Residential energy efficiency in times – analysis of modelling approaches and impacts on energy policy

The TIMES energy system model has been used for informing energy and climate change policies in several countries and regions around the world. The type and scope of the studies varies, but many works consider (at least briefly) energy efficiency in their findings. However, very few include explicit energy efficiency scenarios and/or direct analysis of energy efficiency improvements. The studies that consider explicitly energy efficiency scenarios (in some cases in combination with other type of scenarios such as emission reduction targets) show significant differences on the modelling approach taken, potentially affecting the results and the impact policy decisions. Moreover, a direct comparison between energy efficiency modelling approaches in TIMES has not been developed yet. The work developed in this paper aims to provide insight on this issue, analysing the implications of different energy efficiency modelling approaches in TIMES, and discussing best practices on informing energy efficiency policy. Three types of residential energy efficiency scenarios are analysed using the UK TIMES model, all of them with the objective of reducing 10% of energy consumption on residential heating. Results show that these energy efficiency scenarios, which are in theory equivalent, produced different results, suggesting that the modelling approach taken can significantly impact the outcomes of the model. Also, not all energy efficiency scenarios performed as expected. In one of the scenarios, other user constraints (which are common to all the analysed scenarios) limited the amount of conservation technologies available, so the expected energy savings were lower than in other cases. Therefore, the outcomes obtained show the importance of not solely relying on a particular scenario or model for policy analysis, as this might lead to partial views or suboptimal solutions

Characterisation of Industrial Clusters in the UK and Techno-Economic Cost Assessment for CCTS Implementation

Following the recommendations of the UK Climate Change Committee (CCC) for the 6th Carbon Budget, the UK Government has set up a new target cutting emissions by 78% by 2035 compared to 1990 levels. In addition to this, and as a part of its COVID recovery plans, the UK Government has presented a 10-point plan for a green industrial revolution, describing investments and developments across different sectors of the economy. One key point of this plan is investing in carbon capture, usage and storage, linked to the industrial decarbonisation challenge launched by the UK Government, providing up to £170 million, matched by £261 million from industry, for the development of decarbonisation technologies such as carbon capture and storage and hydrogen fuel switching. The technologies will be deployed and scaled up within the six largest industrial clusters in the UK. All these recent policy developments suggest that there will be important efforts in the UK for the implementation of carbon capture, transport and storage (CCTS). However, there is a lack of detailed UK cluster definitions in the literature. Looking at the CCTS technology literature more widely, there is a considerable number of different cost models for these technologies. However, the available literature presents a wide range of cost values, the studies do not tend to consider all CCTS elements together (onshore, offshore transport networks, shipping and storage), in some cases the studies are too old, and there are very limited number of UK specific analyses. In this paper, we present a review and a detailed characterisation of the main UK industrial clusters. Also, we provide a brief review CCTS cost models and a techno-economic assessment of the characterised UK industrial clusters. To the best of our knowledge, this has not been done yet for the UK context, and such analysis is key for policy analysis and further research

Labour market and other wider economy challenges in decarbonising the UK's industry clusters [LAB-CLUSTER]

Through its Industrial Decarbonisation Strategy and specific mechanisms UK Government has committed to scale deployment of solutions such as Carbon Capture, Utilisation and Storage (CCUS) to decarbonise the UK’s industry clusters and to meet mid-century Net Zero ambitions. Understanding how these can be delivered in economically and politically feasible ways will be critical to the success of decarbonisation efforts and the realisation of wider economy benefits. This research aims to understand how persisting labour market supply constraints and other cost pressures may impact decarbonisation project delivery and sectoral/wider economy outcomes. Our research, focussing here on CCUS in the UK’s regional clusters, will enable consideration of how investment and deployment of industrial decarbonisation actions can be effectively delivered in a dynamic and challenging economic environment, where multiple net zero projects must compete for resources. It will also make a vital contribution to the evolving UK Government CCUS and Hydrogen business models that underpin decarbonisation in the industry clusters

How the pace of residential heat electrification impacts the energy system?

