Energy cost reduction in residential nanogrid under constraints of renewable energy, customer demand fitness and binary battery operations. (July 2021) - Dahiru, Ahmed Tijjani; Tan, Chee Wei; Bukar, Abba Lawan; Yiew Lau, Kwan
Highlights: Energy cost reduction in a grid connected nanogrid using flexible load shapes. Time-of-use fitness is proposed to offset lower energy cost and customer comfort. The method offers real-time based energy demands and supply availability options. Six operational cases under three photovoltaic/wind/battery configurations. Energy cost reduction achieved by 1.72%, 3.10%, 5.75% and 13.38%, 37.45%, 43.40%. Abstract: Intermittence of renewable energy is a challenge to demand side management in distributed grid technologies. Time-of-use tariffs are often applied to implement traditional strategies such as peak shaving and valley filling that are more functional to conventional grids. Time-of-use tariffs are however not suitable to matching customer demands as the periodic charges are fixed and cannot be match with stochastic renewable power generations. This paper proposes a time-of-use fitness in a grid connected photovoltaic/wind/battery nanogrid for energy cost reduction and maintained customer comforts. The proposed method considers three configurations of the nanogrid optimized using nested integer linear programming. Fitness functions are applied to either critical or flexible demands based on real-time residential consumptions, renewable generation and main grid imported power. Demand criticalities and customer fitness are used in preserving customer comforts. The method achieves 1.72–5.75% and 15.63–21.88% reduction in energy consumption costs against $120.30 and $145.14 flat and conventional time-of-use rates respectively in the nanogrid configurations. Use of battery in binary states of operation, as demand or supply further reduces consumption costs by 13.38–43.40% and 28.20–53.09% against the benchmarks. It is envisaged that better performance of the method can be achieved by multiplying operational scenarios of the battery.