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Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model

M. Tostado-Véliz, A.R. Jordehi, S.A. Mansouri, F. Jurado

Applied Energy Vol. 328, pp. 120257-1 - 120257-14

Summary:

Energy communities enable effective coordination among prosumers on pursuing collective targets. This paper focuses on isolated 100% renewable communities, involving individual (controllable appliances and small generators) and collective (wind generators and battery banks) assets. To effectively coordinate the agents involved in these structures, advanced energy management strategies are necessary. This work develops a three-stage day-ahead scheduling strategy for isolated 100% energy communities, involving peer-to-peer transactions among prosumers. The different uncertainties involved are incorporated through a novel stochastic-robust formulation, that results in a computationally tractable optimization framework. To validate the new model, a case study on a six-prosumer benchmark community is analysed. Results reveal the importance of collective assets and peer-to-peer exchanges among prosumers as well as the effectiveness of the developed formulation. The role of batteries is also discussed, helping to reduce the total unserved energy and operating cost by 20% and 19%, respectively, as well as enabling a more efficient use of wind energy. The impact of robustness is also studied, incrementing the expected importable energy by 28% compared to the deterministic case, while the exportable energy from prosumers is notably reduced by 40%. However, uncertainty-aware strategies have a direct impact on operational costs, incrementing the expenditures by 37% when uncertainties are considered.


Keywords: Energy community; Energy storage; Peer-to-peer; Renewable energy; Robust optimization; Stochastic programming


JCR Impact Factor and WoS quartile: 11,200 - Q1 (2022)

DOI reference: DOI icon https://doi.org/10.1016/j.apenergy.2022.120257

Published on paper: December 2022.

Published on-line: November 2022.



Citation:
M. Tostado-Véliz, A.R. Jordehi, S.A. Mansouri, F. Jurado, Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model. Applied Energy. Vol. 328, pp. 120257-1 - 120257-14, December 2022. [Online: November 2022]


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