Distributed Neuro-Dynamic Optimization for Multi-Objective Power Management Problem in Micro-Grid
Academic Article
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
2019 Elsevier B.V. This paper focuses on a multi-objective power management problem considering demand response in micro grid. The multi-objective problem consists of four conflicting objective functions: the average efficiency function of DG (Diesel Generation) unit, the emission of micro-grid, the dissatisfaction caused by demand response and the total profit function. A single-objective product formulation is applied to convert the multi-objective optimization problem into a single-objective optimization problem. It is shown that the optimal solution of single-objective problem is a pareto optimal point of the original multi-objective problem. Then, using a logarithmic obstacle penalty parameter to deal with the inequality constraint, a distributed neuro-dynamic algorithm is proposed for the aforementioned single-objective optimization problem. Lasalle's invariance principle and Lyapunov function are used to prove that the proposed algorithm can converge to the optimal solution. Finally, the numerical simulation in the micro-grid illustrates the feasibility of the proposed algorithm.
