Interval Optimization for Integrated Demand Response in A Battery-Equipped Household Multi-Energy System

The promotion of gas-electric devices and electricity storage devices brings necessity to realize integrated demand response (IDR) for household multi-energy systems (HMES). This paper proposed an interval optimization method for load scheduling in HMES for IDR, which addresses uncertainties in the system model and considers dynamic energy-source switching among gas, electricity and storage. Controllable loads include washing machine, air conditioner and battery as electric devices, and water heater and kitchenware as gas-electric devices. For minimizing energy cost, an interval optimization model with tolerance degree is converted into a deterministic model based on the interval order relationship and interval probability. Then genetic algorithm is applied for solving the deterministic problem. Case studies show that the interval optimization with tolerance method is robust to HMES uncertainty. For a battery-equipped HMES, the energy cost savings are up to 14.7% compared with the traditional method without considering interval optimization and tolerance degree.