An integrated blockchain-based energy management platform with bilateral trading for microgrid communities. (1st April 2020)

• Record Type: Journal Article
• Authors: van Leeuwen, Gijs; AlSkaif, Tarek; Gibescu, Madeleine; van Sark, Wilfried
• Is Part Of: Applied energy. Volume 263(2020)
• Publication Date: 2020-04-01
• Subjects: Microgrids -- Distributed energy resources -- Decentralized optimization -- Optimal power flow -- Local electricity markets -- Blockchain -- Smart contracts; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.114613
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Optimal power flow and trading are combined in a single optimization problem. A real dataset from a prosumer community in Amsterdam is used. The role of a smart contract as a virtual aggregator is described in a detailed manner. Import cost reductions of up to 34.9% are found for the combined model. The combined model shows 50% reduced peak energy imports. Abstract: In this paper, an integrated blockchain-based energy management platform is proposed that optimizes energy flows in a microgrid whilst implementing a bilateral trading mechanism. Physical constraints in the microgrid are respected by formulating an Optimal Power Flow (OPF) problem, which is combined with a bilateral trading mechanism in a single optimization problem. The Alternating Direction Method of Multipliers (ADMM) is used to decompose the problem to enable distributed optimization and a smart contract is used as a virtual aggregator. This eliminates the need for a third-party coordinating entity. The smart contract fulfills several functions, including distribution of data to all participants and executing part of the ADMM algorithm. The model is run using actual data from a prosumer community in Amsterdam and several scenarios of the model are tested to evaluate the impact of combining physical constraints and trading on social welfare of the community and scheduling of energy flows. The scenario variants are trade-only, where only a trading mechanism is implemented, grid-only where only OPF optimization is implemented and a combined scenario where both are implemented. Results are compared with a baseline scenario. Simulation results show that import costs of the whole community are reduced by 34.9% as compared to a baseline scenario, and total energy import quantities are reduced by 15%. Total social welfare is found to be highest without a trading mechanism, however this platform is only viable when all costs are equally shared between all households. Furthermore, peak imports are reduced by over 50% in scenarios including grid constraints.