Optimal Scenario-based Operation and Scheduling of Residential Energy Hubs Including Plug-in Hybrid Electric Vehicle and Heat Storage System Considering the Uncertainties of Electricity Price and Renewable Distributed Generations

The concept of the residential energy hub (REH) including electrical and thermal energy storage system has been developed as a good scheme for optimizing the residential energy systems. Although the optimal operation of REHs has received a great deal of attention, there is a research gap to propose a stochastic-based optimization model, which simultaneously concerns the uncertainties of renewable energy resources and electricity prices. This article tries to fill such a research gap by introducing a probabilistic scenario-based model that concerns the renewable energy sources' uncertainties as well as electricity price's uncertainties. The proposed scenario-based model for optimization of REH operation cost is validated by the comparison of test results and Monte Carlo simulation (MCS)-based ones. It has been concluded that less than 2% inaccuracy occurs due to the simplifying of the proposed model in comparison with simulation-based models like MCS. Also, the proposed model is compared with other available ones. The study of seasonal heat and power demand changes is one of the most crucial contributions of this paper. Furthermore, test results illustrated that the PHEV and heat storage system could act as appropriate solutions to decrease the operation costs of REH.

Automated summary

The article introduces a probabilistic scenario-based model for optimizing the operation cost of REH, which considers uncertainties of renewable energy sources and electricity prices. The proposed model is validated by test results and compared with Monte Carlo simulation-based models, showing less than 2% inaccuracy. Seasonal heat and power demand changes are studied, and it is found that PHEV and heat storage system can decrease the operation costs of REH.