4.7 Article

Real-Time Control of Distributed Batteries With Blockchain-Enabled Market Export Commitments

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 13, Issue 1, Pages 579-591

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2021.3121444

Keywords

Batteries; Real-time systems; Renewable energy sources; Production; Optimization; Investment; Degradation; Batteries; blockchain; distributed generation; smart contract; smart grids

Funding

  1. Innovate U.K. Responsive Flexibility (ReFLEX) [104780]
  2. CEDRI project (Community-Scale Energy Demand Reduction in India) [EP/R008655/1]
  3. CESI project (Centre for Energy Systems Integration) [EP/P001173/1]

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This paper proposes a framework for distributed residential battery aggregation, which places bids on wholesale energy markets in real time using a control algorithm. The results show that this approach significantly increases revenues and improves self-consumption for households.
Recent years have seen a surge of interest in distributed residential batteries for households with renewable generation. Yet, assuring battery assets are profitable for their owners requires a complex optimisation of the battery asset and additional revenue sources, such as novel ways to access wholesale energy markets. In this paper, we propose a framework in which wholesale market bids are placed on forward energy markets by an aggregator of distributed residential batteries that are controlled in real time by a novel Home Energy Management System (HEMS) control algorithm to meet the market commitments, while maximising local self-consumption. The proposed framework consists of three stages. In the first stage, an optimal day-ahead or intra-day scheduling of the aggregated storage assets is computed centrally. For the second stage, a bidding strategy is developed for wholesale energy markets. Finally, in the third stage, a novel HEMS real-time control algorithm based on a smart contract allows coordination of residential batteries to meet the market commitments and maximise self-consumption of local production. Using a case study provided by a large U.K.-based energy demonstrator, we apply the framework to an aggregator with 70 residential batteries. Experimental analysis is done using real per minute data for demand and production. Results indicate that the proposed approach increases the aggregator's revenues by 35% compared to a case without residential flexibility, and increases the self-consumption rate of the households by a factor of two. The robustness of the results to uncertainty, forecast errors and to communication latency is also demonstrated.

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