Advertisement

A Multidimensional Analysis of Smart Energy Systems: Towards Developing a Common Framework for Assessing the Sustainability of Small-Scale Renewables in Selected Societal Sectors

  • Peter GuddeEmail author
  • Justine Oakes
  • Nic Bury
  • Peter Cochrane
  • Nicholas Caldwell
Conference paper
  • 6 Downloads

Abstract

The UK power sector is migrating from an old centralised network of large, mainly fossil-fuel-based generating stations towards a more dynamic energy ecosystem with new entrants generating and actively managing their consumption. This is occurring at a time when electricity system participants are searching for solutions to tackle three criticalities known as the “energy trilemma”: de-carbonising, securing long-term supply resilience and affordability. The wider context is that energy is a fundamental part of UK society. The inability to access clean, reliable sources of affordable energy is a barrier to securing development which is sustainable. However, there is limited published research which takes a comprehensive approach to assessing whether the impact of changes to the UK power system are contributing to sustainable development. This research is therefore focused on an evaluation of sustainability through the investment decisions of stakeholders in respect of solar photovoltaics (solar PV) and other Distributed Energy Resources, in the UK context. This research considers the “sustainability impact” within three sectors: the public, private and third sectors. Relevant metrics and benchmarks will be considered against the UN Sustainable Development Goals (UNSDGs) whilst also exploring the “real” value to society.

Keywords

Smart energy systems Sustainability Assessment framework Stakeholders 

Introduction

In the last decade renewable generation technologies have experienced rapid uptake by new entrants onto the UK power network. This has primarily been driven by national decarbonisation policies and tariff-based instruments supporting small-scale generation. The market has continued to mature, and UK Government has now taken the step to remove state-sponsored support for new solar photovoltaic (solar PV) from April 2019, except for a small number of pre-registered schemes.

There are now over one million low and zero carbon power stations connected to the UK electricity grid, with solar PV accounting for 13 GW of installed capacity (BEIS, 2019). This compares to total UK generating capacity at around 106 GW (Statista, 2019) producing 339 TWh in 2017 (BEIS, 2018).

Moving towards a more diverse, decentralised model of power generation is seen by many as part of a smarter, technology-based solution. However, such Distributed Energy Resources on their own create problems which network operators and the sector more generally are trying to manage. The system must transform if it is to become sustainable (Fig. 1).
Fig. 1

Comparing the features of the current power system and a more sustainable model

Some commentators (Table 1) consider that current UK Government policies are not addressing the energy trilemma: resilience, carbon reduction and affordability. “Each pillar of [this] trilemma is important—ignoring any one will result in failure across the system”, (Royal Academy of Engineering, 2015, p. 9).
Table 1

Example of comments on the energy trilemma

Energy trilemma

Commentary

Resilience

The Royal Academy of Engineering’s report to the Council of Science and Technology commented because of a combination of factors the UK power system “in the absence of intervention, would reduce the capacity margin during the time frame considered by this report, in a manner that would present an increasing risk to security of supply” (Royal Academy of Engineering, 2015, p. 2)

Carbon reduction

Latest evidence from the IPCC stated the need to decarbonise at a far faster rate than the UK or other countries are achieving. Committee on Climate Change (2019) concluded that, “Globally, current pledges of effort do not go far enough.” (CCC, 2019, p. 16)

Affordability

The level of investment required to upgrade the transmission network alone was estimated in 2012 at around £8.8 Billion (Electricity Networks Strategy Group, 2012). The current highly regulated model is creating inertia at national infrastructure level. This is highlighted by the recent announcements from the commercial developers to abandon two planned nuclear power projects in the UK (The Guardian Online, 2019). Similar issues are evident at distribution network level

This is all at a time when established UK energy companies are losing market share to new entrants (Ofgem, 2018) and the sector experiences declining public trust (Competition and Markets Authority, 2014). However, the energy trilemma is only part of a broader set of issues and a failure to account for these could undermine the securing of a smarter UK energy system.

This research has yet to identify a model which takes a multi-stakeholder perspective, sustainability-led approach to managing change in the UK energy system. A new assessment model is, therefore, required to ensure that policy and investment decisions move towards sustainable energy provision whilst embracing the implications for all stakeholders. It is important to ensure that optimal decisions are made throughout the network to secure a sustainable future for the UK.

