Home Energy Management under Tiered Peak Power Charges
David Pérez-Piñeiro, Sigurd Skogestad, Stephen Boyd
Abstract
We consider the problem of operating a battery in a grid-connected home to minimize electricity cost, which includes an energy charge and a tiered peak power charge based on the average of the $N$ largest daily peak powers over a month. With perfect foresight of loads and prices, the minimum cost can be found by solving a mixed-integer linear program (MILP), which provides a lower bound on achievable cost. We propose a model predictive control (MPC) policy that uses simple forecasts of prices and loads and solves a small MILP at each time step. Numerical experiments on data from a home in Trondheim, Norway, show that the MPC policy achieves a cost within $1.7\%$ of the prescient bound.
