A stochastic optimal control solution to the energy management of a microgrid with storage and renewables

Abstract

The presence of renewable energy generators in a microgrid calls for the usage of storage units so as to smooth the variability in energy production. This work addresses the optimal management of a battery in a microgrid including a wind turbine facility. A Markov chain model is employed to predict the wind power production and the optimal management of the energy storage element is formulated as a stochastic optimal control problem. An approximate dynamic programming approach resting on system abstraction is then proposed for control policy design. Some numerical examples show the effectiveness of the approach

Generalization of h-Convex Stochastic Processes and Some Classical Inequalities

“…In (10), if we take η(u, v) � u − v and h(α) � α, we obtain the convex stochastic process. We observe that, by taking u � v in (10), we get…”

“…ere are various ways to define stochastic monotonicity and convexity for stochastic processes [7], and they are of great importance in optimization, especially in optimal designs, and also useful for numerical approximations when there exist probabilistic quantities in the literature [8]. We also refer [9][10][11][12] for detailed survey about the importance and interesting properties of stochastic models.…”

Jump Linear Quadratic Control for Microgrids with Commercial Loads

“…In [27], a semi-Markov process model was proposed to model photovoltaic (PV) power and a rule-based controller was used to compute average generator and battery power during each scheduling interval. Belloni et al [28], use Markov chains to model uncertainties in the RES generation, and propose a stochastic dynamic programming algorithm to minimize the cost of energy consumption in wind powered µGrids with energy storage system. In [29], a Markov jump process was used to model the stochastic changes in distributed energy storage systems.…”