A hierarchical control scheme for optimal secondary frequency regulation with on-off loads in power networks

Author(s):  
Andreas Kasis ◽  
Stelios Timotheou ◽  
Marios Polycarpou
2019 ◽  
Vol 9 (15) ◽  
pp. 3052
Author(s):  
Jiafu Yin ◽  
Dongmei Zhao

Due to the potential of thermal storage being similar to that of the conventional battery, air conditioning (AC) has gained great popularity for its potential to provide ancillary services and emergency reserves. In order to integrate numerous inverter ACs into secondary frequency control, a hierarchical distributed control framework which incorporates a virtual battery model of inverter AC is developed. A comprehensive derivation of a second-order virtual battery model has been strictly posed to formulate the frequency response characteristics of inverter AC. In the hierarchical control scheme, a modified control performance index is utilized to evaluate the available capacity of traditional regulation generators. A coordinated frequency control strategy is derived to exploit the complementary and advantageous characteristics of regulation generators and aggregated AC. A distributed consensus control strategy is developed to guarantee the fair participation of heterogeneous AC in frequency regulation. The finite-time consensus protocol is introduced to ensure the fast convergence of power tracking and the state-of-charge (SOC) consistency of numerous ACs. The effectiveness of the proposed control strategy is validated by a variety of illustrative examples.


1983 ◽  
Vol 1 (3) ◽  
pp. 167-175 ◽  
Author(s):  
Suguru ARIMOTO ◽  
Fumio MIYAZAKI

2018 ◽  
Vol 9 (4) ◽  
pp. 3213-3223 ◽  
Author(s):  
Evangelos Vrettos ◽  
Emre C. Kara ◽  
Jason MacDonald ◽  
Goran Andersson ◽  
Duncan S. Callaway

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8365
Author(s):  
Yushen Miao ◽  
Tianyi Chen ◽  
Shengrong Bu ◽  
Hao Liang ◽  
Zhu Han

Battery energy storage systems (BESSs) play a critical role in eliminating uncertainties associated with renewable energy generation, to maintain stability and improve flexibility of power networks. In this paper, a BESS is used to provide energy arbitrage (EA) and frequency regulation (FR) services simultaneously to maximize its total revenue within the physical constraints. The EA and FR actions are taken at different timescales. The multitimescale problem is formulated as two nested Markov decision process (MDP) submodels. The problem is a complex decision-making problem with enormous high-dimensional data and uncertainty (e.g., the price of the electricity). Therefore, a novel co-optimization scheme is proposed to handle the multitimescale problem, and also coordinate EA and FR services. A triplet deep deterministic policy gradient with exploration noise decay (TDD–ND) approach is used to obtain the optimal policy at each timescale. Simulations are conducted with real-time electricity prices and regulation signals data from the American PJM regulation market. The simulation results show that the proposed approach performs better than other studied policies in literature.


Robotica ◽  
2018 ◽  
Vol 36 (10) ◽  
pp. 1527-1550 ◽  
Author(s):  
Francesco Pierri ◽  
Giuseppe Muscio ◽  
Fabrizio Caccavale

SUMMARYThis paper addresses the trajectory tracking control problem for a quadrotor aerial vehicle, equipped with a robotic manipulator (aerial manipulator). The controller is organized in two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the upper layer. To the purpose, a model-based control scheme is adopted, where modelling uncertainties are compensated through an adaptive term. The stability of the proposed scheme is proven by resorting to Lyapunov arguments. Finally, a simulation case study is proposed to prove the effectiveness of the approach.


2018 ◽  
Vol 120 (6) ◽  
pp. 2761-2774 ◽  
Author(s):  
Michaela Bruton ◽  
Nicholas O’Dwyer

At face value, the term “synergy” provides a unifying concept within a fractured field that encompasses complementary neural, computational, and behavioral approaches. However, the term is not used synonymously by different researchers but has substantially different meanings depending on the research approach. With so many operational definitions for the one term, it becomes difficult to use as either a descriptive or explanatory concept, yet it remains pervasive and apparently indispensable. Here we provide a summary of different approaches that invoke synergies in a descriptive or explanatory context, summarizing progress, not within the one approach, but across the theoretical landscape. Bernstein’s framework of flexible hierarchical control may provide a unifying framework here, since it can incorporate divergent ideas about synergies. In the current motor control literature, synergy may refer to conceptually different processes that could potentially operate in parallel, across different levels within the same hierarchical control scheme. There is evidence for the concurrent existence of synergies with different features, both “hard-wired” and “soft-wired,” and task independent and task dependent. By providing a comprehensive overview of the multifaceted ideas about synergies, our goal is to move away from the compartmentalization and narrow the focus on one level and promote a broader perspective on the control and coordination of movement.


2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Randall T. Fawcett ◽  
Abhishek Pandala ◽  
Jeeseop Kim ◽  
Kaveh Akbari Hamed

Abstract The primary goal of this paper is to develop a formal foundation to design nonlinear feedback control algorithms that intrinsically couple legged robots with bio-inspired tails for robust locomotion in the presence of external disturbances. We present a hierarchical control scheme in which a high-level and real-time path planner, based on an event-based model predictive control (MPC), computes the optimal motion of the center of mass (COM) and tail trajectories. The MPC framework is developed for an innovative reduced-order linear inverted pendulum (LIP) model that is augmented with the tail dynamics. At the lower level of the control scheme, a nonlinear controller is implemented through the use of quadratic programming (QP) and virtual constraints to force the full-order dynamical model to track the prescribed optimal trajectories of the COM and tail while maintaining feasible ground reaction forces at the leg ends. The potential of the analytical results is numerically verified on a full-order simulation model of a quadrupedal robot augmented with a tail with a total of 20 degrees-of-freedom. The numerical studies demonstrate that the proposed control scheme coupled with the tail dynamics can significantly reduce the effect of external disturbances during quadrupedal locomotion.


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