Preparatory Review: Measuring Sustainable Development

The commonly used definition of Sustainable Development adopted by the United Nations is “Development which meets the needs of the present without compromising the ability of future generations to meet their own needs” (UN World Commission on Environment and Development, 1987). The UN General Assembly subsequently adopted 17 Sustainable Development Goals (SDGs) for achievement by 2030 (UN, 2015), summarised in Fig. 2.
Fig. 2

UN sustainable development goals (United Nations, 2019)

The UN has derived 169 targets from these goals against which each national signatory is required to report its progress towards their achievement. In its 2018 report, the UK Stakeholders for Sustainable Development identified 143 of the targets as being relevant to the UK. The UK Government, through the Office of National Statistics, reports national progress against the relevant targets (ONS, 2019).

Currently, there are a wide range of tools and methods to assess progress towards some or all the factors considered part of Sustainable Development (Table 2).
Table 2

A summary of selected performance measurement tools linking the power system to the UN SDGs

Theme

Methodology

Summary

Sustainability indexes

The World Energy Council’s Energy Trilemma Index tool (2019)

Index ranking countries on their ability to provide sustainable energy through three dimensions: Energy security, Energy equity (accessibility and affordability), Environmental Sustainability

Environmental Sustainability Index (Yale and Columbia Universities, 2019) in collaboration with the World Economic Forum and the EU Joint Research Centre

Published through the Socioeconomic Data and Applications Center (SEDAC), the index provides a composite profile of national environmental stewardship based on a compilation of indicators derived from underlying datasets

Environmental/

ecological impact

Life cycle assessment or analysis

A process of evaluating the environmental impacts of a product at each stage of its life

Ecological foot printing

Defined as the amount of land and resources required to sustain a way of living. Examples include: The Natural Step Framework (2019), Global Footprint Network (2019) and World Wide Fund for Nature (2019)

Environmental Impact Assessment methodology within—UK Town and Country Planning

A statutory tool applied when major decisions are being considered within the UK planning system

The UK Building Research Establishment Environmental Assessment Model (BRE, 2019)

A method for calculating the sustainability of a masterplan, development or individual building

Green accounting methodologies

An approach for defining financial value to non-financial (environmental and social) factors to aid business decision-making. An example of this is the tool described by Stanojevića, VranešaI, and Gökalp (2010)

Economic impact

Return on Investment, Internal Rate of Return and Net Present Value, Pay back

An established suite of financial and economic metrics to predict and assess the performance of a proposal from an investment perspective at organisational level

Gross Value Added, Gross Domestic Product as examples

Another established suite of established metrics, in this case, applied at regional or nation state level to measure economic growth

Whole-life costing

A financial evaluation of a range of capital and revenue costs throughout the life of a project, product or service from raw material production to end of life

Levelised cost of energy

A method for comparing the financial competitiveness of a various energy generating technologies. Similar conceptually to payback, it calculates the minimum cost per unit of energy to recover the capital outlay and running costs

Marginal abatement cost (MAC) curves

MAC curves provide an economic estimate of abatement measures such as Greenhouse Gas emissions reduction technologies compared to Business as Usual. They can operate at various scales, an example being at the global in models developed by Mckinsey (2007) as well as being used in policy modelling by UK Government

Social impact

Social Return on Investment

These include work by the SROI Network (2012) based on material originally by published by UK Government Cabinet Office in 2008

Community Energy project assessment

An Excel-based tool published by Community Energy England to help a community groups considering energy projects to be able to measure and assess the benefits that they bring to their community and to the planet (O’Leary & Speciale, 2017)

Various GIS-based modelling tools

Various tools (academic and commercial) using spatially defined data sets to map patterns or features at various geographical scales with a range of functionalities

Nilsson, Griggs, Visbeck, and Ringler (2016) demonstrated the value of developing an integrated approach to measuring progress towards achieving the SDGs. In so doing, a key challenge of managing policy and delivery at global, national and institutional level across a range of policy agendas with often diverging time-horizons was highlighted,

The aspirations of the 2030 Agenda are far reaching, and many will only be achieved in the long term (possibly beyond 2030). And leveraging policies on positive interactions may have longer pay back times and require longer planning horizons than one-goal approaches … A barrier is that much of today’s governmental actions are coloured by short-termism.” (Nilsson, 2016, pp. 23–24)

Research Aims and Methods

By looking at how investment decisions are being made in organisations within three societal sectors (the public, private and third sectors) who are participating in a new and potentially disruptive ways, this research will consider the following questions:
  1. (a)

    What drives stakeholders to invest in renewable energy technologies like solar PV?

     
  2. (b)

    How do we measure the “sustainability” impact of renewable energy deployment?

