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Hierarchical Energy Management of Microgrids including Storage and Demand Response

1
Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2
Faculty of Technology, Policy and Management, Delft University of Technology, 2628 BX Delft, The Netherlands
*
Author to whom correspondence should be addressed.
Energies 2018, 11(5), 1111; https://doi.org/10.3390/en11051111
Received: 6 April 2018 / Revised: 20 April 2018 / Accepted: 27 April 2018 / Published: 1 May 2018
(This article belongs to the Section Energy Storage and Application)
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Abstract

Battery energy storage (BES) and demand response (DR) are considered to be promising technologies to cope with the uncertainty of renewable energy sources (RES) and the load in the microgrid (MG). Considering the distinct prediction accuracies of the RES and load at different timescales, it is essential to incorporate the multi-timescale characteristics of BES and DR in MG energy management. Under this background, a hierarchical energy management framework is put forward for an MG including multi-timescale BES and DR to optimize operation with the uncertainty of RES as well as load. This framework comprises three stages of scheduling: day-ahead scheduling (DAS), hour-ahead scheduling (HAS), and real-time scheduling (RTS). In DAS, a scenario-based stochastic optimization model is established to minimize the expected operating cost of MG, while ensuring its safe operation. The HAS is utilized to bridge DAS and RTS. In RTS, a control strategy is proposed to eliminate the imbalanced power owing to the fluctuations of RES and load. Then, a decomposition-based algorithm is adopted to settle the models in DAS and HAS. Simulation results on a seven-bus MG validate the effectiveness of the proposed methodology. View Full-Text
Keywords: battery energy storage; demand response; microgrid; multi-timescale characteristics; hierarchical energy management; uncertainty battery energy storage; demand response; microgrid; multi-timescale characteristics; hierarchical energy management; uncertainty
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Fan, S.; Ai, Q.; Piao, L. Hierarchical Energy Management of Microgrids including Storage and Demand Response. Energies 2018, 11, 1111.

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