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

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-...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) Vol. 64; no. 5; pp. 4110 - 4120
Main Authors: Qinglai Wei, Derong Liu, Lewis, Frank L., Yu Liu, Jie Zhang
Format: Journal Article
Language:English
Published: New York IEEE 01.05.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive control
Adaptive critic designs
adaptive dynamic programming (ADP)
Algorithms
approximate dynamic programming
Batteries
Control theory
Distributed generation
Dynamic programming
Electric rates
Electricity pricing
Energy management
Iterative algorithms
Iterative methods
Microgrids
mixed iteration
Optimal control
Performance analysis
Performance indices
policy iteration
Residential energy
smart grid
value iteration
ISSN:0278-0046, 1557-9948
Online Access:Get full text
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Summary: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.
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ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2017.2650872