Three-level day-ahead optimal scheduling framework considering multi-stakeholders in active distribution networks: Up-to-down approach

Jingrui Zhang, Yulu Zhou, Zhuoyun Li and Junfeng Cai

Energy, 2021, vol. 219, issue C

Abstract: Distribution systems are transforming from passive networks to active ones with the development and deployment of renewable energy sources, microgrids (MGs) and virtual plants. Accompanied by the emergence of multiple stakeholders owning personal distributed generators (DGs), energy storage systems and even MGs, the optimal dispatch problem in active distribution networks (ADNs) is challenged. Basing on three-level day-ahead optimal scheduling framework, an up-to-down interaction mechanism is proposed firstly for the optimization in ADNs considering multi-stakeholders. The optimization mechanism starts from DN-layer with minimizing total active power loss of the DN, and then it implements the optimizations of all MGs within the optimizations of all users in the corresponding MG. The optimizing information of connection nodes will be fed back to upper layers in turn and this three-level optimization will be repeatedly implemented until the maximal unbalance power generation returned from all MGs satisfying the convergence condition. Additionally, an elasticity coefficient-based demand response program using time-of-use (TOU) pricing is integrated into the optimizations of MG-layer and User-Layer to guide peak load cutting. Moreover, a power flow rebalancing strategy is also integrated into the MG-layer optimization to accelerate the convergence of the whole solution. Finally, an actual 47-bus distribution system is employed to verify this proposed three-level optimization and the results show the effectiveness and applicability of the proposed method.

Keywords: Three-level optimization; Up-to-down approach; Active distribution network; Day-ahead scheduling; Multi-stakeholders (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:219:y:2021:i:c:s0360544220327626

DOI: 10.1016/j.energy.2020.119655

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