Probabilistic Optimal Dynamic Planning of Onsite Solar Generation for Residential Energy Hubs

Solar photovoltaic (PV) systems are becoming an indispensable source of energy for residential customers and are contributing to increase the sustainability of energy systems. However, practical methods that can aid customers to make informed decision on installing the PV systems considering their integration with the residential energy system have remained scarce. This paper proposes a probabilistic dynamic planning model for optimizing decisions on installing PV systems for a residential energy hub. In addition to the PV system, residential energy hub integrates combined heat and power (CHP) units and gas boilers to supply the heat and electrical demands. The proposed planning model minimizes the investment cost of PV systems along with the energy cost of energy hub that includes possible PV energy curtailment cost over the planning horizon. The proposed problem also integrates a heat storage system and responsiveness of the heat and electrical demands to the respective gas and electricity prices as additional flexibility to increase the benefits of PV systems for the customers. Two-point estimate method is used to model the uncertainty of PV generation. The proposed method is implemented on a test energy hub for a 10-year planning period to demonstrate features of the proposed method.