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Research proves there is power in numbers to reduce electricity bills

31.07.2014

Consumers can save money on their electricity bills and negotiate better deals by joining forces

Consumers can save money on their electricity bills and negotiate better deals by joining forces with similar groups of customers to switch energy suppliers according to new research.

Collective switching or group buying schemes, where thousands of consumers join forces to negotiate cheaper electricity tariffs, are becoming more popular in the UK as bills continue to rise putting increasing pressure on household budgets. Initiatives like Which?'s Big Switch, People Power or the Big Deal have helped thousands of consumers to save, on average, up to a third of their yearly electricity bills.

Now research from Heriot-Watt University and the University of Southampton proves these schemes work and proposes a model to help consumers form more efficient buying groups and minimize switching risks.

A common problem with existing schemes is that one tariff may not be efficient for every consumer. Often they may have been financially better off not switching, or as the research now shows creating a new sub-group which chooses a different tariff.

Speaking at the AAAI Artificial Intelligence conference in Canada this week Dr. Valentin Robu from Heriot-Watt University explains, "Electricity suppliers buy from the wholesale market where electricity prices are considerably lower. There are a number of ways they sell this onto consumers but typically they predict the amount of electricity required and pass on premium prices to consumers to cover any risk associated with over or under buying, allowing them to make profits.

"Crucially, this is where group buying is important. While everyone has potentially some uncertainty about their future consumption, our work shows that, by grouping together, consumers can gain size and market power and reduce their risk and access better prices."

In the new group buying models consumers start with a 'prediction-of-use tariff' which predicts their future consumption using their past data. Based on these patterns, they can then choose to join one of many different types of buyer groups with different tariffs, ranging from:

  • Unpredictable: best suited to a flat tariff, which is identical to existing flat rate supplier tariffs, in which they just pay per unit consumed, irrespective of their prediction
  • Predictable: best suited to a structured tariff where they pay less per unit of power predicted in advance but a higher penalty for over or under consumption

The research has been tested using consumption data from 3,000 UK domestic consumers and techniques from the fields of artificial intelligence and coalition theory to help find the best solution for each household.

Dr. Robu added, "While we now know how to efficiently form buyer groups to reduce each customer's electricity bill, previous research and practice shows customers are often reluctant to switch providers. Even if we can calculate what the most efficient decision would be consumers worry about loss of convenience and uncertainty of the future benefits.

"Our next challenge is to design smarter systems that not only propose the efficient tariff groups, but also "nudge" people towards making the optimal choice for them."

The ultimate aim of the research is to use artificial intelligence to design tools that enable consumers to choose their optimal tariff and allow them to identify other consumers to group with that have an efficient match in terms of their consumption patterns.

###

For more information please contact:

Lynne Veitch
0131 556 0770 or email Lynne.veitch@pagodapr.com

Notes for editors

  • Technical note: The research was performed in collaboration with Dr. Meritxell Vinyals (currently at CEA, the French Centre for Alternative Energies and Atomic Energy in Paris) and Professors Alex Rogers and Nicholas R. Jennings from The University of Southampton. The paper is presented at AAAI, the 28th International Conference for the Advancement of Artificial Intelligence, held in Quebec, Canada. An authors' pre-print of the full paper is available at: http://eprints.soton.ac.uk/364307/ 
  • Collective switching / group buying schemes emerged in Europe, particularly in Belgium and the Netherlands. In the UK the Big Switch estimated an average saving of around £233 per year, while Big Deal estimated £291 per year. 
  • While there is no minimum number to create a collective switching group for the uncertainty reduction effects to be reasonable and to negotiate the best tariffs around 3,000 would be needed to make a scheme viable. The Big Switch attracted 37,000, while the BigDeal attracted 10,000.

About Heriot-Watt University

Heriot-Watt University specialises in science, technology, engineering, business and design, with a particular focus on developing solutions to critical global issues, such as climate change and energy.

Established in 1821, the university has campuses in Edinburgh, the Scottish Borders, Orkney and Dubai, and is investing £35 million in a new campus in Malaysia. http://www.hw.ac.uk

Lynne Veitch | Eurek Alert!

Further reports about: Conference Intelligence Switch artificial electricity techniques

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