Table 1.
Summary of literature on DSM techniques for EV integration.
Fig 1.
Example of conventional electricity demand (without data from electric vehicle recharging).
Fig 2.
Conventional load demand (blue) and EV load demand (red).
Fig 3.
Result found at the end of CVF.
Fig 4.
Result of the OVF heuristic.
Fig 5.
Load conservation valley-filling (LCVF) heuristic flowchart.
Fig 6.
Schematic flow of the state storage process in the LCVF algorithm.
Fig 7.
Result of the LCVF heuristic.
Fig 8.
Original (first use-case) scenario: Daily power demands of conventional and electrical vehicle.
Fig 9.
Flexible (second use-case) scenario: Daily power demands of conventional and electrical vehicle.
Fig 10.
Increased EV power demand (third use-case) scenario: Daily power demands of conventional and electrical vehicle.
Fig 11.
8-Hour availability EV power demand (fourth use-case) scenario: Daily power demands of conventional and electrical vehicle.
Fig 12.
24-Hour availability EV power demand (fifth use-case) scenario: Daily power demands of conventional and electrical vehicle.
Fig 13.
Comparison of the results obtained in each scenario between the three techniques.
(a) 1st Use-Case: Original Scenario. (b) 2nd Use-Case: Flexible Scenario. (c) 3rd Use-Case: Increased Consumption. (d) 4th Use-Case: 8-Hour Availability. (e) 5th Use-Case: 24-Hour Availability.
Table 2.
Summary of Shapiro-Wilk—Pc results.
Table 3.
Summary of Kruskal-Wallis—Pc results.
Table 4.
Summary of Dunn test—Pc results.
Fig 14.
Distribution of Pc values of the heuristics in each scenario.
Table 5.
Summary of Shapiro-Wilk—Runtime results.
Table 6.
Summary ANOVA—Runtime results.
Table 7.
Summary of Tukey HSD test—Runtime results.
Fig 15.
Distribution of runtime of the heuristics in each scenario.
Table 8.
Comparative results (in kW) of scenarios and heuristics.