An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response

Under the background of the popularity of household gas-electric equipment, an interval optimization method considering the Integrated Demand Response (IDR) and tolerance degree is proposed to deal with the household load scheduling. The proposed method mainly tackles the dynamic switching of energy forms (natural gas and electricity) and uncertain variables in the system caused by household load and photovoltaic (PV). The thermostatically controllable loads contain gas-electric heater and air conditioning, and the interruptible loads contain gas-electric kitchen stove and clothes washer. An interval optimization model is formulated to optimize the operation cost and emissions of a household multi-energy system. The uncertain parameters are modeled as interval numbers, and the constraints are relaxed by tolerance degree. To solve the equation, the interval optimization model is transformed into a deterministic optimization model based on the interval order relation and interval possibility degree. Then, Genetic Algorithm is applied to solve the deterministic optimization model. Simulation results indicate that interval optimization is robust to the uncertainties and flexible to meet users' demands. Both IDR and tolerance degree are able to optimize users' energy cost, and the optimization results are accumulative. For a gas-electric equipment installed home, the proposed method can reduce expenditures by up to 23.4% compared with traditional method that do not consider IDR, tolerance degree and interval optimization.