Scottish TIMES is a whole system energy model of Scotland. It models all key areas of the energy system, from generation, transportation and end use, and all key sectors of the economy. It is used by the Scottish Government as an analytical tool to support the development of climate change and energy-related policies and plans.

The industrial sector is a key sector within TIMES as many of its outputs are used by other modelled sectors and are therefore inherently linked. Inaccuracies in the industrial sector data could potentially have large implications for the rest of the model, under- or over-estimating costs and emissions.  

The aim of this project was to update and improve the current assumptions in Scottish TIMES relating to the industrial sector. The project reviewed and updated key data related to variables such as cost and process efficiency and checked them against the latest sector, industry, or academic research to ensure they are up to date and that they provide an accurate representation of the technologies and processes within the sector.

This, therefore, provides an accurate set of data on how much each sector contributes to Scottish greenhouse gas emissions, having reviewed the following sectors: carbon capture usage and storage (CCUS), hydrogen, biofuels, petroleum refining, chemicals, cement, food and drink, iron and steel, paper products, non-ferrous metals, non-metallic minerals and other industries.

The review has led to updating of a range of parameters such as capital and operating cost, process efficiency, expected operational life and technology availability date for the industrial processes across sectors where such data was available. This included data for new and emerging technologies such as CCUS and hydrogen, along with traditional industrial sectors such as oil refining and chemicals. As TIMES is a cost optimised model that selects the lowest cost technology option, updating these parameters could have significant implications on which technologies are selected and how they are operated under different decarbonisation scenarios.

The review also identified several new processes for inclusion, such as hydrogen above ground storage, and recommended the removal of others such as hydrogen salt cavern storage, as these are not available in Scotland. The review updated data for industrial processes that are common across a range of sectors, such as motor drive, low and high temperature heating, drying and refrigeration.  

This report looks at different approaches to modelling energy efficiency within TIMES, the whole energy system modelling framework used by the Scottish Government to inform energy and climate change policy decisions. The findings are based on six different energy efficiency scenarios for residential heating.

This has two objectives:

  1. To identify different approaches for energy efficiency scenario modelling in TIMES, and provide an assessment of strengths and limitations of each modelling approach.
  2. To give recommendations on how to use TIMES effectively for energy efficiency policy analysis.

There is no single energy efficiency scenario which is superior to the others, as each focuses on different policy targets which could come into conflict with each other. For example, the results of some scenarios prioritise energy efficiency improvements whereas others prioritise cost reduction or emission reductions. Policy makers should understand the compromises involved in using each of these scenarios and prioritise certain indicators over others.

The Scottish Government has set very ambitious targets and policies in its Climate Change Plan to decarbonise the energy system. The Scottish TIMES model is as a key tool informing these new climate change policies.

TIMES is a well-known, widely used model. However, the adequacy of TIMES for energy efficiency policy analysis has not been assessed in the literature. This report sets out the potential for using TIMES to understand the system impacts of energy efficiency improvements.

The main challenges identified in the specific context of using TIMES for energy efficiency analysis are:

  • Energy efficiency implementation in TIMES is not straightforward. Several approaches could be followed, delivering potentially different results.
  • Decisions are cost driven. The cost minimisation algorithm would lead to outcomes involving extreme specialisation (corner solutions), if not prevented by user determined constraints (e.g. imposing maximum shares for different technologies).
  • Energy demands and actions and reactions across the wider economy impacts are not modelled within TIMES. More generally, market “problems” and other drivers for consumer behaviour are not captured.

From a policy analysis perspective, TIMES is a very powerful tool that could be used to support decision making. Therefore, building on the model’s strengths, the report discusses possible TIMES uses and ways to go forward, grouped as:

  • using TIMES as it is;
  • developing TIMES improvements; and
  • soft-linking with other models.