scholarly journals Tie-line Power Adjustment Method Based on Proximal Policy Optimization Algorithm

2021 ◽  
Vol 1754 (1) ◽  
pp. 012229
Author(s):  
Jinxiu Hou ◽  
Zhihong Yu ◽  
Qingping Zheng ◽  
Huating Xu ◽  
Shufang Li
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 156160-156174
Author(s):  
Huating Xu ◽  
Zhihong Yu ◽  
Qingping Zheng ◽  
Jinxiu Hou ◽  
Yawei Wei ◽  
...  

2020 ◽  
Author(s):  
Chuanchao Huang

Abstract In order to realize the coordination and integration optimization of the power system itself, this paper constructed the mathematical model of the hybrid power system and solved the multi-objective optimization problem of the heating system through the optimized particle swarm optimization algorithm. Based on the back-to-back VSC-HVDC grid-connected composite system, this paper studied the integrated control strategy of the device to achieve the simultaneous parallel and tie line currents. At the same time, this paper simplified and improved the proposed disassembly criteria for grid-connected composite devices and integrated them into the grid-connected composite device. In addition, on this basis, the integrated control of the three functions of de-listing, juxtaposition and tie line power adjustment of the same device was further studied. Simulation studies show that the proposed algorithm has certain effects and can provide theoretical reference for subsequent related research.


2015 ◽  
Vol 740 ◽  
pp. 696-701
Author(s):  
Shu Hui Zheng ◽  
Ling Yu Zhang

Considering the inertia weight adjustment problems in the standard particle swarm optimization algorithm, a kind of particle swarm inertia weight adjustment method based on multi-step iteration fitness changes was put forward, and by analyzing if particle optimal fitness values was further optimized after a certain number of iterations, then how to set the inertia weight was determined, which can balance the particle swarm global optimization and local optimization. Simulation results show that the improved algorithm was better than the standard particle swarm optimization algorithm in convergence speed and accuracy of solution.


The paper endeavours to analyse the load frequency control for two area system. In this paper, two areas has been considered in which non-reheated type of turbine in both area are used and whose secondary loop consists a latest controller called 2 degree-of-freedom PID (2-DOF-PID) controller. The parameter of the this controller is been optimized by the latest meta heuristic algorithm also called Moth flame optimization algorithm (MFO) to minimize the deviation in frequency of area and tie-line power respectively. The same processes are repeated with PID controller and Integral controller whose parameters are also optimized by MFO. A comparison is made among the result of these and 2-DOF-PID controller prove its superiority over the other controller for minimizing the deviation which occurs in frequency of the area as well as the tie-line power.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Weiguang Wang ◽  
Hui Li ◽  
Wenjie Zhang ◽  
Shanlin Wei

D2D communication improves the cellular network performance by using proximity-based services between adjacent devices, which considered is an effective way to solve the problem of spectrum scarcity caused by tremendous mobile data traffic. If the cache-enabled users are willing to send the cached file to the requesters, the content delivery traffic can be offloaded through the D2D link. In this paper, we strive to find the maximum energy efficiency of the D2D caching network through the joint optimization of cache policy and content transmit power. Specifically, based on stochastic geometry-aided modeling of the network, we derive the data offloading rate in closed form, which jointly considers the effects of success sensing probability and success transmission probability. According to the data offloading rate, we formulate a joint optimization problem integrating cache policy and transmit power to maximize the system energy efficiency. To solve this problem, we propose two optimization algorithms that the cache policy optimization algorithm based on gradient update and the joint optimization algorithm. The simulation results demonstrate that the joint optimization has twice the superiority in improving the energy efficiency of the D2D caching network compared with other schemes.


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