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Sources Of Risk And Uncertainty In Deploying Smart Grids | Science Trends

Sources Of Risk And Uncertainty In Deploying Smart Grids

Future electricity networks will have to become smarter, but how, and is it a free lunch? “The smart grid” is not a single artifact that can be picked off a shelf. The starting points are unique combinations emerging from historical choices about infrastructure, current generation, the potential for renewables, market structure, network regulation, competition, company incentives, and consumer behavior.

Different networks in different countries will benefit from different levels of smartness since each has developed, and will continue to develop, at its own pace. Furthermore, multiple factors will influence how quickly they can adapt to emergent conditions and new technologies.

Smart energy technology will be in competition with the old “dumb” approaches to strengthening networks by adding copper. In addition, demand will vary depending on local needs. This competition will be shaped by regulatory structures and the degree to which they evolve, the innovation they stimulate, which stakeholders can bring the products of this innovation to market, and how consumers respond. But it won’t happen without recognizing that there are substantive sources of risk giving rise to uncertainties that impact the scale, scope, and timeframe for adopting smart grids.

While some factors may be specific to the UK, many sources of uncertainty will be present in many national and other systems. Our multi-stage methodology of interviews, questionnaires, and workshops identified sources of uncertainty in seven categories, with specific issues within each category as well as cross-cutting issues.

The UK’s Supply Mix has changed considerably since the 1990 privatization, with a shift away from coal towards gas, wind, and solar. The UK is committed to increasing supply from renewables and improving energy efficiency as part of reducing CO2emissions by 80% by 2050. The UK Government’s policy is to drive new nuclear capacity, replacing an aging fleet of reactors largely due for decommissioning by 2030. However, the high cost of nuclear is deterring investors. Planning policy and subsidy cuts are severely limiting new onshore wind deployment and subsidy cuts are already slowing PV installation rates. Meanwhile, expected growth in the use of electric vehicles (EVs) will increase network stress and local load balancing problems, as will a desired uptick in the use of heat pumps for decarbonizing heat demand. What factors will form the smart grid will be shaped by politics, technology, economics, market design and access, and consumer choice among other factors. All of this makes it difficult to know where and when to invest in the grid and where to move to smart or stick with dumb network measures.

The major stakeholder concern was the absence of longevity of policy planning by the government and regulators. There was considerable emphasis on the need for both to act together in taking a consistent approach, with the failure to do so perceived as a major impediment to investment. Some strongly positive initiatives on changing network incentives were widely acknowledged by stakeholders but still identified too often as being piecemeal rather than part of a holistic plan.

Markets as a source of risk concern both current arrangements and those options that might be (dis)allowed by future regulation. The smart energy paradigm sees dynamic pricing (e.g. time of use tariffs), demand shifting, and other changes as integral, but there are many hurdles. Currently, the residential sector has limited potential for demand flexibility, but this may change with large-scale deployment of EVs and heat pumps and other sources of demand and this is seen as having a desirable potential for enhanced systemic flexibility. There is potential for flexibility to emerge inequitably with subsidized EVs, PV, and heat pumps installed by those with sufficient access to capital and then their owners benefitting from low costs as they access lower tariffs, leaving any less flexible user to pay higher costs.

Users of the system — residential, commercial, and industrial consumers — present uncertainty through their reaction to new demand-side approaches, which may dictate limits on options for smart system uptake. Many stakeholders expect industrial and commercial consumers to respond more flexibly than residential consumers but there was a concern as to the limitations placed on system flex if residential consumers opted not to engage.

The generation, capture, and use of large volumes of data and information are central to the potential for smart grids, but stakeholder concerns related to data protection, security, privacy, and public trust. Data volumes will increase over time, potentially enabling functions such as time-of-use tariffs, but this will require infrastructure for smart meters and sufficient data communication and processing capacity and substantial investment.

Network operators respond to regulatory incentives. Their key source of uncertainty is not knowing what generators and consumers will require beyond a five-year timescale, making decisions about investment and incentives difficult. Stakeholders emphasized that business as usual (BAU) was no longer an appropriate approach to network operation. This is problematic; distribution networks have historically made incremental cost savings rather than wholesale changes. One long-term concern was the impact of increasing self-generation of electricity by consumers and the impact this would have on network usage and thus network operator income. A new paradigm for network financing may be needed.

The issues above impact investment conditions. The low-carbon transition requires considerably more investment than BAU which will only be met if investors can see a route to a return based on the increasing risk emerging from the various sources of greater uncertainty.

Conclusion

Smartness as an ongoing process facilitating flexibility, not an endpoint. Many risks emerge from the increasing complexity in enabling the low-carbon transition, with a lack of long-term political and regulatory vision the biggest source of uncertainty and thus risk. Continual coherent planning and action by governments and regulators will be essential in creating the environment for the scale of investment needed to successfully smarten the grid and to minimize the total cost of transition.

Published by Peter Connor and Colin Axon

Renewable Energy, University of Exeter and the Institute of Energy Futures, Brunel University

These findings are described in the article entitled Sources of risk and uncertainty in UK smart grid deployment: An expert stakeholder analysis, recently published in the journal Energy (Energy 161 (2018) 1-9). This work was conducted by P.M. Connor from the University of Exeter, C.J. Axon from Brunel University, D. Xenias from Cardiff University, and N. Balta-Ozkan from Cranfield University.

About The Author

Peter Connor
Dr. Peter Connor is a Senior Lecturer in Renewable Energy Policy at the University of Exeter. Peter researches and teaches in the area of national renewable energy policy and regulation. He has a particular interest in the design and implementation of policy and regulation to support renewable energy sources of electricity and heat within the UK and amongst EU Member States. He is also interested in policy and regulation as it applies to the development of smarter delivery of energy.
Colin Axon

Colin Axon is a senior lecturer and current Chair of the Energy Group of the Institute of Physics. His research is about the use of energy in the urban environment and the limits to natural resources. His main areas of interest are in transport, electricity networks, energy security, resource efficiency, and the application of robust methods for metrics and indicators. He has published more than 80 reviewed articles and technical reports.