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.

This blog is reposted from The University of Strathclyde blog where it was published in September 2018

The Climate Change Bill, presented by the Scottish Government in May 2018 seeks to raise the ambition of the 2050 target from an 80% reduction in greenhouse gas emissions from the baseline to a 90% reduction. As well as providing the outputs from analysis of the global costs and benefits of climate change action, and the ‘administrative costs’ for the Scottish Government of moving the target, the accompanying Financial Memorandum presents estimates of the whole system costs for Scotland. We have looked at how these calculations were done, and what is included and excluded from them.

The Financial Memorandum briefly explains the process developed, using the Scottish TIMES model, to estimate the whole system cost to achieve the 90% decarbonisation target. It notes that the TIMES-derived analysis considers only total system costs and not any ‘administration’ costs.

Scottish TIMES is a high-level whole energy system model, allowing the analysis of least-cost energy future scenarios (see our earlier report for more information on the TIMES model). Models such as TIMES are particularly useful for conducting whole system analysis, and they can be really effective decision-support tools. However, we have identified a number of issues with the use of technology-driven models, such as TIMES, for assessing costs in the energy system.

Not all the potential costs (and benefits) are considered.

TIMES provides detail in its calculations of technology and energy costs. However, not all costs are considered. Significant omissions include:

  • Economy-wide sector and market impacts. Changes to the ways in which sectors exchange (buy and sell) fuel and technologies to one another, have implications on labour, capital and commodity prices, affecting economic growth and energy demand. The analysis developed through TIMES would benefit greatly from also using a whole-economy economic model to understand the impacts on the economy due to the changes in the energy system. See our earlier report for further discussion on this.
  • Financial costs. As a model, TIMES assumes that all investment money for the energy system is available. The model does consider an overall discount rate for all investments, but this implies that the cost to borrow money is the same for all sectors and for all projects, which we know is not the case in practice.
  • Other social costs and benefits. The decarbonisation of the energy system is likely to bring other costs and benefits to the Scottish people. For instance, improving the energy efficiency of the building stock and the decarbonisation of transport are expected to produce important improvements in health and well-being. These effects cannot be captured in TIMES and other tools and analyses will be needed (as indeed the Scottish Government has recognised; see for example the three ‘Evidence Reviews of the Potential Wider Impacts of Climate Change Mitigation Options’ published by the Scottish Government on 19 January 2017).

The importance of model assumptions.

As a cost-optimising systems model, TIMES is an extremely effective tool for supporting analysis of decarbonisation scenarios. However, its long-term character makes it very sensitive to the assumptions made on demand projections, technology costs profiles and expected technology availability. It is therefore critical that users understand the assumptions made, in order to assess the reliability of the outcomes. Unfortunately, the Financial Memorandum lacked detail on the model assumptions.

We have commented previously on the importance of this in our comments on the Climate Change Plan Technical Annex. We would underline that making model assumptions more transparent would allow closer scrutiny by external stakeholders of the reliability of outputs from the TIMES model.

How can we really know what the energy system will look like in 2050?

To achieve deeper emissions cuts than currently legislated, the energy system will have to change more profoundly than currently projected. The Financial Memorandum recognises that decarbonisation costs increase considerably from 2040 (before that, the energy system under the 80% and 90% targets does not look significantly different), which suggests that the last 10% of decarbonisation is the most difficult to achieve and involves expensive technology changes. The lack of information on the technology mix in 2050 creates two potential problems. i) It may be based on ´future´ technologies that are not widely commercially available yet (e.g. hydrogen or CCS), for which actual costs and performance are likely to be very different from our current expectations. ii) The actual sectoral allocation of costs cannot be assessed, such that we do not know which sectors will have to take on the biggest burden of the decarbonisation target.

Ultimately, who pays and who benefits from this?

