A Novel Hybrid Two-Stage Framework for Flexible Bidding Strategy of Reconfigurable Micro-Grid in Day-Ahead and Real-Time Markets

Mohammad Amin Mirzaei, Mohammad Hemmati, Kazem Zare, Mehdi Abapour, Behnam Mohammadi-Ivatloo, Mousa Marzband, Amjad Anvari-Moghaddam

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)
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Microgrids are going to be used in the future intelligent grids as a promising technology to enable widespread utilization of renewable energy sources in a high-efficient and reliable manners. It is known that reconfiguration of micro-grids, using tie-line and sectionalizing switches, can provide more operational flexibility. Additionally, coordinated scheduling of flexible loads and energy storage systems within a micro-grid can play an important role in the optimal scheduling of micro-grid; thus lowering the costs. This paper proposes an optimal bidding strategy for a micro-grid in day-ahead and real-time markets, based on AC power flow model, considering the hourly reconfiguration of the micro-grids. Fuel cell-based hydrogen energy storage and multiple shiftable loads are considered in the proposed method according to the load’s activity schedule. A reconfigurable micro-grid incorporates energy production and consumption of its local components to trade power in both day-ahead and real-time markets in order to maximize its profit as a private entity. The bidding problem faces issues due to the high level of uncertainties, consisting of wind power generation and electric load as well as variations of market prices. A hybrid two-stage bi-level optimization model is proposed to manage such uncertainties so that wind power, load demand, and day-ahead market prices are handled through scenario-based stochastic programming, and an information gap decision theory is applied to model the uncertainty of real-time market prices under two strategies, namely risk-seeker and risk-averse. The numerical simulation results confirm the effectiveness of the proposed model.
Original languageEnglish
Article number106293
JournalInternational Journal of Electrical Power and Energy Systems
Early online date13 Jul 2020
Publication statusPublished - 1 Dec 2020


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