Abstract
This paper determines the optimal capacities of small wind turbine (SWT) and battery energy storage (BES) for a grid-connected household (GCH) with or without an electric vehicle (EV) to minimize the overall cost of electricity (COE). Rule-based home energy management systems (HEMSs) are developed for two different configurations of the GCH: (i) with only SWT, and (ii) with SWT and BES. For each configuration, the HEMSs are developed for two cases: with and without an EV in the premises of the GCH. Uncertainties are also included in the arrival time, departure time, and initial state of charge (at arrival) of the EV. The above technique is then applied to a typical household in South Australia (SA) using the yearly load profile of the household and actual yearly wind speed data at an interval of one hour. To investigate the effects of stochastic nature of household load, EV, and wind power generation on various results, the optimization process is repeated using 10-year of actual wind speed data and probabilistic load and EV uncertainties. The results of several sensitivity analyses of various system parameters are presented. It has been found that the SWT can effectively decrease the COE of the household for both cases (with and without an EV). However, the current price of battery may not be in favor of further reducing the COE of the household.
Original language | English |
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Number of pages | 11 |
Journal | IEEE Transactions on Industrial Informatics |
Early online date | 2022 |
DOIs | |
Publication status | E-pub ahead of print - 2022 |
Keywords
- Batteries
- battery energy storage
- capacity optimization
- cost of electricity
- Costs
- electric vehicle
- energy management system
- Load modeling
- Optimization
- small wind turbine
- Uncertainty
- Wind speed
- Wind turbines