Evaluation of a Control Strategy for Electric Vehicle Charging : A case study of the monetary gain and peak load reduction of implementing a control strategy for electric vehicle charging at a parking facility

The purpose of this project is to quantitatively evaluate the monetary impact and peak-load reduction of a control strategy (CS) that was applied to an electric vehicle charging system at Uppsala Parkering AB:s parking facility Dansmästaren during a 6 week period. The aforementioned CS aims to reduce electricity costs through an algorithm that reduces power consumption in relation to the current energy cost (spot price) during the hours of 15-24. Ideally, this will shift energy consumption from peak-hours to off-peak hours, as well as alleviate pressure on the power grid by reducing the highest energy consumption spikes. To analyze the efficiency of the CS calculations are made, providing how many hours were successfully moved from peak load hours to off-peak load hours in the grid, and to what extent it has reduced peak loads for Dansmästaren during the active period. To achieve this, the hourly energy consumption data at Dansmästaren is analyzed and reconstructed based on the algorithm to identify the impact of the CS. Furthermore, a sensitivity analysis is conducted, where the hours for which the CS is active, as well parameters for the battery system are modified - investigating how these changes impact the monetary profit and peak load reduction of the CS. The results ultimately show a successful reduction of 8.5% in user pattern dependent energy costs by implementing the CS during the examined period, but that the battery system was under-utilized due to peak-load reduction. Meanwhile, the CS was successful in reducing power consumption peaks by approximately 20%. Additionally, the sensitivity analysis suggests that by changing the active hours of the CS to the peak load hours 06-22, the quantity of power consumption shifted from peak- to off-peak hours could be increased - further reducing transmission fees; although, introducing a higher risk of negatively impacting the consumers due to impaired ability to fast charge electric vehicles during the time the CS is active. Furthermore, by changing parameters for the battery system and considering its technical specifications, it could have been utilized to a significantly greater extent when the CS was active, further reducing the power subscription fee resulting from peak energy consumption. In total, the sensitivity analysis resulted in a reduction of usage-dependent costs by 17.1% compared to the original CS with 8.5% cost reduction.