A Data-Driven Approach for Blockchain-Based Smart Grid System
| Autor: | Hao Tang, Weiwei Miao, Zeng Zeng, Zhang Mingming, Meiya Dong |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
blockchain
Mathematical optimization Blockchain General Computer Science Computer science 020209 energy 020208 electrical & electronic engineering General Engineering P2P trading Smart grid 02 engineering and technology LEM TK1-9971 Data-driven Power (physics) Matrix decomposition Mean absolute percentage error ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 0202 electrical engineering electronic engineering information engineering General Materials Science Energy market Electrical engineering. Electronics. Nuclear engineering Integer programming |
| Zdroj: | IEEE Access, Vol 9, Pp 70061-70070 (2021) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2021.3076746 |
| Popis: | The smart grid is emerging as a future paradigm for power networks. While it has many successful applications, peer-to-peer trading in the local energy market (LEM) is still challenging due to the lack of security and trading mechanisms. In this paper, we design a data-driven, secure, and smart solution $DS^{2}$ to address this problem. We first propose a five-layer design of LEM based on blockchain. We then model peer-to-peer trading in LEM as a cost minimization problem and derive an efficient online solution leveraging matrix factorization and integer linear programming. $DS^{2}$ is implemented and evaluated on a private Ethereum blockchain. We show that $DS^{2}$ achieves a mean absolute percentage error (MAPE) of 12.8% compared with the offline optimal method through extensive simulations on the real-world dataset. |
| Databáze: | OpenAIRE |
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