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

28 Citations (Scopus)

Abstract

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
Volume123
Early online date13 Jul 2020
DOIs
Publication statusPublished - 1 Dec 2020

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