Adaptive Residential Energy Hubs Scheduling Considering Renewable Sources

One of the crucial challenges within the optimal operation of smart cities is coordinated management of multiple energy carriers in the residential buildings owing to disparate and often conflicting objectives. In response to this challenge, this paper proposes a novel conceptual cost-emission-based scheme for optimal energy-gas use in a smart home in the context of residential energy hubs considering a meaningful trade-off between cost saving and environmental protection. Various energy conversion resources containing energy and heat storage systems, rooftop photovoltaic modules, and also combined heat and power units along with responsible electrical and thermal loads are taken into account in the proposed model. Furthermore, an efficient stochastic scenario-based method is executed to tackle the intense uncertainty associated with photovoltaic production. The proposed model reduces domestic energy consumption and utility costs by incorporating a weighted summation mixed objective function under various system constraints and user preferences, while at t the same time optimal task scheduling and comfort for the resident that it can guarantee a good lifestyle. The presented scheme is carried out on a realistic case study equipped with energy hubs and as expected, introduces its applicability and effectiveness in the optimal energy management of the proposed residential energy hub problem. The simulation results confirm that energy procurement costs can be saved by up to 46.16% and emission costs by 34.07% while maintaining the desired level of comfort for the head of the household.