4.7 Article

Novel Flexibility Indices of Controllable Loads in Relation to EV and Rooftop PV

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2022.3146237

Keywords

Smart homes; Load modeling; Indexes; Costs; Electric vehicle charging; Demand side management; Water heating; Controllable load; electric vehicles; flexibility; machine learning; photovoltaics; smart homes

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This study proposed flexibility indices for electric vehicles (EV) and photovoltaics (PV) in smart homes, which can be used by homeowners and policymakers to make flexible choices in installation and updating devices. Different home clusters and charging levels were considered, and sensitivity analysis was conducted. Simulation results showed the effectiveness of the proposed method.
In order to analyze the flexibility of controllable loads in smart homes, two flexibility indices are proposed in this study. The first index, the electric vehicle (EV) flexibility index, determines the ability of any particular controllable load to avoid the EV charging intervals during its operation. The second index, the photovoltaic (PV) flexibility index, evaluates the ability of any controllable load to absorb PV power during its operation. Both these indices can be utilized by homeowners or policymakers in installing/updating PVs and controllable home appliances. Higher index values imply more flexibility and thus those devices are more beneficial for the homeowners. In order to capture different consumption patterns in different homes, five home clusters are considered in this study. In each cluster, the controllable loads are grouped into three groups based on their flexibility level and utilization purpose. The performance of the proposed method is analyzed for the two commonly used charging levels in the residential sector, i.e. level 1 and level 2. In addition, sensitivity analysis of different uncertain factors such as PV power, the arrival time of EVs, and daily mileage of EVs is also carried out. Simulation results have shown the effectiveness of the proposed method in determining the flexibility of different controllable loads with respect to EVs and PV.

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