into TIMES.

The numerous techno-economic parameters of the technologies and processes are also given to the model. These parameters include technology costs (per unit), discount rates, efficiencies, and other technical constraints. For instance, the equipment costs, energy efficiency and lifespan of a gas boiler are examples of such techno-economic parameters.

The outputs of the model include emissions and waste variables, capacity planning of the different technologies and several economic variables, including energy prices, costs and profits. In addition, energy flows and losses between the different steps of the energy system are also outputs of the model. In other words, TIMES gives you the technologies, the energy flows (how much energy and of which type is produced and consumed), the costs and emissions of your energy system, relative to a certain demand projection and constraints.

Energy efficiency analysis

As a part of the energy strategy, the Scottish Government has defined energy efficiency in buildings an infrastructure priority (see Scotland’s Energy Efficiency Programme (SEEP) (Scottish Government, 2017c)). Hence, the interest of energy efficiency policy analysis with TIMES. However, two main challenges have been identified:

  1. Energy efficiency in buildings is not straightforward in TIMES. There are several ways to implement and model energy efficiency scenarios, and due to the modelling approaches taken and user constraints (such as maximum technology adoption rates), the outcomes could be quite different. For example, an energy efficiency scenario could be developed, limiting the buildings energy input without modifying the energy service demands, provoking (in theory) the system to shift to more efficient technologies and energy conservation measures (building retrofitting, thermal isolation, etc.). Alternatively, the energy efficiency scenario could involve the implementation of more energy conservation measures, but this not necessarily provokes the change in technology adoption and the actual energy savings could be lower than other scenarios. Therefore, a careful selection of the energy efficiency scenarios must be done, to obtain reliable outcomes and policy analysis.
  2. Not all energy efficiency benefits are captured. It has been identified that energy efficiency in buildings provides several benefits, not only on the energy system but on the wider economy, health and productivity as well (IEA, 2014; Riddoch et al., 2016). Moreover, it has been documented that energy efficiency measures commonly provoke “rebound” effects (Anson and Turner, 2009). However, these impacts are not captured in TIMES, mainly due to the heterogeneous demand drivers of the model, which do not respond to changes in prices or consumer substitution effects (families could use the savings on energy bills on other commodities/services).

Potential solutions and the way forward

We should remember that there are no perfect models and TIMES, despite its “problems”, is one of the best tools currently available to inform energy policy decisions. Therefore, using TIMES as it is a good first approach that provides sensible results and useful insight. However, the limitations should be taken into account. Therefore, this type of energy efficiency analysis should be seen as rough numbers, rough pathways. Also, it is required to run multiple scenarios, do sensibility analysis, and contrasts the results before taking decisions.

On the other hand, rebound effects and economic impacts can be better assessed with the soft-linking of TIMES with economy-wide models. This is a very promising second step, after solely using TIMES. The idea behind this is to use the outcomes of one model to inform the other in an iterative way. The economy-wide model will provide valuable feedback to the energy system, adapting the energy service demands and producing more accurate results, also allowing to assess other economy-wide impacts and benefits that could only be predicted otherwise (e.g. job creation due to energy efficiency). However, the soft-linking process presents several challenges including data aggregation issues, model fitting, common scenario assumptions, etc.

Certainly, there is not a unique “right” way forward. But it is important not to solely rely on a single model or a single analysis for complex policy assessment, where are so many factors involved. We should, therefore, remember that using the outcomes of multiple scenarios and different models are likely to deliver more reliable and effective energy efficiency policy.

(To learn more about TIMES and energy policy analysis, please see the report Using the TIMES model in developing energy policy)

TIMES schematic from IEA-ETAPS 


Anson, S., Turner, K., 2009. Rebound and disinvestment effects in refined oil consumption and supply resulting from an increase in energy efficiency in the Scottish commercial transport sector. Energy Policy, New Zealand Energy Strategy 37, 3608–3620. doi:10.1016/j.enpol.2009.04.035

ClimateXChange :: Using the TIMES model in developing energy policy [WWW Document], 2017. URL (accessed 10.2.17).

IEA, 2014. Publication: Capturing the Multiple Benefits of Energy Efficiency [WWW Document]. URL (accessed 4.3.17).

IEA-ETSAP | Energy Systems Analysis Applications [WWW Document], 2017. URL (accessed 8.14.17).

Loulou, R., Remne, U., A. Elbaset, A., Lehtila, A., Goldstein, G., 2005. Documentation for the TIMES Model PART I.

Riddoch, F., Turner, K., Figus, G., 2016. Increasing energy efficiency, improving household incomes and boosting the economy – University of Strathclyde.

Scottish Government, 2017a. Draft Climate Change Plan – the draft Third Report on Policies and Proposals 2017-2032 (Report). Scottish Government, St. Andrew’s House, Regent Road, Edinburgh EH1 3DG Tel:0131 556 8400

Scottish Government, 2017b. Draft Scottish Energy Strategy: The Future of Energy in Scotland [WWW Document]. URL (accessed 2.6.17).

Scottish Government, 2017c. National Infrastructure Priority for Energy Efficiency – Scotland’s Energy Efficiency Programme [WWW Document]. URL (accessed 2.9.17).



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