TY - GEN
T1 - Coordinated Control of Wind Turbine Generator and Energy Storage System for Frequency Regulation under Temporal Logic Specifications
AU - Xu, Zhe
AU - Julius, Agung
AU - Chow, Joe H.
N1 - Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - In this paper, we present a coordinated control method for wind turbine generator and energy storage system for frequency regulation with provable probabilistic guarantees in the stochastic environment of wind power generation. The regulation requirement is specified in the form of metric temporal logic (MTL). We present the stochastic control bisimulation function, which bounds the divergence of the trajectories of the stochastic control system and the diffusionless deterministic control system in a probabilistic fashion. We first design a feedforward controller by solving an optimization problem for the nominal trajectory of the deterministic control system with robustness against initial state variations and stochastic uncertainties. Then we generate a feedback control law from the data of the simulated trajectories. We implement our control method on a four-bus system and test the effectiveness of the method with a generation loss disturbance. We also test the advantage of the feedback controller over the feedforward controller when unexpected disturbance occurs.
AB - In this paper, we present a coordinated control method for wind turbine generator and energy storage system for frequency regulation with provable probabilistic guarantees in the stochastic environment of wind power generation. The regulation requirement is specified in the form of metric temporal logic (MTL). We present the stochastic control bisimulation function, which bounds the divergence of the trajectories of the stochastic control system and the diffusionless deterministic control system in a probabilistic fashion. We first design a feedforward controller by solving an optimization problem for the nominal trajectory of the deterministic control system with robustness against initial state variations and stochastic uncertainties. Then we generate a feedback control law from the data of the simulated trajectories. We implement our control method on a four-bus system and test the effectiveness of the method with a generation loss disturbance. We also test the advantage of the feedback controller over the feedforward controller when unexpected disturbance occurs.
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U2 - 10.23919/ACC.2018.8431710
DO - 10.23919/ACC.2018.8431710
M3 - Conference contribution
AN - SCOPUS:85052581842
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 1580
EP - 1585
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -