Coordinated Frequency Control Strategy for Electric Vehicles and Air Conditioners Based on Hierarchical Control Scheme

Author(s):  
Mingchao Xia ◽  
Teng Lu ◽  
Qifang Chen
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.


2014 ◽  
Vol 556-562 ◽  
pp. 1220-1225
Author(s):  
Yan He Zhu ◽  
Lan Ming Guo ◽  
Jie Zhao

The most critical issue of the blanket module remote maintenance operation is to remove or replace the heavy module with high positioning accuracy of 1mm. Located in vacuum vessel (VV) of the nuclear fusion device, the blanket module is weight up to 500kg, thus the grasp and installation of blanket module come to be the essential problem during the maintenance operation. To meet the requirement, we propose a new hierarchical control strategy of rough and fine positioning technology based on combined sensors. The detail procedures and implementation of the control scheme has been carried out successfully on Virtual Robot Experiment Platform to demonstrate the feasibility of the control strategy.


2016 ◽  
Vol 40 (6) ◽  
pp. 497-517 ◽  
Author(s):  
Nour EL Yakine Kouba ◽  
Mohamed Menaa ◽  
Mourad Hasni ◽  
Mohamed Boudour

This article presents the design of a new effective control strategy to enhance frequency stability of an isolated micro-grid-based wind–diesel hybrid system. The suggested control methodology involves load frequency control coordinated with battery energy storage systems. A recently developed meta-heuristic algorithm called multi-verse optimizer was applied to design an intelligent load frequency control scheme in the aim to handle the frequency fluctuation due to load changes and wind farm integration. The multi-verse optimizer algorithm was used to optimize the proportional–integral–derivative controller parameters for the load frequency control loop. The proposed controller was coordinated with two different kinds of storage system, which are redox flow batteries and electric vehicles. To demonstrate the effectiveness of the proposed control strategy, the simulation was performed under step load changes and then was extended with doubly-fed induction generator wind farm integration. Furthermore, to show the potential of multi-verse optimizer algorithm, a comparative study was done with other approaches available in the literature. In addition, robustness analysis was carried out. The obtained simulation results show that the proposed strategy is a very effective means for providing robust load frequency control controller and to avoid hybrid system instability. Furthermore, the system frequency can be improved using an optimal power management of the stored energy in both redox flow batteries and electric vehicles to compensate the load frequency control capability of the diesel groups, which allow to the possibility of integration of a large penetration of wind farms. In summary, the proposed control strategy may be helpful to identify the needed load frequency control capacity in the presence of dispersed generation’s units.


2019 ◽  
Vol 67 (12) ◽  
pp. 1047-1057
Author(s):  
Fabio Molinari ◽  
Aaron Grapentin ◽  
Alexandros Charalampidis ◽  
Jörg Raisch

Abstract This work presents a distributed hierarchical control strategy for fleets of autonomous vehicles cruising on a highway with diverse desired speeds. The goal is to design a control scheme that can be employed in scenarios where only vehicle-to-vehicle communication is available and where vehicles need to negotiate and agree on their positions on the road. To this end, after reaching an agreement on the lane speed with other traffic participants, each vehicle decides whether to keep cruising along the current lane or to move into another one. In the latter case, it negotiates the entry point with others by taking part in a distributed auction. An onboard controller computes an optimal trajectory transferring the vehicle with agreed velocity to the desired lane while avoiding collisions.


2014 ◽  
Vol 687-691 ◽  
pp. 500-503
Author(s):  
Chun Jie Wang ◽  
Le Ge ◽  
Yong Xin Tian

This paper introduces the vector control of permanent magnet synchronous motor (PMSM), and proposes the control strategy according to the characteristics of the electric vehicles. The dynamics equation is obtained based on the analysis of the power system of electric vehicles, and the control scheme for PMSM is proposed. In the environment of MATLAB/SIMULINK software, the model of PMSM vector control and the electric vehicles drive system are established and analyzed.


Author(s):  
Runing Lin ◽  
Baisravan HomChaudhuri ◽  
Pierluigi Pisu

This paper presents a fuel efficient control strategy for a group of connected hybrid electric vehicles (HEVs) in urban road conditions. A hierarchical control architecture is proposed in this paper where the higher level controller is considered to be a part of the transportation infrastructure while the lower level controllers are considered to be present in every HEV. The higher level controller uses model predictive control strategy to evaluate the energy efficient velocity profiles for every vehicle for a given horizon. Each lower level controller then tracks its velocity profile (obtained from the higher level controller) in a fuel efficient fashion using equivalent consumption minimization strategy (ECMS). In this paper, the vehicles are modeled in Autonomie software and the simulation results provided in the paper shows the effectiveness of our proposed control architecture.


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