Classification of energy use patterns and multi-objective optimal scheduling of flexible loads in rural households

The significant stochastic volatility of renewable energy makes the regulation of flexible loads important in improving the matching degree of energy supply and demand. Under the background of urbanization, rural China is developing rapidly with an increasingly obvious trend of rural differentiation, resulting in different energy use patterns in different households. To accurately assess the flexibility potential, this study identified the use patterns of typical flexible load equipment based on the data from a field survey in the rural Guanzhong Plain, and classified rural households there accordingly. Giving full consideration to flexible loads, this study built a multi-objective optimal load scheduling model aimed at economic efficiency and user comfort. The non-dominated sorting genetic algorithm (NSGA-II) was applied to solve the proposed multi-objective optimization problem in MATLAB software. Then technique for order preference by similarity to an ideal solution (TOPSIS) method was to make the final decision from the Pareto frontier. According to the results of this study: 1) The usage patterns of washing machines were divided into morning usage pattern (Wm) and the late afternoon usage pattern (Wa). The charging patterns of scooters were classified into evening charging pattern (Ve) and night charging pattern (Vn). The usage patterns of air conditioners included midday usage pattern (ACm) and evening usage pattern (ACe). 2) The Wm-Vn-ACe households show greatest flexibility potential under the Scenario TOU (Time-of-use), the peak-valley difference of load curve is reduced by 22.9% compared with that before the optimal dispatching; The Wa-Vn-ACm households show greatest flexibility potential under the Scenario PVS (Photovoltaic system), the self-consumption increased by 10.7% compared with that before the optimal dispatching.3) Air conditioner usage patterns had a significant impact on the flexibility potential.