Heating buildings is the source of nearly a quarter of UK emissions (UK Government, 2021a). Thus, meeting net zero will involve virtually all heat in buildings to be decarbonised. In their Heat and buildings strategy, the UK Government (2021b) set out its plans to deliver at least 600,000 heat pump systems per year by 2028. This will involve significant changes to the energy system - including the upgrade of the energy networks and increasing renewable energy generation capacity - alongside the installation of new heating systems in people’s homes. Understanding how these costs are distributed, where benefits might accrue and how the wider economy might be impacted will be key. These questions are set within a quickly changing policy environment where for example, surging global gas prices have driven a significant increase to the energy price cap for GB energy consumers. Although the significant increase in international gas prices has markedly narrowed the gap between the cost of electricity and gas, this price differential - where consumers currently pay significantly more per unit of energy for electricity - remains an important factor for understanding how different decarbonisation options will affect the affordability of heating systems. Many studies have been developed to analyse the impact of heat electrification. However, most of them do not consider different heat pump adoption pathways and normally they only analyse the implications of a large penetration of heat electrification in the power sector, not considering, for example, the changes on emissions, energy use and consumer costs. The work developed in this paper aims to provide insight on this issue, analysing the implications of the electrification of residential heat under different adoption pathways, using the UK TIMES energy system model. Preliminary results show that the speed in which heat pumps are rolled out can have important impacts on energy use, emissions and the level of network investments, and thus higher costs for the final consumer

Getting to Net Zero Working Group : Energy Networks Snap-Shot Report

The electricity gas and heat networks are finding it necessary to increase their ad hoc interactions as they develop their contribution to the net zero1 targets for green house gases for the UK and Scotland. The organisations involved in the “Getting to Net Zero” working group are all directly engaged in the energy sector encountering day-to-day challenges around how to include “getting to net zero” in their operations. The working group met to consider the progress of networks to date in addressing net zero and to identify immediate actions that would remove barriers to progress. This snap shot report summarises the working group findings

Energy Management in Smart Cities

Models and simulators have been widely used in urban contexts for many decades. The drawback of most current models is that they are normally designed for specific objectives, so the elements considered are limited and they do not take into account the potential synergies between related systems. The necessity of a framework to model complex smart city systems with a comprehensive smart city model has been remarked by many authors. Therefore, this PhD thesis presents: i) a general conceptual framework for the modelling of energy related activities in smart cities, based on determining the spheres of influence and intervention areas within the city, and on identifying agents and potential synergies among systems, and ii) the development of a holistic energy model of a smart city for the assessment of different courses of action, given its geo-location, regulatory and technical constraints, and current energy markets. This involves the creation of an optimization model that permits the optimal planning and operation of energy resources within the city. In addition, several analyses were carried out to explore different hypothesis for the smart city energy model, including: a)      an assessment of the importance of including network thermal constraints in the planning and operation of DER systems at a low voltage distribution level, b)      an analysis of aggregator’s market modelling approaches and the impact on prices due to DER aggregation levels, and c)      an analysis of synergies between different systems in a smart city context. Some of the main findings are: It is sensible to not consider network thermal constraints in the planning of DER systems. Results showed that the benefit decrement of considering network constraints was approximatively equivalent to the cost of reinforcing the network when necessary after planning without considering network constraints. The level of aggregation affects the planning and overall benefits of DER systems. Also, price-maker approaches could be more appropriate for the planning and operation of energy resources for medium to large aggregation sizes, but could be unnecessary for small sizes, with low expected impact on the market price. Synergies between different energy systems exist in an interconnected smart city context. Results showed that the overall benefits of a joint management of systems were greater than those of the independently managed systems. Lastly, the smart city energy model was applied to a case study simulating a real smart city implementation, considering five real districts in the southern area of Madrid, Spain. This analysis allowed to assess the potential benefits of the implementation of a real smart city programme, and showed how the proposed smart city energy model could be used for the planning of pilot projects. To the best of our knowledge, such a smart city energy model and modelling framework had not been developed and applied yet, and no economic results in terms of the potential benefits of such a smart city initiative had been previously reported.QC 20171010</p

