Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium
Abstract
:1. Introduction
1.1. Context
1.2. Literature Overview
- Frequency Containment Reserve (FCR): primary reserve, which is automatically fully activated within a timeframe of 30 s in case of a significant frequency deviation and stabilizes the frequency fluctuations [18].
- Automated Frequency Restoration Reserve (aFRR): secondary reserve, which is automatically fully activated within a timeframe between 30 s and 7.5 min, in order to restore the frequency at the predefined level [19].
- Manual Frequency Restoration Reserve (mFRR): tertiary reserve, which is manually activated on demand within 15 min, in order to restore frequency at the predefined level in case of major imbalances [20].
Automated Frequency Restoration Reserve (aFRR)
- Minimum amount of 1 MW of power for capacity bid and 1 MWh for energy bid [19].
- Pay-as-bid auction principle, where the TSO pays exactly the amount indicated in the elected bid. The problem with this principle is that smaller entities rarely have sufficient resources for efficient continuous market analytics and are simply not able to indicate an up-to-date adequate price [23].
- Expensive specialized metering equipment, which must be installed at every delivery point aiming to provide aFRR services [24].
1.3. Contribution
2. Methodology
2.1. Model
- CRaFRR: power capacity remuneration;
- ERaFRR: energy remuneration.
- aFRRCapacity Bid: aFRR capacity bid (in €/MW/h) for the considered time period (Treserved);
- y: type of EVSE (from 1 to Z) (e.g., uni/bi-directional; AC/DC; EVSE power level);
- Ny: number of EVSE types y participating in the provision of aFRR services;
- Ky: power level of EVSE type y;
- Treserved: reservation time period of the available BSP power capacity;
- Pplug-in: probability that the EVSE type y is going to be plugged into an EV during the reservation time period (Treserved);
- Pfailure: risk factor, indicating the probability that the BSP will fail and be penalized;
- Ffailure: the multiplication factor forming aFRR penalties, which is the factor to be multiplied with the price of the missing MW of power the BSP was not able to deliver;
- PTO: risk factor, indicating the probability of the necessity of opting for the transfer of obligations (TO) service;
- CTO: cost of TO service.
- aFRREnergy Bid: aFRR energy bid (in €/MWh) for the considered time period (Tactivated);
- Tactivated: activation time period of the available BSP power capacity.
- ∆Py: difference in price between uni- and bidirectional EVSE with comparable power level;
- Ly: useful lifetime of EVSE type y;
- m: number of aFRR delivery points (from 1 to N) in the EVSE network;
- Pm: price of specialized aFRR metering equipment;
- Lm: useful lifetime of specialized aFRR metering equipment.
2.2. V2G-Enabled aFRR Use-Case
2.2.1. General Provisions
2.2.2. Coping with Uncertainties for aFRR Capacity Remuneration
2.2.3. Values of the Model Parameters
2.2.4. Design and Assumptions of the Case Study
- (a)
- The costs of TO are defined by the bilateral contracts between the BSPs and are therefore not disclosed. The current study assumes this cost to be 120% of the capacity remuneration, as it is slightly lower than the one that is applicable for penalties.
- (b)
- The average EV battery capacity of the EVs charging at the respective EVSE is 50 kWh.
- (c)
- The provided case study does not include any bidding strategies, assuming all the power capacity bids are to be elected based on the average market price.
2.2.5. Scenarios
- Scenario 1: Natural behavior. The EV user agrees to the fact that his/her EV is going to be used for V2G-enabled aFRR services (or is unaware of this fact), but does not change his/her charging behavior and acts naturally. This scenario is based purely on the historical real-life data of EV charging patterns determining Pplug-in, PTO, and Pfailure. The EV user is not bound by any obligations and is able to unplug the EV at any time. At the same time, the EV user receives no shared revenues from the provision of V2G-enabled aFRR services.
