Sensibility and Uncertainties Analysis method dedicated to home energy management problem

This paper focuses on the energy management problem applied to residential sector. The studied optimization problem is defined as the optimal management of production and consumption activities in buildings. A scheduling problem is identified to adjust the energy consumption to both the energy cost and the users' comfort. The optimization procedure of energy management is based on available predictions (weather forecast, users habit, etc.). These predictions are not entirely known data of the optimization problem because of uncertainties. Parametric uncertainties are introduced in the home energy management problem in order to provide robust energy allocation. To improve the taking into account of uncertainties of prediction and the energy management problems, a Sensibility and Uncertainties Analysis method based on the procedure Branch & Bound and the multi-parametric linear programming is proposed. After a description of general principles and main steps, this algorithm is applied to various energy flow management problems in a smart platform. Practical application: The problem of energy management in buildings is described as the optimization problem which is defined to adjust the energy consumption of buildings in order to reach equilibrium between production and consumption on the grid. This home energy management problem has been modeled with a lot of parameters that are uncertain data. This is generally the case in modeling. This is particularly true in the energy management problem because of the high sensitivity of the decision (the energy allocation) to the data. The proposed approach permits to analyze the sensitivity of the solutions according to uncertain parameters. Then the impact of an uncertainty can be analyzed. Each family of solutions can be used to quantify locally the stability of a robust solution over the uncertainties.