Abstract
This paper proposes a price-maker bidding and offering model for networked microgrids (NMG) in a pool-based day-ahead electricity market. The objective of this model is to maximize the net revenue of NMG by coordinating the joined individual microgrids to submit aggregated offers/bids to the market operator. A hybrid stochastic-robust optimization framework is developed to offset multiple associated uncertainties. The bidding and offering model is first formulated as a hard-to-solve mixed-integer nonlinear programming (MINLP) problem, which is later converted to its easy-to-solve mixed-integer linear programming (MILP) counterpart. To resolve privacy concerns of each microgrid and improve the scalability of the proposed bidding and offering model, a coordinated scheduling framework for NMG based on the Dantzig-Wolfe decomposition (DWD) method is proposed to obtain the global optimum. Numerical simulations with real-world measured data validate the effectiveness of the proposed price-maker bidding model, which is shown to outperform existing price-taker models.
Original language | English |
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Pages (from-to) | 5201-5211 |
Number of pages | 11 |
Journal | IEEE Transactions on Smart Grid |
Volume | 12 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Nov 2021 |
Externally published | Yes |
Keywords
- Dantzig-Wolfe decomposition
- Day-ahead electricity market
- hybrid stochastic-robust optimization
- networked microgrids
- price-maker
ASJC Scopus subject areas
- General Computer Science