# Optimal Bi-Level Scheduling Method of Vehicle-to-Grid and Ancillary Services of Aggregators with Conditional Value-at-Risk

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## Abstract

**:**

## 1. Introduction

- (1)
- The optimisation method has taken into account the risk of loss of revenue due to lack of vehicle charging capacity to provide service and EV battery degradation, and the CVaR was used to mitigate the uncertainties. (CVaR, also known as expected shortfall, was originally used to evaluate the market and credit risk of investment portfolios [22,23]).
- (2)
- A preferred operating point will be suggested within the ancillary capacity, with consideration of the onsite renewable generation and the above risk.

## 2. Bi-Level Scheduling Method for Vehicle-to-Grid and Ancillary Services

#### 2.1. Upper-Level Problem

#### 2.2. Lower-Level Problem

#### 2.3. Uncertainties Study Methodology

#### 2.4. Profit Risk Management of Electric Vehicle (EV) Charging Stations

#### 2.5. The System Adjustment Signal of Aggregator

## 3. Solution to the Bi-Level Problem

## 4. Case Study

#### 4.1. Electricity Spot Price Data

#### 4.2. Application of a BASIC Bi-Level Service Scheduling Method

#### 4.3. Uncertainties of EV Charging Behavior

#### 4.4. The Different Result of Peak Time and Workdays

#### 4.5. Conditional Risk Sensitivity Analysis

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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**Figure 1.**(

**a**) Relationship between preferred operating point and ancillary services capacities (battery power draw); (

**b**) Relationship between preferred operating point and ancillary services capacities (battery power draw).

**Figure 3.**Result of different operating point under 3 different kinds of electric vehicle (EV) in bi-level model.

Symbol | Mean | Standard Deviation | Max | Min |
---|---|---|---|---|

Initial State of Charge (%) | 50 | 20 | 70 | 20 |

Arrive time (h) | 8 | 4 | 14 | 6 |

Departure time (h) | 16 | 4 | 24 | 12 |

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**MDPI and ACS Style**

Wang, Y.; Jia, Z.; Li, J.; Zhang, X.; Zhang, R.
Optimal Bi-Level Scheduling Method of Vehicle-to-Grid and Ancillary Services of Aggregators with Conditional Value-at-Risk. *Energies* **2021**, *14*, 7015.
https://doi.org/10.3390/en14217015

**AMA Style**

Wang Y, Jia Z, Li J, Zhang X, Zhang R.
Optimal Bi-Level Scheduling Method of Vehicle-to-Grid and Ancillary Services of Aggregators with Conditional Value-at-Risk. *Energies*. 2021; 14(21):7015.
https://doi.org/10.3390/en14217015

**Chicago/Turabian Style**

Wang, Yilu, Zixuan Jia, Jianing Li, Xiaoping Zhang, and Ray Zhang.
2021. "Optimal Bi-Level Scheduling Method of Vehicle-to-Grid and Ancillary Services of Aggregators with Conditional Value-at-Risk" *Energies* 14, no. 21: 7015.
https://doi.org/10.3390/en14217015