     
  3. (c)

    What are the resulting synergies, conflicts and trade-offs across the key Sustainable Development themes?

     
  4. (d)

    How do stakeholders beyond those who are making the investment decisions influence technology deployment—do they benefit or lose out and in what ways?

     
The following pre-curser questions will also be considered:
  1. (e)

    What assumptions are being made?

     
  2. (f)

    What outcomes or scenarios should be considered based on these assumptions?

     
  3. (g)

    If the UN SDGs are inappropriate, what are the alternatives at sub-nation state level?

     
A multidimensional view of a smarter electricity system is, therefore, needed. This research will consider economic, environmental, social and organisational values and their inter-relationships upstream and downstream to understand how they deliver against both institutional drivers and the UN SDGs. Quantitative and qualitative data from a variety of sources including scientific and grey literature will be considered. It is intended to utilise a range of research methods as a basis for further definition and refinement (Table 3).
Table 3

Data and capture methods

Area

Proposed data and capture methods

Technical

Literature review of performance data for deployed technologies and impact on energy profile

Predicted and actual electricity generation data from the deployed technology

Predicted and actual energy consumption from the selected organisations

Economic

Literature review of the economics of the deployed technology

Analysis of supply chain costs and energy market costs

Environmental

Use of published industry, site and network-generated data along the supply chain

Analysis of the impact on greenhouse gas emissions

Assessment against a range of possible scenarios (e.g. National Grid Futures)

Social

Literature review of the health on stakeholders up and downstream

Collection and evaluation of perceptions of key stakeholder groups

Research Results

Preparatory research shows that defining the impact of change in the energy system using the conventional energy trilemma model does not provide confidence that a sustainable approach will be followed (Fig. 3). It is proposed, therefore, to develop a framework to assess and measure the performance of energy-related interventions against defined sustainable development criteria. It is anticipated that any ensuing model or tool will require spatial and time-variable functionality.
Fig. 3

Factors affecting investment decisions in the UK Energy System

Initial research suggests that although the SDGs provide a comprehensive platform, there is very little available published material to show how the SDGs and the relevant targets can be linked to institutional activity in the UK, more specifically to the changing nature of the power system and investment decisions made by new entrants investing in renewable generation.

Building on the work of Nilsson et al. (2016), the International Council for Science (ICSU, 2017) explored the interlinkages between and within some of the SDGs to evaluate an initial set of four SDGs. When applied to the aspects model in Fig. 3, this causal and functional relationship framework helps to show how positive or negative feedbacks could be measured, for example, between ownership (Economic aspect), energy affordability and stakeholder behaviours (Social aspects) in the context of small-scale renewable energy generation. However, although the methodology for scoring put forward by Nilsson et al. may be appropriate for this research, it will be necessary to translate the intent of the SDGs to see if they apply to the UK institutional sectors that will be evaluated.

Discussion

The mind map shown in Fig. 3 indicates that there are significant factors that require consideration as we transition towards a smarter energy system. Initial research suggests that the focus on the energy trilemma fails to consider the impact of deploying Distributed Energy Resources upstream or downstream of the UK energy system.

Currently, the energy industry takes a predominantly investment and shareholder return-led approach based on technical solutions operating within a complex regulatory environment. Government policy and the way that the principal power sector participants behave, for example, have been shown to contribute to higher than expected customer costs and slower technology deployment to deal with the energy trilemma (Helm, 2017, pp. xi–xiii).

Scientific research has tended to take a single aspect or dimensional approach whether within the disciplines of engineering, economics or behavioural science. Examples include Wolsink (2012), Blazqueza, Bracamontesa, Bollinob, and Nezamuddina (2018), and Shove and Walker (2014). Espinoza, Samaniego, Jara-Alvear, and Ochoa (2017) considered the interface between the technology and the citizen to explore the possibility of a “power ecosystem”.

This suggests that in order to understand the impact on society and key stakeholders of a smarter energy system, we must first model the various scenarios and be able to measure the system’s total value taking account of all aspects, weighted according to their relative importance to each stakeholder. From this, we can then derive an understanding of the relative values in time and space from each stakeholder perspective. This means that we need to understand how to compare aspects which may exhibit quite different quantitative and qualitative characteristics at different spatial and temporal scales.

The initial literature research undertaken to date has highlighted that it is necessary to broaden the viewpoint of stakeholders in a rapidly expanding and complex part of the UK’s key infrastructure. For example, it is important to have a comprehensive dialogue with all those involved from system design through to investors, operators and consumers. Currently, there are few shared commonalities of understanding.