- Scenario 2: Binding contract. The EV users receive binding day-ahead contracts, offering 20% of the aFRR+ capacity revenues for the permission to use their EV batteries for grid-balancing purposes. In this case, the EV would be plugged in and blocked for a period of 6 h, beginning 1 h before the elected CCTU (allowing fpr the user to opt for the TO option in case of emergency) and ending 1 h after the CCTU (ensuring that 100% SOC is reached for the EV after the provision of the service). In case of a violation of contract terms (e.g., not plugging in or unplugging before the contractually defined moments), the EV user pays a penalty equivalent to the penalty the BSP would receive for missing the MW (securing the BSP from losses in case of contract violations). This allows for a the situation where PTO = Pfailure = 0. This can be seen as another risk-mitigation method, cutting out the additional expenses related to uncertainties by sharing 20% of capacity revenues with the EV users.
- Scenario 3: Non-binding contract. The EV users receive non-binding day-ahead contracts, offering 20% of aFRR+ capacity revenues for the permission to use their batteries for grid-balancing purposes. This contract type is a non-binding commercial offering that does not involve any penalties in case the EV user is not plugged-in during the defined period of time. Thus, in the worst case, the violation of the contract terms by the EV user would mean that no remuneration is received. In this scenario, 20% of the contracted users are assumed to violate the non-binding contract on average, creating losses related to TO and penalties for the BSP. This scenario can be seen as another risk-mitigation method, although less efficient than the one described in Scenario 2 in absolute terms for the BSP, but it is also less binding, and thus more attractive for EV users. In this case, the PTO and Pfailure are limited to 20% of their initial value.
3. Results
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Parameter | Symbol | Value | Units | |
---|---|---|---|---|
External data source | EVSE type | y | DC V2G | / |
EVSE power level [27] | Ky | 0.01 | MW | |
Difference between uni- and bidirectional EVSE price [27,28,29,30] | ∆Py | 3000 | € | |
aFRR capacity bid [26] | aFRRCapacity Bid | 65.07 | €/MW/h | |
aFRR energy bid [31] | aFRREnergy Bid | 282.60 | €/MWh | |
CCTU time [19] | Treserved | 4 | H | |
Average activation time per CCTU [32] | Tactivated | 103 | minutes | |
EVSE useful lifetime [15,33] | Ly | 10 | Years | |
Metering equipment cost [34] | Pm | 2000 | € | |
Metering equipment useful lifetime [34] | Lm | 10 | Years | |
Failure factor [19] | Ffailure | 1.3 | / | |
EV charging data | Plug-in probability during CCTU | Pplug-in | [0.136; 0.99] | / |
Probability of failure | Pfailure | [0.009; 0.32] | / | |
Probability of TO | PTO | [0.01; 0.864] | / | |
Assumptions | Cost of TO | CTO | 1.2×Capacity remuneration | € |
EVSE network size | Ny | 250 | Units |
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Share and Cite
Goncearuc, A.; Sapountzoglou, N.; De Cauwer, C.; Coosemans, T.; Messagie, M.; Crispeels, T. Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium. World Electr. Veh. J. 2023, 14, 339. https://doi.org/10.3390/wevj14120339
Goncearuc A, Sapountzoglou N, De Cauwer C, Coosemans T, Messagie M, Crispeels T. Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium. World Electric Vehicle Journal. 2023; 14(12):339. https://doi.org/10.3390/wevj14120339
Chicago/Turabian StyleGoncearuc, Andrei, Nikolaos Sapountzoglou, Cedric De Cauwer, Thierry Coosemans, Maarten Messagie, and Thomas Crispeels. 2023. "Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium" World Electric Vehicle Journal 14, no. 12: 339. https://doi.org/10.3390/wevj14120339
APA StyleGoncearuc, A., Sapountzoglou, N., De Cauwer, C., Coosemans, T., Messagie, M., & Crispeels, T. (2023). Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium. World Electric Vehicle Journal, 14(12), 339. https://doi.org/10.3390/wevj14120339