首页|An inertial neurodynamic algorithm for collaborative time-varying energy management for energy internet containing distributed energy resources
An inertial neurodynamic algorithm for collaborative time-varying energy management for energy internet containing distributed energy resources
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Elsevier
This paper investigates the energy management of an Energy Internet (EI) that integrates multiple energy networks. Based on the structure of EI and the fluctuation of load, an optimal energy management model considering part of the load as time-varying factor is proposed. Under the influence of load, the actual energy management problem (EMP) is formulated as a time-varying optimization problem subject to a set of global and local constraints. Its optimal solution varies continuously with time, which leads to difficulties in obtaining optimal solutions by conventional algorithms. Consequently, to obtain better tracking performance, this paper proposes a distributed inertial projection neurodynamics algorithm (DIPNA) based on the Nesterov accelerated gradient descent method. This algorithm tracks the optimal solution of the EMP with a fast convergence rate O(1/t~2), providing a referenceable active power for each energy unit in real time. Finally, the performance evaluation results demonstrated the effectiveness and fast convergence of the proposed algorithm.
Energy managementEnergy internetInertial neurodynamicsTime-varyingConvergence rate
Gui Zhao、Xing He、Chaojie Li
展开 >
Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China
The department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, China
NETL
NSTL
Elsevier