At the University of Strathclyde’s Centre for Energy Policy we have two main strands of research relating to climate change policy. Both are critical to developing a deeper understanding of the future whole system costs (and benefits) of the low carbon transition. First, we look at who ultimately ‘pays the bill’ for action to meet policy targets. Second, we consider how a wider range of societal benefits might emerge as a result of taking action(s). These questions are important because climate change policy is particularly subject to ‘public good’ problems where private costs of actions borne by individuals (e.g. energy bill payers) are generally not offset by delivery of private benefits, or at least benefits that are currently valued by those paying the costs.

The problem is compounded by the fact societal benefits do not necessarily accrue where costs are borne. Scottish action to reduce climate change impacts may deliver benefits that ultimately accrue mainly in other parts of the world while costs are borne in a range of ways by Scottish consumers, taxpayers and the wider private and public sectors.

Understanding which parts of society ultimately pay for and benefit from climate actions, and communicating the nature and extent of a wider set of societal costs and benefits arising, provides a solid foundation for developing climate policy that meets wider societal goals of sustainable and inclusive growth. It can help determine both what the overall level of ambition should be (e.g. a 90% or net zero target) and what policy actions should be taken across sectors.

The ambitious climate targets set by governments and the interconnection between energy and economic objectives requires careful planning and assessment. Among other instruments, energy and climate specialists often rely on models to inform their policy recommendations. Specialists have extensively used whole energy system models, like TIMES, and energy-economic models, such as Computable General Equilibrium (CGE). Each type of model presents different features and has strengths and limitations. However, the interaction of models, mainly using a ‘soft-linking’ approach, is recognised as a potential solution to overcome some of the drawbacks of the standalone models, and to improve the depth of analyses. The approach consists of using information from one model to inform the other in iteration until the two models are harmonised.

The University of Strathclyde Centre for Energy Policy and Fraser of Allander Institute are currently investigating best practices and challenges on the use and links of TIMES/CGE models for the analysis of future climate and energy scenarios in Scotland. The research is supported by ClimateXChange. Preliminary results from the research have been discussed during a one-day workshop in May 2018.

The event brought together stakeholders and researchers from different countries, to discuss practical challenges and share experiences. Presenters in the workshop included: Andrew Mortimer (Scottish Government), Patricia Fortes (New University Lisbon), Matthew Winning (UCL), Anna Krook-Riekkola (Luleå University of Technology), James Glynn (UCC), Anna Darmani (InnoEnergy), and the two organisers of the event Gioele Figus and Christian Calvillo (University of Strathclyde).

Gioele Figus and Christian Calvillo presenting their research

Each presentation provided a valuable point of view in the debate. Although, Portugal, Sweden, Ireland or Scotland may have different policy objectives, the presentations have highlighted common methodological practices and challenges that are applicable across different countries and regions.  The process of linking the two models and use them in an iterative fashion raises a number of challenges that the Strathclyde team has summarised as follows:

  • Model calibration, updating and data problems. Using TIMES and CGE is a dynamic process that requires constant updating and development. This requires considerable efforts and time. Moreover, the data to calibrate and update the models is not always available, and this further complicates the process.
  • Validation of model improvements. When models are developed to improve the analysis of specific policies (e.g. modifying the CGE model to better represent the power system), it is difficult to check the reliability of the outputs. This is because the data might not be available to validate the changes made.
  • Fundamental differences in the models’ objectives. The two models have been created with different objectives. TIMES chooses the technology mix that minimises the cost of delivering energy to a specific country or region. The CGE considers firms within the same region that produce goods and services by maximising their profit and sells them to consumers. To reconcile both objectives is not always an easy task.
  • The soft-linking methodology is not straightforward. What to link and how? Which one is the dominant model? Where to start? Convergence criteria? These all are important questions that do not have a single general solution, as this depends on the application and analysis objectives.
  • Data harmonisation for soft-linking. Mapping sectors and variables from one model to the other is not straightforward and it is likely to be different in both directions. For instance, the two models express energy in two different units of measure, monetary versus physical units.
  • Sector bias on models. Researchers often focus on improving one single aspect of the two models, such as the treatment of heat or a particular industry. However, this could create imbalances in the solutions and potential reliability of the model, when a holistic approach is not considered.
  • When to stop? Further improvements are always possible, but it is not always clear when new changes in the models are adding value to the analysis, making worth the effort, and when changes could bias the solutions.

