Robust Peak-Shaving for a Neighborhood with Electric Vehicles
Abstract
:1. Introduction
- It only uses a prediction of a single parameter that characterizes the optimal solution, together with a power prediction of the house for the upcoming interval to plan the charging of an electric vehicle in a house.
- A peak at the transformer can be counteracted with low communication overhead using a decision making process that also requires predictions of characteristics that aid at making trade-offs at the neighborhood level.
- A prediction scheme for the required parameters, combined with a sensitivity study that shows that the results do not suffer much from prediction errors.
2. Related Work
2.1. Control-Based DSM
2.2. Planning-Based DSM
2.3. Groups of Electric Vehicles
3. Online Electric Vehicle Planning
3.1. The EV Charging Problem
3.2. Online Optimization
3.3. Predictions
Algorithm 1 Online EV planning for time interval m. |
{needed for } |
if then {needed for } |
end if |
4. Fleet Planning
- The charging of EVs is planned locally within the houses such that the total household consumption power profile (including the EV) becomes as flat as possible.
- When the total power P of a group of houses is above a given threshold of X watts, the EVs are requested to decrease their total charging in the next time interval by in a way that keeps the individual local power profiles as flat as possible for their remaining charging window.
- When the total power P of a group of houses is below a given threshold of Y watts (e.g., PV production peak), the EVs are requested to increase their total charging in the next time interval by in a way that keeps the individual local power profiles as flat as possible for their remaining charging window.
5. Predictions
6. Evaluation
7. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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(kWh) | Max. Power | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Min | Med | Max | Min | Med | Max | Min | Med | Max | Min | Med | Max | ||
6 | 1188 | 1463 | 1713 | 21 | 22 | 24 | 1118 | 1361 | 1584 | 1.20 | 1.00 | 1.07 | 1.16 |
12 | 2188 | 2492 | 2776 | 22 | 24 | 24 | 2118 | 2385 | 2643 | 1.13 | 1.00 | 1.05 | 1.11 |
18 | 3188 | 3492 | 3798 | 24 | 24 | 24 | 3118 | 3388 | 3643 | 1.09 | 1.00 | 1.04 | 1.09 |
24 | 4188 | 4492 | 4798 | 24 | 24 | 24 | 4118 | 4388 | 4643 | 1.07 | 1.00 | 1.03 | 1.07 |
(kWh) | Max. Power | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Min | Med | Max | Min | Med | Max | Min | Med | Max | Min | Med | Max | ||
6 | 809 | 1057 | 1268 | 31 | 35 | 40 | 749 | 969 | 1184 | 1.25 | 1.00 | 1.06 | 1.18 |
12 | 1409 | 1721 | 1962 | 35 | 38 | 40 | 1349 | 1627 | 1851 | 1.18 | 1.00 | 1.06 | 1.15 |
18 | 2009 | 2340 | 2603 | 37 | 39 | 40 | 1949 | 2253 | 2468 | 1.14 | 1.00 | 1.05 | 1.12 |
24 | 2609 | 2943 | 3221 | 39 | 40 | 40 | 2549 | 2859 | 3079 | 1.11 | 1.00 | 1.04 | 1.10 |
PeakS | NC | PS | Coord (This Paper) | NoCoord (This Paper) | |
---|---|---|---|---|---|
Total losses (kWh) | 61.31 | 89.22 | 33.90 | 34.36 | 35.95 |
Lowest voltage (V) | 209.92 | 199.77 | 219.15 | 219.11 | 218.88 |
Highest voltage (V) | 232.28 | 232.28 | 231.51 | 231.51 | 231.51 |
Max. peak (kW) | 171.04 | 575.09 | 175.70 | 170.82 | 195.28 |
Max. cable load (%) | 106.87 | 143.35 | 57.41 | 57.41 | 57.41 |
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Gerards, M.E.T.; Hurink, J.L. Robust Peak-Shaving for a Neighborhood with Electric Vehicles. Energies 2016, 9, 594. https://doi.org/10.3390/en9080594
Gerards MET, Hurink JL. Robust Peak-Shaving for a Neighborhood with Electric Vehicles. Energies. 2016; 9(8):594. https://doi.org/10.3390/en9080594
Chicago/Turabian StyleGerards, Marco E. T., and Johann L. Hurink. 2016. "Robust Peak-Shaving for a Neighborhood with Electric Vehicles" Energies 9, no. 8: 594. https://doi.org/10.3390/en9080594
APA StyleGerards, M. E. T., & Hurink, J. L. (2016). Robust Peak-Shaving for a Neighborhood with Electric Vehicles. Energies, 9(8), 594. https://doi.org/10.3390/en9080594