Adaptive Dynamic Programming Approach for Micro-grid Optimal Energy Transmission Scheduling

Abstract

Micro-grid energy scheduling optimization is a complex nonlinear optimization problem. During the studies, the micro-grid is the low-voltage system whose resistance of the transmission line plays an important role in the system. Difference in traditional micro-grid control scheme, a new control scheme is proposed which the power flow of each transmission line is taken as decision variables, that is to say, the power flow of each line is controlled in order to get the optimal operating cost of micro-grid. Based on the above, in this paper we focus on the micro-grid optimal energy transmission scheduling. It is formulated as a nonlinear quadratic programming problem with quadratic constraints, due to infinite micro-grid operating cycle, it is also an infinite steps optimization problem. Traditional optimal scheduling algorithm is difficult to deal with. Therefore, we propose an adaptive dynamic programing (ADP) algorithm which is effective to solve the infinite steps optimization problem. ADP could avoid meeting the curse of dimensionality caused by the micro-grid optimization, and also has the neural networks which are updated by themselves during applications. By theoretical proof, we obtain an optimal control accuracy and operation efficiency. Finally, numerical simulation results show that the adaptive dynamic programming algorithm has less operating cost and better control scheme compared with the simulated annealing algorithm.