There are clearly many challenges in the use of these two modelling families, and the workshop participants agreed to continue to collaborate and share information. However, some best practices have already emerged. These are:

  • The importance of the baseline scenario – Each model considers a baseline against which counterfactual scenarios can be assessed. The consistency of the baseline in the two models is fundamental for a successful soft-link.
  • Soft-linking is not always the solution. Some questions can be answered directly with one model or the other, removing the need of complicated soft-linking processes. Here, it is fundamental to have specialists with enough knowledge of the two models to assess which instrument is the most appropriate.
  • Clear time frames for policy decisions help choosing the adequate model. As discussed previously, different models have been developed with different objectives and time horizons. For instance, TIMES can be used to answer how the energy system will look like in 30 years time, but it might not be the best tool to assess the changes in the energy system in next one to two years. It is, therefore, important to understand this in order to use the best tool for the problem at hand.

The main point to take home from this workshop is that an active and cohesive community of experts is a prerequisite for the correct and informed use of complex modelling technique for policy analysis. The workshop participants have agreed to increase the level of engagement by setting up forums and shared repositories of documents. Moreover, a second meeting will take place this time next year to continue discussing the progress made by the Strathclyde team and by the rest of the community.

Read more about our energy research

As Prof. Karen Turner has noted, the Scottish Government gave energy folks an interesting early Christmas present: the new Scottish Energy Strategy. The strategy outlines the vision and main objectives for the energy system in Scotland up to 2050, and the alternative options that may be pursued to help achieve them.  In other words, it describes “low-regret” priorities, policies and technologies to help achieve the objective of a mostly decarbonised energy system for Scotland.

The strategy presents two indicative scenarios (informed by the Scottish TIMES model), depicting two different potential futures for the Scottish energy system: one based on electrification, and one based on hydrogen (note that these scenarios do not imply a 100% reliance on a particular energy carrier but rather which one will be the main fuel. So the electric scenario also considers hydrogen in a smaller scale, and vice versa).

Though certainly “these [scenarios] are purely illustrative, designed to help us understand what infrastructure and behaviours might be required under different future scenarios” (Scottish Energy Strategy).

Note that in order to model these “extreme” scenarios in TIMES, several assumptions and user constrains are needed, which could be practical (or not) in real life. We are not provided with any information on these assumptions, but we’d like to believe they are based on realistic projections and considerations.

Also, TIMES tries to find the least-cost solution for the energy system, according to the particularities defined in each scenario. However, it is unlikely that either future energy scenario will deliver the cheapest energy system, and the ‘optimal’ solution is likely to fall somewhere in between. Therefore, this brief analysis will try to assess what elements are less or more plausible from each scenario, what can we learn from them and to provide some insights on how the future will look like.

Scenario 1: an electric future

This scenario is based on the electrification of services, mainly replacing fossil fuels for transport and heating needs. The specific changes in the different sectors include:

  • In transport, the Scottish car and van fleet has been fully converted to electric vehicles. Important infrastructure investments will be carried out, with fast chargers replacing petrol pumps at service stations, and a range of charging infrastructure will be available both domestically and in other typical destinations such as supermarkets and carparks.

Buses will also be transformed to electric drive trains and heavy good vehicles (HGV) will be fuelled partly by electrolysed hydrogen fuel.

