Presented By: Industrial & Operations Engineering
IOE 899 Seminar Series: Ruiwei Jiang, University of Michigan
Distributionally Robust Co-Optimization of Power Dispatch and Do-Not-Exceed Limits
The IOE 899 Seminar Series is open to all. U-M Industrial and Operations Engineering graduate students and faculty are especially encouraged to attend.
The seminar will be followed by a reception in the IOE Commons (Room 1709) from 4:00 pm-5:00 pm.
Title: Distributionally Robust Co-Optimization of Power Dispatch and Do-Not-Exceed Limits
Abstract:
To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears challenging to compute DNE limits that simultaneously maintain the system flexibility and incorporate a large portion of the available renewable energy at the minimum cost. In addition, it is often challenging to accurately estimate the joint probability distribution of the renewable energy. In this paper, we propose a two-stage distributionally robust optimization model that co-optimizes the power dispatch and the DNE limits, by adopting an affinely adjustable power re-dispatch and an adjustable joint chance constraint that measures the renewable utilization. Notably, this model admits a second-order conic reformulation that can be efficiently solved by the commercial solvers (e.g., MOSEK). We conduct case studies based on large-size test instances to demonstrate the effectiveness of the proposed approach and analyze the trade-off among the system flexibility, the renewable utilization, and the dispatch cost.
Bio:
Biosketch: Ruiwei Jiang is an Assistant Professor of Industrial & Operations Engineering in the University of Michigan. He conducts research on the theory of stochastic and robust optimization, integer programming, and their applications on power systems and healthcare operations. The recognition of his research includes an NSF Career Award and an INFORMS Junior Faculty Interest Group paper award (honorable mention).
The seminar will be followed by a reception in the IOE Commons (Room 1709) from 4:00 pm-5:00 pm.
Title: Distributionally Robust Co-Optimization of Power Dispatch and Do-Not-Exceed Limits
Abstract:
To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears challenging to compute DNE limits that simultaneously maintain the system flexibility and incorporate a large portion of the available renewable energy at the minimum cost. In addition, it is often challenging to accurately estimate the joint probability distribution of the renewable energy. In this paper, we propose a two-stage distributionally robust optimization model that co-optimizes the power dispatch and the DNE limits, by adopting an affinely adjustable power re-dispatch and an adjustable joint chance constraint that measures the renewable utilization. Notably, this model admits a second-order conic reformulation that can be efficiently solved by the commercial solvers (e.g., MOSEK). We conduct case studies based on large-size test instances to demonstrate the effectiveness of the proposed approach and analyze the trade-off among the system flexibility, the renewable utilization, and the dispatch cost.
Bio:
Biosketch: Ruiwei Jiang is an Assistant Professor of Industrial & Operations Engineering in the University of Michigan. He conducts research on the theory of stochastic and robust optimization, integer programming, and their applications on power systems and healthcare operations. The recognition of his research includes an NSF Career Award and an INFORMS Junior Faculty Interest Group paper award (honorable mention).
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