Energy Management in Smart Cities

Models and simulators have been widely used in urban contexts for many decades. The drawback of most current models is that they are normally designed for specific objectives, so the elements considered are limited and they do not take into account the potential synergies between related systems. The necessity of a framework to model complex smart city systems with a comprehensive smart city model has been remarked by many authors. Therefore, this PhD thesis presents: i) a general conceptual framework for the modelling of energy related activities in smart cities, based on determining the spheres of influence and intervention areas within the city, and on identifying agents and potential synergies among systems, and ii) the development of a holistic energy model of a smart city for the assessment of different courses of action, given its geo-location, regulatory and technical constraints, and current energy markets. This involves the creation of an optimization model that permits the optimal planning and operation of energy resources within the city. In addition, several analyses were carried out to explore different hypothesis for the smart city energy model, including: a)      an assessment of the importance of including network thermal constraints in the planning and operation of DER systems at a low voltage distribution level, b)      an analysis of aggregator’s market modelling approaches and the impact on prices due to DER aggregation levels, and c)      an analysis of synergies between different systems in a smart city context. Some of the main findings are: It is sensible to not consider network thermal constraints in the planning of DER systems. Results showed that the benefit decrement of considering network constraints was approximatively equivalent to the cost of reinforcing the network when necessary after planning without considering network constraints. The level of aggregation affects the planning and overall benefits of DER systems. Also, price-maker approaches could be more appropriate for the planning and operation of energy resources for medium to large aggregation sizes, but could be unnecessary for small sizes, with low expected impact on the market price. Synergies between different energy systems exist in an interconnected smart city context. Results showed that the overall benefits of a joint management of systems were greater than those of the independently managed systems. Lastly, the smart city energy model was applied to a case study simulating a real smart city implementation, considering five real districts in the southern area of Madrid, Spain. This analysis allowed to assess the potential benefits of the implementation of a real smart city programme, and showed how the proposed smart city energy model could be used for the planning of pilot projects. To the best of our knowledge, such a smart city energy model and modelling framework had not been developed and applied yet, and no economic results in terms of the potential benefits of such a smart city initiative had been previously reported.QC 20171010</p

Energy Management in Smart Cities

Models and simulators have been widely used in urban contexts for many decades. The drawback of most current models is that they are normally designed for specific objectives, so the elements considered are limited and they do not take into account the potential synergies between related systems. The necessity of a framework to model complex smart city systems with a comprehensive smart city model has been remarked by many authors. Therefore, this PhD thesis presents: i) a general conceptual framework for the modelling of energy related activities in smart cities, based on determining the spheres of influence and intervention areas within the city, and on identifying agents and potential synergies among systems, and ii) the development of a holistic energy model of a smart city for the assessment of different courses of action, given its geo-location, regulatory and technical constraints, and current energy markets. This involves the creation of an optimization model that permits the optimal planning and operation of energy resources within the city. In addition, several analyses were carried out to explore different hypothesis for the smart city energy model, including: a)      an assessment of the importance of including network thermal constraints in the planning and operation of DER systems at a low voltage distribution level, b)      an analysis of aggregator’s market modelling approaches and the impact on prices due to DER aggregation levels, and c)      an analysis of synergies between different systems in a smart city context. Some of the main findings are: It is sensible to not consider network thermal constraints in the planning of DER systems. Results showed that the benefit decrement of considering network constraints was approximatively equivalent to the cost of reinforcing the network when necessary after planning without considering network constraints. The level of aggregation affects the planning and overall benefits of DER systems. Also, price-maker approaches could be more appropriate for the planning and operation of energy resources for medium to large aggregation sizes, but could be unnecessary for small sizes, with low expected impact on the market price. Synergies between different energy systems exist in an interconnected smart city context. Results showed that the overall benefits of a joint management of systems were greater than those of the independently managed systems. Lastly, the smart city energy model was applied to a case study simulating a real smart city implementation, considering five real districts in the southern area of Madrid, Spain. This analysis allowed to assess the potential benefits of the implementation of a real smart city programme, and showed how the proposed smart city energy model could be used for the planning of pilot projects. To the best of our knowledge, such a smart city energy model and modelling framework had not been developed and applied yet, and no economic results in terms of the potential benefits of such a smart city initiative had been previously reported.QC 20171010</p

Report : UK TIMES-CGE soft-linking work – review of progress and next steps

This report presents the progress made in the UK TIMES/CGE soft-linking work developed so far. It explains in detail the methodology used in the soft-linking process and presents an example of a soft-linking application, implementing a residential energy efficiency scenario. Both TIMES (energy system model) and CGE (economy-wide model) have been used widely in policy analysis. The rationale behind linking energy systems models with economic models is to include the feedback effects between energy cost and energy service demands. This coupling enables analysis of heterogeneous sectoral dynamics that energy systems models on their own can only approximate with elastic demand. The objectives of the work developed are: • To study the impact of energy efficiency improving policies from different modelling perspectives • To understand the value added from linking different types of models in terms of insights to policy analysis • To understand the benefits for each model from a methodological perspective and potential gains for each model from soft-links • To support the Scottish Government in their own use of the models. Note that the soft-linking exercise developed here is not a complete functioning soft-linking methodology, but an exploratory analysis of different soft-linking approaches and a first attempt in the implementation of a UK TIMES-CGE soft-linking scheme. Therefore, the methodology presented here could be seen as the basis for further developments and future work

Consultation Response: Heating Homes

Response submitted by the Centre for Energy Policy to the Energy Security and Net Zero Select Committee Inquiry on Heating Home