  • In the residential and services sector, most buildings will use heat pumps, with heat storage (when possible) providing more flexibility. Additionally, important attention will be paid to energy efficiency in buildings, so energy demand will decrease significantly. All this will translate to around 80% of total residential demand and 70% of the service sector will be electric.
  • In the industrial sector, less changes are expected as the industrial sector relies on a mix of fuels, to meet the specific requirements of certain processes, which cannot be provided solely by electricity.
  • In the power sector important changes are expected. The electrification of services will produce an increase of 60% in electricity demand (since 2015), and it will be accompanied by the growth of renewable generation.

Peak demand will also increase considerably, but this is mitigated with smart meters, demand response, and new market structures, promoting changes in consumer behaviour. Stronger interconnectors with Europe and the rest of the UK will be present to balance the high levels of renewable generation, and Scotland retains some gas generation capacity but this is used increasingly rarely.

  • Overall, a reduction a 30% in final energy delivered through the energy system is achieved in this scenario.

This scenario has many elements that seem not only possible, but also probable. For instance, the full electrification of the Scottish vehicle fleet, considering the technology availability at this point and the objectives and investment plans set by the Scottish Government. On the other hand, the electrification of heating is, of course, possible as the technologies are available and continue to improve.

However, to achieve this level of change involves several factors that are not straight forward. First of all is cost, right now the unit of electricity is almost four times the price of the unit of gas and according to the tariff and the technology used, the average cost of heating your house with electricity could be approximately 2 to 4 times higher than the equivalent using gas and that is not even taking into account the equipment costs.

So considering that the electricity demand is only going to increase (due to the electrification of heat and transport) I can see electricity prices, and thus costs, going up. The cost also relates to a second point: behavioural change.

In order to be as cost-effective as possible, the electric heating and hot water production requires changes in behaviour from consumers; that is, when and how we use our heating systems. Information feedback and smart systems will be increasingly important for this, making sure that the user has the right incentives to be involved, as not everyone might have the knowledge, the tools or the willingness to behave “optimally”.

Scenario 2: a hydrogen future

The second scenario is based on using low carbon hydrogen as the main fuel to meet our energy needs. Therefore, most of the end-use gas demand and fossil fuels for transport are replaced by hydrogen. The specific changes in the different sectors include:

  • In transport, all cars and vans will be hydrogen-powered, using fuel cells and an electric drivetrain. So, petrol and diesel service stations are converted gradually to hydrogen. A similar change happens with hydrogen-powered buses and HGVs, partially decarbonising larger road vehicles.
  • In the residential and services sector, Natural gas boilers will be replaced with highly efficient hydrogen boilers and fuel cells, and whenever possible other appliances are converted as well. Hence, 60% of demand in the residential sector will be met with hydrogen.
  • In the industrial sector, Hydrogen replaces natural gas for most industrial and commercial heat demand. However, some specialist processes will continue to use natural gas. Processes at large industrial installations will be coupled with carbon capture and storage (CCS).
  • In other infrastructure, Hydrogen is produced through electrolysers (taking advantage of renewable energy) and from steam methane reforming (SMR) plants paired with CCS. So, the national gas transmission system will continue to supply an increased demand of natural gas to feed the hydrogen production process (demand for gas as an input increases by around 60%).

The gas demand will be met from a variety of sources, a large share of which will be imports of both natural gas from Europe and liquid natural gas (LNG) from other markets world-wide.

Just like the electrification scenario, this hydrogen scenario has many elements that seem feasible for the future, especially on those changes relating to industry, as several processes cannot be supplied with electricity, and thus the reliance on technologies such as CCS.

Additionally, this hydrogen scenario gives renewed importance to the Scottish gas and oil sector, which is one of the defined priorities of the Scottish Government, by maintaining the gas network to supply the required natural gas for hydrogen production and to store captured carbon.

For the residential and transport sectors, the path presented in this scenario is not that straightforward. Hydrogen fuelled cars and vans are currently available but they have not reached the scale and costs of EVs (hydrogen cars are currently 2 to 3 times more expensive), so the latter technology seems slightly more plausible in the medium term.

