With decentralisation and the emergence of local energy communities, the challenge arises in a transactive energy market of maximising the value for all the participants, i.e. the buyers and sellers of electricity and the local network operators whose infrastructure is being used.
The two key elements are the price at which the electricity is sold and bought and the remuneration to the DSO and or TSO for the provision of the network.
The former is relatively straightforward, given a buyer-seller relationship.
As an example, in the UK the independent renewable supplier Good Energy, which sources electricity from small scale independent producers, is known for delivering local tariff schemes to domestic customers.
For example, in 2013 Good Energy was able to offer a ‘Delabole Local’ tariff 20% cheaper than its standard electricity tariff to users living within 2km of the Delabole wind farm.
The latter is more complicated as the network operators generally own or manage infrastructure over a much larger area and their charges are partly if not wholly socialised across all the users in their footprint.
How these charges are established aren’t always transparent. Indeed in Germany, for example, they are said to be completely opaque.
In its peer-to-peer power matching white paper, Open Utility estimated that for a particular large user, the Eden Project in southwest England, the distribution charges could be reduced by up to about 39% or £20,000 with local sourcing of electricity and network charging.
While this would represent a loss to the network operator, in practice local peer-to-peer matching could bring alternative benefits through reduced power flows at higher levels of the network.
For example, UK DNO Western Power Distribution (WPD) has estimated an investment need of £224.5m between 2015 and 2023 to create additional network capacity at voltages above 22kV to manage the anticipated increasing peak demand flows.
With local power matching, this network reinforcement could be avoided or deferred as the power flows and peak demand growth are reduced or delayed.
In addition, the lower flows could help reduce distribution losses.
Modelling suggests that if 10% of demand from LV and HV half hourly metered customers is matched with local generation – leading to a 5% reduction in peak time power flows through the EHV and 132kV network levels – customers in WPD areas could save £1m per year on avoided generation through reduced losses and an additional £0.2m in avoided carbon costs.
All of these figures have to be tested but they are indicative of the potential and the opportunity for building business value in the emerging decentralised market.
Local pricing models
In order to take this concept further, the UK network operator Western Power Distribution has collaborated with Open Utility and others on an investigation of pricing models for local energy markets.
Three models were evaluated with the potential to create value through better local balancing of supply and demand.
In the ‘Network Replicating Private Wires’ model, a generator supplies electricity directly to the consumer via a privately-owned wire. Network and environmental charges and levies are only applicable for the element of demand met through imported supply, thereby providing a price incentive for local matching.
However, there is no signal to locate in areas of network need. The model also has downsides in terms of duplication of DNO network assets, scalability as few businesses can participate and inability of DNOs to plan and manage their networks around them.
This ‘Virtual Private Wire’ model is similar to an NRPW but uses licensed distribution network assets in place of investment in a physical private wire. This model avoids some of the downsides of the NRPW by routing electricity over DNO’s networks, avoiding duplication, providing better transparency and generating revenue for DNOs.
Regulatory changes would be needed to implement a VPW. The netting off of demand and supply is a problem in that policy costs levied on unit prices are then borne by fewer customers.
The final model that was investigated is locational distribution use of system charging, where price signals encouraging local matching are sent through different rates for matched and unmatched demand and supply.
This model has a different target as it allows anyone to participate and benefit, but the lower financial incentive created means a weaker signal to generators and customers to match locally. This means that it requires significant scaling to deliver greatest system value.
Commenting on the findings, James Johnston, CEO of First Utility, told Engerati that each of these models has limitations and there wasn’t a clear winning solution among them.
“Each has pros and cons for different stakeholder groups. Ultimately, it’s about fairness as a model has to be fair to all the parties – the network operator, the participants, and everyone else.”
Stating that other models could be investigated, he says there is ongoing engagement on the findings with WPD as well as with Ofgem and the energy ministry.
With the potential impacts on the various participants in a transactive market, getting the pricing model right is a priority towards which all parties should work.