Conclusions and Future Work

So far, this research has established that the energy trilemma provides a narrow basis on which to assess the value of deploying renewable energy technologies like solar PV. The current power system demonstrates significant policy, regulatory and financial inertial forces. These inertial forces hamper progress to the ideal system state shown in Fig. 1.

There are a wide range of tools and methods available to model the impact of change (Table 2) which are applicable to specific aspects of the energy system. Although there is common agreement amongst the key participants who perform the energy policy, regulatory and operational functions in the UK that change is needed to address the energy trilemma, there is a lack of an effective mechanism, including an agreed and shared model, to assess the impact of change in the power sector at different scales and across time. Exploring a Geographical Information System (GIS) based approach, among others, could have significant merit given the need to manage and model spatial information.

The model presented at Fig. 3 indicates that there are at least forty factors that could play a part when an organisation is planning to make an investment decision affecting their interaction with the energy system, whether that is installing solar PV on a single building or making decisions that affect national infrastructure. At this time, no framework has been identified which looks at the relative importance of these aspects from different stakeholder perspectives to derive an optimal investment position.

Furthermore, there is a gap between how nations, using the UN Sustainable Development Goals as the basis and individual organisations using a range of environmental, social and economic metrics, set and track progress to achieving sustainability.

The proposed research will, therefore, aim to verify these initial conclusions and, if shown to be valid, will try to put forward a model to address the gap that this initial analysis suggests.

