Energy community;
Energy storage;
Robust optimization;
Uncertainty;
MANAGEMENT;
D O I:
10.1016/j.scs.2024.105878
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
Future cities must play a vital role in reducing energy consumption and decarbonizing the electricity sector, thus evolving from passive structures towards more efficient smart cities. This transition can be facilitated by energy communities. This emerging paradigm consists of collectivizing a set of residential installations equipped with onsite renewable generators and storage assets (i.e., prosumers), which can eventually share resources to pursue collective welfare. This paper focuses on cooperative communities, where prosumers share resources without seeking selfish monetary counterparts. Despite their apparent advantages, energy management and scheduling of energy communities suppose a challenge for conventional tools due to the high level of uncertainty (especially due to intermittent renewable generation and random demand), and privacy concerns among prosumers. This paper addresses these issues. Specifically, a novel management structure based on multiple aggregators is proposed. This paradigm preserves users' confidential features while allowing them to extract the full potential of their assets. To efficiently manage the variety of assets available under uncertainty, an adaptive robust day-ahead scheduling model is developed, which casts as a solvable and portable Mixed Integer Linear Programming framework, which eases its implementation in real-world cases. The new proposal concerns uncertain generation and demand using a polyhedral representation of the uncertainty set. A case study is conducted to validate the developed model, showing promising results. Moreover, different results are obtained and analysed. Finally, it is worth remarking on how the level of robustness impacts the collective bill, incrementing it by 75 % when riskaverse conditions are assumed. In addition, the role of storage assets under pessimistic conditions is remarked, pointing out that these assets rule the scheduling plan of the community instead of renewable generators.
机构:
Polytech Porto ISE IPP, GECAD Res Grp Intelligent Engn & Comp Adv Innovat, Rua Dr Almeida 431, P-4200072 Porto, PortugalPolytech Porto ISE IPP, GECAD Res Grp Intelligent Engn & Comp Adv Innovat, Rua Dr Almeida 431, P-4200072 Porto, Portugal
Borges, Nuno
Soares, Joao
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机构:
Polytech Porto ISE IPP, GECAD Res Grp Intelligent Engn & Comp Adv Innovat, Rua Dr Almeida 431, P-4200072 Porto, PortugalPolytech Porto ISE IPP, GECAD Res Grp Intelligent Engn & Comp Adv Innovat, Rua Dr Almeida 431, P-4200072 Porto, Portugal
Soares, Joao
Vale, Zita
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机构:
Polytech Porto ISE IPP, GECAD Res Grp Intelligent Engn & Comp Adv Innovat, Rua Dr Almeida 431, P-4200072 Porto, PortugalPolytech Porto ISE IPP, GECAD Res Grp Intelligent Engn & Comp Adv Innovat, Rua Dr Almeida 431, P-4200072 Porto, Portugal
机构:
Pontifical Catholic Univ Rio de Janeiro, Dept Elect Engn, Rio De Janeiro, BrazilPontifical Catholic Univ Rio de Janeiro, Dept Elect Engn, Rio De Janeiro, Brazil
Rodrigues, Mariana
Street, Alexandre
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机构:
Pontifical Catholic Univ Rio de Janeiro, Dept Elect Engn, Rio De Janeiro, BrazilPontifical Catholic Univ Rio de Janeiro, Dept Elect Engn, Rio De Janeiro, Brazil
Street, Alexandre
Arroyo, Jose M.
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机构:
Univ Castilla La Mancha, Dept Ingn Elect Elect Automat & Comunicac, Ciudad Real, SpainPontifical Catholic Univ Rio de Janeiro, Dept Elect Engn, Rio De Janeiro, Brazil