Continuous Optimal Control Approaches to Microgrid Energy Management

Benjamin Heymann 1, 2 J. Frederic Bonnans 1, 2 Pierre Martinon 1, 2 Francisco Silva 3 Fernando Lanas 4 Guillermo Jimenez 4
1 Commands - Control, Optimization, Models, Methods and Applications for Nonlinear Dynamical Systems
CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique, Inria Saclay - Ile de France, UMA - Unité de Mathématiques Appliquées, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR7641
3 XLIM-DMI - DMI
XLIM - XLIM
Abstract : —We propose a novel method for the microgrid energy management problem by introducing a continuous-time, rolling horizon formulation. The energy management problem is formulated as a deterministic optimal control problem (OCP). We solve (OCP) with two classical approaches: the direct method [1], and Bellman's Dynamic Programming Principle (DPP) [2]. In both cases we use the optimal control toolbox BOCOP [3] for the numerical simulations. For the DPP approach we implement a semi-Lagrangian scheme [4] adapted to handle the optimization of switching times for the on/off modes of the diesel generator. The DPP approach allows for an accurate modeling and is computationally cheap. It finds the global optimum in less than 3 seconds, a CPU time similar to the Mixed Integer Linear Programming (MILP) approach used in [5]. We achieve this performance by introducing a trick based on the Pontryagin Maximum Principle (PMP). The trick increases the computation speed by several orders and also improves the precision of the solution. For validation purposes, simulation are performed using datasets from an actual isolated microgrid located in northern Chile. Results show that DPP method is very well suited for this type of problem when compared with the MILP approach.
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Article dans une revue
Energy Systems, Springer, 2017
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  • HAL Id : hal-01129393, version 2

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Benjamin Heymann, J. Frederic Bonnans, Pierre Martinon, Francisco Silva, Fernando Lanas, et al.. Continuous Optimal Control Approaches to Microgrid Energy Management. Energy Systems, Springer, 2017. 〈hal-01129393v2〉

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