On the other hand, hydrogen used for heating looks like a sensible idea, as current infrastructure can be used with only minor changes (in comparison with the alternative of electrification, which is likely to require more infrastructure investments on the power system and equipment change at household level). However, it is not clear at this point how expensive will be hydrogen as a heating fuel, and if it makes more sense than electricity.

What can we learn from the scenarios and what can we expect for 2050?

There are many uncertainties and questions for the future, but despite all the big unknowns, these two scenarios give, in my opinion, three important hints for 2050: i) what we don’t want, ii) what we do want, and iii) that the final outcome will be some hybrid of the fully-electric and hydrogen scenarios.

Things that we probably won’t see

The UK Government in its Clean Growth Strategy presents three possible scenarios for 2050, two very similar to the ones presented by the Scottish government (based on electricity and hydrogen) and an alternative one called ‘Emissions removal pathway’, based on using biomass and CCS.

I believe that the Scottish government did not present a third alternative scenario because that would be clearly infeasible, highly impractical (like a full reliance on biomass, or full reliance on imports), or based on “prohibited” technologies. Alf Young raised this same point, remarking that there is no mention of nuclear or fracking, suggesting that they will not be considered in the future energy system.

Common ground

For the second point, we need to look into the common ground between the two scenarios. Also considering the vision and guidelines set on the energy strategy, there are some elements that stand out.

For instance, hydrogen and CCS technologies seem to be an important part of several industrial processes, so this is likely to happen no matter the scenario. Another common point is the increase of productivity.

Both scenarios suggest that there will be important efforts towards improving buildings’ energy efficiency, and the strategy sets a new productivity target which is likely to affect technologies and the way we do things, independent of the energy carrier we use (the wider scope of this productivity target is discussed with more detail in Karen Turner’s blog post).

The final outcome

Lastly, the Scottish Government recognises that “Scotland’s energy system in 2050 is unlikely to match either of these (scenarios), but will probably include aspects of both.” In the transport and residential sectors there are no clear ‘winners’, so the most probable outcome is to have complementary technologies.

For instance, a large share of the car and van fleet is likely to be electric, with some hydrogen (fuel cell) vehicles as well, and for bigger vehicles (such as HGV and buses) hydrogen seems to be a more reliable option.

A similar mix of fuels is likely to happen for residential heating. Heat pumps and storage heaters continue to improve and are readily available, while pipes serving domestic hydrogen will still take a few years to be fully accessible.

So it seems that considering the urgency to decarbonise the building stock (see the targets set on the Scotland’s Energy Efficiency Programme (SEEP)), many houses, especially those not connected to the gas network, will take the electric path while other will slowly transition to hydrogen in the medium term.

Whichever the path we follow, what is clear is that action must be taken as soon as possible, and everyone has to play their part to achieve a smooth and successful energy transition.

This blog was first published by the 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 http://iea-etsap.org/index.php/etsap-tools/model-generators/times 

References

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, 2017.

IEA, 2014. Publication: Capturing the Multiple Benefits of Energy Efficiency [WWW Document]. URL https://www.iea.org/publications/freepublications/publication/capturing-the-multiple-benefits-of-energy-efficiency.html (accessed 4.3.17).

IEA-ETSAP | Energy Systems Analysis Applications [WWW Document], 2017. URL https://iea-etsap.org/index.php/applications (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 ceu@scotland.gsi.gov.uk.

Scottish Government, 2017b. Draft Scottish Energy Strategy: The Future of Energy in Scotland [WWW Document]. URL http://www.gov.scot/Publications/2017/01/3414/downloads (accessed 2.6.17).

Scottish Government, 2017c. National Infrastructure Priority for Energy Efficiency – Scotland’s Energy Efficiency Programme [WWW Document]. URL http://www.gov.scot/Publications/2017/01/2195/downloads (accessed 2.9.17).

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.