References

  1. BEIS. (2018). Digest of UK Energy Statistics (DUKES) 2018—Chapter 5: Electricity. BEIS. Retrieved April 27, 2019, from assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/736152/Ch5.pdf.
  2. BEIS. (2019). Solar photovoltaics deployment in the UK. BEIS. Retrieved March 31, 2019, from www.gov.uk/government/statistics/solar-photovoltaics-deployment.
  3. Blazqueza, J., Bracamontesa, F., Bollinob, C., & Nezamuddina, N. (2018). The renewable energy policy paradox. Renewable and Sustainable Energy Reviews, 82(1), 1–5.CrossRefGoogle Scholar
  4. Building Research Establishment. (2019). The Building Research Establishment Environmental Assessment Method. Building Research Establishment. Retrieved May 2, 2019, from www.breeam.com/.
  5. Committee on Climate Change. (2019). Net Zero—The UK’s contribution to stopping global warming. Retrieved May 2, 2019, from www.theccc.org.uk/wp-content/uploads/2019/05/Net-Zero-The-UKs-contribution-to-stopping-global-warming.pdf.
  6. Competition and Markets Authority. (2014). Energy market investigation. Competition and Markets Authority. Retrieved June 14, 2018, from www.gov.uk/cma-cases/energy-market-investigation#final-report.
  7. Electricity Networks Strategy Group. (2012). Our electricity transmission network: A vision for 2020—A Summary of an Updated Report to the Electricity Networks Strategy Group, URN 11D/955. Retrieved May 2, 2019, from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/48275/4264-ensg-summary.pdf.
  8. Espinoza, J. L., Samaniego, E., Jara-Alvear, J., & Ochoa, T. D. (2017). Smart grids: A multi-scale framework of analysis. Industrial Electronics (ISIE), IEEE 26th International Symposium.Google Scholar
  9. Global Footprint Network. (2019). Retrieved May 2, 2019, from www.footprintnetwork.org/our-work/ecological-footprint/.
  10. Helm, D. (2017). Cost of Energy Review, Department for Business, Energy & Industrial Strategy. Retrieved June 17, 2019, from www.gov.uk/government/publications/cost-of-energy-independent-review.
  11. International Council for Science. (2017). A guide to SDG interactions: from science to implementation. International Council for Science. pp. 18–30. Retrieved June 17, 2019, from https://council.science/cms/2017/05/SDGs-Guide-to-Interactions.pdf.
  12. McKinsey. (2007). A cost curve for greenhouse gas reduction. Retrieved May 4, 2019, from www.mckinsey.com/business-functions/sustainability/our-insights/a-cost-curve-for-greenhouse-gas-reduction.
  13. Nilsson, M. (2016). Understanding and mapping important interactions among SDGs—Background paper for Expert meeting in preparation for HLPF 2017. Readying institutions and policies for integrated approaches to implementation of the 2030 Agenda, Vienna.Google Scholar
  14. Nilsson, M., Griggs, D., Visbeck, M., & Ringler, C. (2016). A draft framework for understanding the SDG interactions, ICSU Working Paper. Paris: International Council for Science.Google Scholar
  15. O’Leary, A., & Speciale, G. (2017). Monitoring and evaluating community energy: Reviewing existing tools and outlining a pilot standardised tool. Retrieved May 10, 2018, from www.pureleapfrog.org/monitoring-and-evaluation.
  16. Office of National Statistics. (2019). UK data for Sustainable Development Goal Indicators. Office of National Statistics. Retrieved April 25, 2019, from https://sustainabledevelopment-uk.github.io/.
  17. Ofgem. (2018). Electricity supply market shares by company: Domestic, GB, Ofgem. Retrieved June 13, 2018, from www.ofgem.gov.uk/data-portal/electricity-supply-market-shares-company-domestic-gb.
  18. Royal Academy of Engineering. (2015). A critical time for UK energy policy what must be done now to deliver the UK’s future energy system—A report for the Council for Science and Technology. Royal Academy of Engineering. Retrieved May 2, 2019, from www.raeng.org.uk/publications/reports/a-critical-time-for-uk-energy-policy.
  19. Shove, E., & Walker, G. (2014). What is energy for? Social Practice and Energy Demand, Theory, Culture and Society, 31, 41–58.Google Scholar
  20. Stanojevića, M., VranešaI, S., & Gökalp, I. (2010). Green accounting for greener energy. Renewable and Sustainable Energy Reviews, 14(9), 2473–2491.CrossRefGoogle Scholar
  21. Statista. (2019). Total electricity generation capacity projections of major power producers in the United Kingdom (UK) from 2018 to 2035 (in Gigawatt), Statista. Retrieved April 27, 2019, from www.statista.com/statistics/496283/total-electricity-generation-capacity-uk/.
  22. The Guardian Online. (2019). Hitachi scraps £16bn nuclear power station in Wales. Retrieved April 27, 2019 from www.theguardian.com/business/2019/jan/17/hitachi-set-to-scrap-16bn-nuclear-project-anglesey-wales.
  23. The Natural Step. (2019). Retrieved May 2, 2019, from https://thenaturalstep.org/.
  24. The SROI Network. (2012). A guide to Social Return on Investment. Retrieved May 1, 2019, from www.socialvalueuk.org/app/uploads/2016/03/The%20Guide%20to%20Social%20Return%20on%20Investment%202015.pdf.
  25. UN World Commission on Environment and Development. (1987). Report of the World Commission on Environment and Development: Our Common Future, United Nations. Retrieved May 2, 2019, from www.un-documents.net/wced-ocf.htm.
  26. United Nations. (2015). Resolution adopted by the General Assembly on 25 September 2015, 70/1.Transforming our world: the 2030 Agenda for Sustainable Development, 70th Session 21st October 2015, United Nations. Retrieved May 9, 2019, from www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_RES_70_1_E.pdf.
  27. United Nations. (2019). Sustainable Development Goals, United Nations. Retrieved April 29, 2019, from www.un.org/sustainabledevelopment/sustainable-development-goals/.
  28. United Nations World Commission on Environment and Development. (1987). Our Common future A/42/427, United Nations. Retrieved April 29, 2019, from www.un-documents.net/wced-ocf.htm.
  29. Wolsink, M. (2012). The research agenda on social acceptance of distributed generation in smart grids: Renewable as common pool resources. Renewable and Sustainable Energy Reviews, 16, 822–835.CrossRefGoogle Scholar
  30. World Energy Council. (2019). Energy Trilemma Index. World Energy Council. Retrieved May 2, 2019, from https://trilemma.worldenergy.org/#!/energy-index.
  31. Worldwide Fund for Nature. (2019). Ecological foot printing—A measure of sustainability. Worldwide Fund for Nature. Retrieved May 2, 2019, from wwf.panda.org/knowledge_hub/teacher_resources/webfieldtrips/ecological_balance/eco_footprint/.
  32. Yale University. (2019). Environmental Performance Index Global metrics for the environment. Yale University. Retrieved April 21, 2019, from https://epi.envirocenter.yale.edu/.

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Peter Gudde
    • 1
    • 2
    Email author
  • Justine Oakes
    • 2
  • Nic Bury
    • 1
    • 2
  • Peter Cochrane
    • 1
  • Nicholas Caldwell
    • 1
  1. 1.School of Science, Technology and EngineeringUniversity of SuffolkIpswichUK
  2. 2.Suffolk Sustainability InstituteUniversity of SuffolkIpswichUK

Personalised recommendations