Smart contract platforms have the potential to allow shared automatic control of energy transfer within networks in a replicable, secure, verifiable and trustworthy way. Here we present a general form of smart contract which captures the elements needed for shared control that will help formalize decentralization. Two mechanisms were defined for agreement of control instructions for a medium-voltage direct-current (MVDC) link connecting two separately operated 33 kV distribution networks. These were instantiated as smart contracts and were evaluated in terms of cost and the computational requirements for their execution. Real network and converter data from the ANGLE-DC demonstration project were used to model the MVDC link. We demonstrate that using smart contracts to agree control instructions between different parties is feasible. The potential for shared control using smart contracts gives operators and regulators a way of defining and decentralizing operating responsibilities within energy systems.
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Information about the code used in this research, including how to access it, can be found in the Cardiff University data catalogue at https://doi.org/10.17035/d.2018.0064088749.
Information about the modelled power network cost data used in this research, including how to access it, can be found in the Cardiff University data catalogue at https://doi.org/10.17035/d.2018.0064088749. The modelled power network cost data, allowing the results to be recreated, are also provided as Supplementary Data. Underlying electricity network data is the property of Scottish Power Energy Networks and is not available via Cardiff University.
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This research was conducted with the support of the EPSRC HubNet: ‘Blockchain based smart contracts for peer to peer energy trading using the GB smart metering system’ (EP/N030028/1), EPSRC ENCORE ‘Feasibility of applying Blockchain and smart contracts technology to distribution grid management in the GB power system’ (EP/N010019/1), and EPSRC Reconfigurable Distribution Networks project (EP/K036327/1). The researchers would like to acknowledge and thank the funders. The authors acknowledge and thank Scottish Power Energy Networks, who provided the data needed for this research. Finally, the authors thank K. Rucinska for her review and improvement of the Abstract.
The modelled power network cost data