Grid-connected microgrid participation in frequency-regulation markets via hierarchical coordination

The large integration of renewable energy into the power grid requires frequency regulation and ancillary services support. Grid-connected microgrids, which naturally include a portfolio of distributed energy resources and flexible loads, are a promising tool that can provide this utility by adapting their tie-line power to track frequency regulation signals. In this paper, we propose a framework by which grid-connected microgrids can participate in a frequency-regulation market and respond to a frequency-regulation request by leveraging their distributed energy resources and loads. The proposed framework is hierarchical, with a central and lower layers focusing on a microgrid. The central layer solves an energy dispatch problem that aims to match the tie-line power to the reference signal from the Regional Transmission Organization (RTO). The lower layer post-adjusts the optimum of the central layer through distributed optimization with consideration of the power flow constraints and uncertain loads in the microgrid. The framework combines recent progress on distributed algorithms, optimal power flow solvers, and regulation market in a novel way. Simulations demonstrate the effectiveness of the proposed framework.

[1]  Lin Zhao,et al.  A unified Stochastic Hybrid System approach to aggregated load modeling for demand response , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[2]  A. David,et al.  Strategic bidding in competitive electricity markets: a literature survey , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[3]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[4]  Georgios B. Giannakis,et al.  Distributed Optimal Power Flow for Smart Microgrids , 2012, IEEE Transactions on Smart Grid.

[5]  K. Mani Chandy,et al.  Inverter VAR control for distribution systems with renewables , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[6]  Jonathan Donadee,et al.  Stochastic Optimization of Grid to Vehicle Frequency Regulation Capacity Bids , 2014, IEEE Transactions on Smart Grid.

[7]  E. Maasland,et al.  Auction Theory , 2021, Springer Texts in Business and Economics.

[8]  Christoforos N. Hadjicostis,et al.  A Distributed Generation Control Architecture for Islanded AC Microgrids , 2015, IEEE Transactions on Control Systems Technology.

[9]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[10]  Duncan S. Callaway,et al.  State Estimation and Control of Electric Loads to Manage Real-Time Energy Imbalance , 2013, IEEE Transactions on Power Systems.

[11]  Sonia Martínez,et al.  A scheduled-asynchronous distributed optimization algorithm for the optimal power flow problem , 2017, 2017 American Control Conference (ACC).

[12]  Babak Hassibi,et al.  Equivalent Relaxations of Optimal Power Flow , 2014, IEEE Transactions on Automatic Control.

[13]  Michael Kintner-Meyer Regulatory Policy and Markets for Energy Storage in North America , 2014, Proceedings of the IEEE.