Blockchain-Based and Multi-Layered Electricity Imbalance Settlement Architecture

In the power grid, the Balance Responsible Parties (BRPs) purchase energy based on a forecast of the user consumption. The forecasts are imperfect, and the corrections of their real-time deviations are managed by a System Operator (SO), which charges the BRPs for the procured imbalances. Flexible consumers, associated with a BRP, can be involved in a demand response (DR) program to reduce the imbalance costs. However, running the DR program requires the BRP to invest resources in the infrastructure and increases its operating costs. To limit the intervention of BRP, we implement the DR via a blockchain smart contract. Moreover, to reduce the delay of publication of the imbalance price, caused by the inefficient accounting process of the current balancing markets, a second blockchain is adopted at the SO layer, procuring a fast and auditable credit settlements. The feasibility of the proposed architecture is evaluated over an Ethereum blockchain platform. The results show that block chains can enable a high automation of the balancing market, by providing (i) the implementation of aggregators with low operating cost and (ii) the timely and transparent access to the balancing information, thus fostering new business models for the BRPs.

[1]  F. K. Tuffner,et al.  Using electric vehicles to mitigate imbalance requirements associated with an increased penetration of wind generation , 2011, 2011 IEEE Power and Energy Society General Meeting.

[2]  C. Redl,et al.  Refining Short-Term Electricity Markets to Enhance Flexibility , 2016 .

[3]  Jaap Gordijn,et al.  Agent-Based Electricity Balancing with Distributed Energy Resources,  A Multiperspective Case Study , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[4]  Peter Cappers,et al.  Demand Response for Ancillary Services , 2013, IEEE Transactions on Smart Grid.

[5]  R. V. D. Veen,et al.  The electricity balancing market: Exploring the design challenge , 2016 .

[6]  Andres Ramos,et al.  The impact of European balancing rules on wind power economics and on short-term bidding strategies , 2014 .

[7]  David Menga,et al.  Novel market approach for locally balancing renewable energy production and flexible demand , 2017, 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[8]  Tom Holvoet,et al.  Decentralized coordination of plug-in hybrid vehicles for imbalance reduction in a smart grid , 2011, AAMAS.

[9]  Ildefons Magrans de Abril,et al.  NRGcoin: Virtual currency for trading of renewable energy in smart grids , 2014, International Conference on the European Energy Market.

[10]  Debora Coll-Mayor,et al.  Cryptocurrency as guarantees of origin: Simulating a green certificate market with the Ethereum Blockchain , 2017, 2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE).

[11]  R. A. C. van der Veen,et al.  A comparison of imbalance settlement designs and results of Germany and the Netherlands , 2010 .

[12]  Jonathan Mather,et al.  Blockchains for decentralized optimization of energy resources in microgrid networks , 2017, 2017 IEEE Conference on Control Technology and Applications (CCTA).

[13]  Daniel Davis Wood,et al.  ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER , 2014 .

[14]  K. Bell,et al.  Delivering a highly distributed electricity system: technical, regulatory and policy challenges , 2018 .

[15]  J. Torriti,et al.  A review of the costs and benefits of demand response for electricity in the UK , 2013 .

[16]  Petar Popovski,et al.  Distributed proportional-fairness control in microgrids via blockchain smart contracts , 2017, 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[17]  Mattias Jonsson The business value of demand response for balance responsible parties , 2014 .