scholarly journals Data-Driven Optimization Control for Dynamic Reconfiguration of Distribution Network

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2628 ◽  
Author(s):  
Dechang Yang ◽  
Wenlong Liao ◽  
Yusen Wang ◽  
Keqing Zeng ◽  
Qiuyue Chen ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Distribution Network ◽  
Dynamic Reconfiguration ◽  
Complex Model ◽  
Data Driven ◽  
Optimal Control Strategy ◽  
Current Case ◽  
Optimization Control ◽  
Conventional Methods

To improve the reliability and reduce power loss of distribution network, the dynamic reconfiguration is widely used. It is employed to find an optimal topology for each time interval while satisfying all the physical constraints. Dynamic reconfiguration is a non-deterministic polynomial problem, which is difficult to find the optimal control strategy in a short time. The conventional methods solved complex model of dynamic reconfiguration in different ways, but only local optimal solutions can be found. In this paper, a data-driven optimization control for dynamic reconfiguration of distribution network is proposed. Through two stages that include rough matching and fine matching, the historical cases which are similar to current case are chosen as candidate cases. The optimal control strategy suitable for the current case is selected according to dynamic time warping (DTW) distances which evaluate the similarity between the candidate cases and the current case. The advantage of the proposed approach is that it does not need to solve complex model of dynamic reconfiguration, and only uses historical data to obtain the optimal control strategy for the current case. The cases study shows that the optimization results and the computation time of the proposed approach are superior to conventional methods.

scholarly journals Development of an Optimal Start Control Strategy for a Variable Refrigerant Flow (VRF) System

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 271
Author(s):  
Yusung Lee ◽  
Woohyun Kim
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Predictive Performance ◽  
Building Energy ◽  
Data Driven ◽  
Energy Usage ◽  
Optimal Control Strategy ◽  
Save Energy ◽  
Time Required ◽  
Optimal Control Methods

In this study, an optimal control strategy for the variable refrigerant flow (VRF) system is developed using a data-driven model and on-site data to save the building energy. Three data-based models are developed to improve the on-site applicability. The presented models are used to determine the length of time required to bring each zone from its current temperature to the set point. The existing data are used to evaluate and validated the predictive performance of three data-based models. Experiments are conducted using three outdoor units and eight indoor units on site. The experimental test is performed to validate the performance of proposed optimal control by comparing between conventional and optimal control methods. Then, the ability to save energy wasted for maintaining temperature after temperature reaches the set points is evaluated through the comparison of energy usage. Given these results, 30.5% of energy is saved on average for each outdoor unit and the proposed optimal control strategy makes the zones comfortable.

scholarly journals Research on Optimal Control Strategy for Unpowered Downslope of High-Voltage Inspection Robot Based on Motor Temperature Rise in Complexity Microgrid Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhiyong Yang ◽  
Qiao Fang ◽  
Zihao Zhang ◽  
Xing Liu ◽  
Xianjin Xu ◽  
...  
Keyword(s):  
Optimal Control ◽  
High Voltage ◽  
Temperature Difference ◽  
Temperature Rise ◽  
Control Strategy ◽  
Energy Recovery ◽  
Rear Wheel ◽  
Optimal Control Strategy ◽  
Inspection Robot ◽  
Optimization Control

In order to avoid the motor damage caused by excessive temperature rise of armature winding of the walking motor during braking of high-voltage inspection robot in complexity microgrid networks, an unpowered downhill speed and energy recovery optimization control strategy is proposed based on temperature rise characteristics of the walking motor. Firstly, the thermal equivalent circuit model of the walking motor is established, and the mapping relationship between the armature winding temperature of the walking motor and ambient temperature is solved; secondly, the influence of armature winding temperature on unpowered downhill speed and energy recovery control strategy of robot is analyzed; thirdly, according to the temperature of front and rear wheel walking motors and the temperature difference between them, the optimal control strategy of unpowered downhill speed and energy recovery of robot is put forward; fourthly, by adjusting the duty ratio u of the energy consumption speed control system and the front wheel feedback brake distribution factor λ , the temperature difference between the front and rear wheel walking motors is reduced. Through the experimental analysis on the simulated line, it is verified that the unpowered downhill speed and energy recovery optimization control method based on the temperature rise characteristics of the walking motor can effectively reduce the temperature difference between the front and rear wheels.

Application of Optimal Control Strategy to Converter Gas Recovery System

2012 ◽  
Vol 38 (6) ◽  
pp. 1017 ◽  
Author(s):  
Jia-Yan ZHANG ◽  
Zhong-Hai MA ◽  
Xiao-Bin QIAN ◽  
Shao-Ming LI ◽  
Jia-Hong LANG
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Gas Recovery ◽  
Recovery System ◽  
Converter Gas

Optimal control strategy for cancer remission using combinatorial therapy: A mathematical model-based approach

2021 ◽  
Vol 145 ◽  
pp. 110789
Author(s):  
Parthasakha Das ◽  
Samhita Das ◽  
Pritha Das ◽  
Fathalla A. Rihan ◽  
Muhammet Uzuntarla ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Combinatorial Therapy ◽  
Model Based ◽  
Cancer Remission

scholarly journals Dynamical Analysis and Optimal Control for a SEIR Model Based on Virus Mutation in WSNs

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 929
Author(s):  
Guiyun Liu ◽  
Jieyong Chen ◽  
Zhongwei Liang ◽  
Zhimin Peng ◽  
Junqiang Li
Keyword(s):  
Optimal Control ◽  
Rapid Development ◽  
Hamiltonian Function ◽  
Propagation Model ◽  
Dynamical Analysis ◽  
Optimal Control Strategy ◽  
Epidemic Dynamics ◽  
Optimization Control ◽  
The Cost ◽  
The Pontryagin Maximum Principle

With the rapid development of science and technology, the application of wireless sensor networks (WSNs) is more and more widely. It has been widely concerned by scholars. Viruses are one of the main threats to WSNs. In this paper, based on the principle of epidemic dynamics, we build a SEIR propagation model with the mutated virus in WSNs, where E nodes are infectious and cannot be repaired to S nodes or R nodes. Subsequently, the basic reproduction number R0, the local stability and global stability of the system are analyzed. The cost function and Hamiltonian function are constructed by taking the repair ratio of infected nodes and the repair ratio of mutated infected nodes as optimization control variables. Based on the Pontryagin maximum principle, an optimal control strategy is designed to effectively control the spread of the virus and minimize the total cost. The simulation results show that the model has a guiding significance to curb the spread of mutated virus in WSNs.

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