logo
banner

Journals & Publications

Publications Papers

Papers

Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids
Jul 18, 2017Author:
PrintText Size A A

Title: Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids 

Authors: Wei, QL; Liu, DR; Lewis, FL; Liu, Y; Zhang, J

 Author Full Names: Wei, Qinglai; Liu, Derong; Lewis, Frank L.; Liu, Yu; Zhang, Jie

 Source: IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 64 (5):4110-4120; 10.1109/TIE.2017.2650872 MAY 2017

 Language: English

 Abstract: In this paper, a novel mixed iterative adaptive dynamic programming (ADP) algorithm is developed to solve the optimal battery energy management and control problem in smart residential microgrid systems. Based on the data of the load and electricity rate, two iterations are constructed, which are P-iteration and V-iteration, respectively. The V-iteration is implemented based on value iteration, which aims to obtain the iterative control law sequence in each period. The P-iteration is implemented based on policy iteration, which updates the iterative value function according to the iterative control law sequence. Properties of the developed mixed iterative ADP algorithm are analyzed. It is shown that the iterative value function is monotonically nonincreasing and converges to the solution of the Bellman equation. In each iteration, it is proven that the performance index function is finite under the iterative control law sequence. Finally, numerical results and comparisons are given to illustrate the performance of the developed algorithm.

 ISSN: 0278-0046

 eISSN: 1557-9948

 IDS Number: ES6QM

 Unique ID: WOS:000399674000065

*Click Here to View Full Record