TY - JOUR
T1 - An Optimal Primary Frequency Control Based on Adaptive Dynamic Programming for Islanded Modernized Microgrids
AU - Davari, Masoud
AU - Gao, Weinan
AU - Jiang, Zhong Ping
AU - Lewis, Frank L.
N1 - Funding Information:
Manuscript received December 5, 2019; revised March 4, 2020; accepted April 21, 2020. Date of publication June 3, 2020; date of current version July 2, 2021. This article was recommended for publication by Associate Editor S. Dadras and Editor Q. Zhao upon evaluation of the reviewers’ comments. This work was supported by the U.S. National Science Foundation (NSF) awards through the Core Program of Energy, Power, Control, and Networks in the Division of Electrical, Communications and Cyber Systems (ECCS) under Grant #1808279, Grant #1902787, and Grant #1903781. (Corresponding author: Weinan Gao.) Masoud Davari and Weinan Gao are with the Department of Electrical and Computer Engineering, Allen E. Paulson College of Engineering and Computing, Georgia Southern University (Statesboro Campus), Statesboro, GA 30460 USA (e-mail: mdavari@georgiasouthern.edu; wgao@georgiasouthern.edu).
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2021/7
Y1 - 2021/7
N2 - In many pilot research and development (RD) microgrid projects, engine-based generators are employed in their power systems, either generating electrical energy or being mixed with the heat and power technology. One of the critical tasks of such engine-based generation units is the frequency regulation in the islanded mode of modernized microgrid (MMG) operation; MMGs are microgrids equipped with advanced controls to address more emerging scenarios in smart grids. For having a stable and reliable MMG, we need to synthesize an optimal, robust, primary frequency controller for the islanded mode of MMG of the future. This task is challenging because of unknown mechanical parameters, occurrence of uncertain disturbances, uncertainty of loads, operating point variations, and the appearance of engine delays, and hence nonminimum phase dynamics. This article presents an innovative primary frequency control for the engine generators regulating the frequency of an islanded MMG in the context of smart grids. The proposed approach is based on an adaptive optimal output-feedback control algorithm using adaptive dynamic programming (ADP). The convergence of algorithms, along with the stability analysis of the closed-loop system, is also shown in this article. Finally, as experimental validation, hardware-in-the-loop (HIL) test results are provided in order to examine the effectiveness of the proposed methodology practically. Note to Practitioners - This article was motivated by the problem of primary frequency controls in modernized microgrids (MMGs) using engine generators, which are still one of the prime sources of regulating frequency in pilot research and development (RD) microgrid projects. Although MMGs will be integral parts of the smart grid of the future, their primary controls in the islanded mode are not advanced enough and not considering existing theoretical challenges scientifically. Existing approaches to regulate frequency using industrially accepted methods are highly model-based and not optimal. Besides, they are not considering the nonminimum phase dynamics. These dynamics are mainly associated with the engine delays - an inherent issue of mechanical parts - for islanded microgrids. This article suggests a new adaptive optimal output-feedback control approach based on the adaptive dynamic programming (ADP) to the abovementioned problem under consideration. By using the proposed methodology, MMGs can deal with the issues mentioned earlier, which are challenging. The proposed approach is optimally rejecting uncertain disturbances (considering the load uncertainty and operating point variations) and reducing the impacts of nonminimum phase dynamics caused by the engine delay. Based on our currently available hardware-in-the-loop (HIL) device's capability of modeling power systems' components in real time, our HIL-based experiments demonstrate that this approach is feasible.
AB - In many pilot research and development (RD) microgrid projects, engine-based generators are employed in their power systems, either generating electrical energy or being mixed with the heat and power technology. One of the critical tasks of such engine-based generation units is the frequency regulation in the islanded mode of modernized microgrid (MMG) operation; MMGs are microgrids equipped with advanced controls to address more emerging scenarios in smart grids. For having a stable and reliable MMG, we need to synthesize an optimal, robust, primary frequency controller for the islanded mode of MMG of the future. This task is challenging because of unknown mechanical parameters, occurrence of uncertain disturbances, uncertainty of loads, operating point variations, and the appearance of engine delays, and hence nonminimum phase dynamics. This article presents an innovative primary frequency control for the engine generators regulating the frequency of an islanded MMG in the context of smart grids. The proposed approach is based on an adaptive optimal output-feedback control algorithm using adaptive dynamic programming (ADP). The convergence of algorithms, along with the stability analysis of the closed-loop system, is also shown in this article. Finally, as experimental validation, hardware-in-the-loop (HIL) test results are provided in order to examine the effectiveness of the proposed methodology practically. Note to Practitioners - This article was motivated by the problem of primary frequency controls in modernized microgrids (MMGs) using engine generators, which are still one of the prime sources of regulating frequency in pilot research and development (RD) microgrid projects. Although MMGs will be integral parts of the smart grid of the future, their primary controls in the islanded mode are not advanced enough and not considering existing theoretical challenges scientifically. Existing approaches to regulate frequency using industrially accepted methods are highly model-based and not optimal. Besides, they are not considering the nonminimum phase dynamics. These dynamics are mainly associated with the engine delays - an inherent issue of mechanical parts - for islanded microgrids. This article suggests a new adaptive optimal output-feedback control approach based on the adaptive dynamic programming (ADP) to the abovementioned problem under consideration. By using the proposed methodology, MMGs can deal with the issues mentioned earlier, which are challenging. The proposed approach is optimally rejecting uncertain disturbances (considering the load uncertainty and operating point variations) and reducing the impacts of nonminimum phase dynamics caused by the engine delay. Based on our currently available hardware-in-the-loop (HIL) device's capability of modeling power systems' components in real time, our HIL-based experiments demonstrate that this approach is feasible.
KW - Adaptive dynamic programming (ADP)
KW - coupled dynamics
KW - engine delay
KW - hardware-in-the-loop (HIL) islanded mode of modernized microgrids (MMGs)
KW - nonminimum phase zero dynamics
KW - output-feedback control
KW - primary frequency control
KW - smart modernized grids
KW - uncertain
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U2 - 10.1109/TASE.2020.2996160
DO - 10.1109/TASE.2020.2996160
M3 - Article
AN - SCOPUS:85102228235
VL - 18
SP - 1109
EP - 1121
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
SN - 1545-5955
IS - 3
M1 - 9107341
ER -