Parameter closed-loop optimization for pure electric vehicles: unified design of power system and control parameters

Author(s):  
Junjiang Zhang ◽  
Yang Yang ◽  
Yi Zhou ◽  
Zhong Yang ◽  
Chunyun Fu
Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1623
Author(s):  
Federico Lozano Santamaria ◽  
Sandro Macchietto

Heat exchanger networks subject to fouling are an important example of dynamic systems where performance deteriorates over time. To mitigate fouling and recover performance, cleanings of the exchangers are scheduled and control actions applied. Because of inaccuracy in the models, as well as uncertainty and variability in the operations, both schedule and controls often have to be revised to improve operations or just to ensure feasibility. A closed-loop nonlinear model predictive control (NMPC) approach had been previously developed to simultaneously optimize the cleaning schedule and the flow distribution for refinery preheat trains under fouling, considering their variability. However, the closed-loop scheduling stability of the scheme has not been analyzed. For practical closed-loop (online) scheduling applications, a balance is usually desired between reactivity (ensuring a rapid response to changes in conditions) and stability (avoiding too many large or frequent schedule changes). In this paper, metrics to quantify closed-loop scheduling stability (e.g., changes in task allocation or starting time) are developed and then included in the online optimization procedure. Three alternative formulations to directly include stability considerations in the closed-loop optimization are proposed and applied to two case studies, an illustrative one and an industrial one based on a refinery preheat train. Results demonstrate the applicability of the stability metrics developed and the ability of the closed-loop optimization to exploit trade-offs between stability and performance. For the heat exchanger networks under fouling considered, it is shown that the approach proposed can improve closed-loop schedule stability without significantly compromising the operating cost. The approach presented offers the blueprint for a more general application to closed-loop, model-based optimization of scheduling and control in other processes.


2015 ◽  
Vol 798 ◽  
pp. 261-265
Author(s):  
Miao Yu ◽  
Chao Lu

Identification and control are important problems of power system based on ambient signals. In order to avoid the model error influence of the controller design, a new iterative identification and control method is proposed in this paper. This method can solve model set and controller design of closed-loop power system. First, an uncertain model of power system is established. Then, according to the stability margin of power system, stability theorem is put forward. And then controller design method and the whole algorithm procedure are given. Simulation results show the effective performance of the proposed method based on the four-machine-two-region system.


2014 ◽  
Vol 1070-1072 ◽  
pp. 892-896
Author(s):  
Fu Xia Wu ◽  
Jian Rong Gong ◽  
Jun Xie ◽  
Ying Jun Wu

Power system stabilizer in a power system is a closed-loop controller. The conventional participation factor method just considers the effect of PSS input signal. When the system stress is heavier, it may give misleading results. Based on the participation factor of modal analysis, an integrative participation factor is proposed to determine the optimum PSS location. The integrative participation factor takes into account both the input and control effect of PSS controllers. The case studied in 2-area 4-generator power system power system confirms that the integrative participation factor is more reasonable and effective than the participation factor method.


2004 ◽  
Vol 59 (24) ◽  
pp. 5695-5708 ◽  
Author(s):  
Xiangming Hua ◽  
Sohrab Rohani ◽  
Arthur Jutan

2021 ◽  
Vol 2121 (1) ◽  
pp. 012004
Author(s):  
Weijie Du ◽  
Miao Yu ◽  
Jinglin Li ◽  
Shouzhi Zhang ◽  
Jingxuan Hu

Abstract Identification and control are important problems of closed-loop power system. At present, most studies are separate identification methods. This paper studies an online and real-time integrated identification method, which can solve the problems of model set and controller design of closed-loop power system. This paper investigates a new iterative identification algorithm and its convergence problem of closed-loop power system based on ambient signals. Firstly, the whole algorithm procedure is given. This algorithm uses the iterative process under the closed-loop condition, which combines system model identification with controller design. Then the complementary of model identification and control design has been realized. Secondly, because of the dynamic performance of the iterative identification algorithm, it has characteristics described from the perspective of a partitioned dynamic system. Regard each iterative identification step as a state node. In this situation, the algorithm guarantees all the state nodes converge to the Lyapunov stable equilibrium. Finally, the simulation results show the correctness and effectiveness of the proposed method through the simulation of a power system with four-machine-two-region.


2018 ◽  
Vol 2 ◽  
pp. 9-16
Author(s):  
A. Al-Ammouri ◽  
◽  
H.A. Al-Ammori ◽  
A.E. Klochan ◽  
A.M. Al-Akhmad ◽  
...  

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