# Design of Three Electric Vehicle Charging Tariff Systems to Improve Photovoltaic Self-Consumption

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## Abstract

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## 1. Introduction

- I.
- EV users prefer to charge their vehicles when prices are lower. Therefore, if reduced prices are offered during PV surplus hours, users will adjust their charging times.
- II.
- The resolution in the control of EV charging power considered in this article is ideal.

- The design of indirect control EV charging is based on temporary PV surplus, with the main objective of increasing the SCR of a real PV CSC project.
- A detailed description of the design of three TSs for EV charging, which can be easily replicated and adjusted to any case.

## 2. Case Study

## 3. Proposed Pricing Methods

#### 3.1. Market Tariff Used as Base Tariff

#### 3.2. Tariff System 1

^{®}software 9.13.0.2166757 (R2022b) Update 4. The simulation was performed for each day where EVs were charged during the above-mentioned six months. The EVs considered in the simulation on a given day were processed in the order of original arrival at the charging point. Additionally, since charging system 1 is an indirect control, once the EV had started to charge in the simulation (when the reduced price was offered), the EV was charged at its maximum power until it was fully charged, even though after a while the reduced price was no longer offered. This process was considered to be the most realistic.

^{th}EV) charging is carried out. On the contrary, if the difference does not exceed 7 kW, the variable t is incremented, and the difference is recalculated and compared with the threshold of 7 kW. Whenever diff(t) is greater than 7 kW, it is checked if there is free space at the charging point. If the variable EV_Connected is less than 2, this means that there is space available, and the simulation of the EV(y) charging pattern starts.

_{y}is created. This index represents how many time intervals the EV(y) has been connected to. It is necessary to (i) know how long EV(y) has needed to complete its charge and (ii) consider that a connector of the charging point has been occupied during the time interval t

_{y}. Index t

_{y}increases each time EV(y) spends a sample period charging. The variable EV_rem_en oversees how much energy the EV(y) must consume to complete its charge. These data are known from the registers of the Charge and Parking application. Whenever EV_rem_en is greater than 0, it means that the EV(y) has not yet completed its charge. The variable EV_char_pat records the EV(y) charge pattern, i.e., the energy consumed in each t interval. During an interval, an EV charges the maximum amount of energy. This value is obtained by multiplying the maximum charging power of the EV by the sampling time. In the flow chart, this maximum energy is defined as EV_max_en_SP. Whenever the variable EV_rem_en is greater than EV_max_en_SP, the charge pattern for that interval is the maximum energy that can be charged. After recording in the variable EV_char_pat how much energy has been consumed for that interval, EV_rem_en is updated, as shown in Equation (1). In addition, the fact that a connector has been occupied by that interval is also recorded (Equation (2)).

_{y}is increased by one, and EV(y) continues to be charged. In the last interval before the end of the charge, EV_rem_en is lower than the maximum power it can charge in one interval. Then, the charge pattern for that interval is the amount of remaining energy (EV_rem_en). Next, the variable EV_rem_en becomes 0, and the variable EV_Connected registers one last time that the connector is occupied.

#### 3.3. Tariff System 2

^{th}EV is detected. Depending on the value of the maximum charging power of the EV, a different tariff is offered. Hence, once the maximum charging power of the EV is known, it is classified into one of these three groups: charging power (a) lower than 7 kW, (b) between 7 and 11 kW, and (c) greater than or equal to 11 kW. After classifying the y

^{th}EV within the corresponding group, the difference between the consumption and the PV production at time t (diff(t)) is calculated. If the variable diff(t) exceeds the threshold of the corresponding group, y

^{th}EV charging is carried out. For group a), for EVs with maximum charging power under 7 kW, diff(t) must exceed 3 kW. In group b), for EVs with charging power between 7 kW and 11 kW, diff(t) must exceed 7 kW. And finally, in group c), for EV maximum charging power greater or equal to 11 kW, diff(t) must exceed 11 kW. On the contrary, if the difference does not exceed the corresponding threshold, t is incremented, and the difference is recalculated and compared with the corresponding threshold for each group. Whenever diff(t) is greater than the threshold, the availability of free space at the charging point is checked. If the variable EV_Connected is less than 2, this means that there is space available, and the simulation of the EV(y) charging pattern starts.

#### 3.4. Tariff System 3

^{th}EV is not yet charged, i.e., if EV_rem_en > 0, it is connected. On the other hand, if the y

^{th}EV is already charged, y is updated to 2 to assess the status of the next EV of the day. Before EV connection, it is verified that there is an available slot. If no EV is connected (EV_Connected < 1), the first EV connects on one connector, index y_1 obtains the value of y

^{th}EV (y_1 = y). Conversely, if EV_Connected equals 1, the second EV is connected on the last connector, and index y_2 obtains the value of the y

^{th}EV (y_2 = y), and the charging simulation begins. Finally, when y is greater than Num_EV_Charge, it is checked that all connected EVs are fully charged. If there is an EV connected, it starts being charged.

^{th}EV still has much energy left to complete its charge and there is enough PV energy, the charging is performed at the maximum EV power. Otherwise, y

^{th}EV charging power varies to match the momentary surplus, i.e., diff(t). This is the main property that characterises the third TS. Similarly, in this case, the y

^{th}EV is at the end of its charge and must consume less than EV_max_en_SP, and it is checked if there is enough PV surplus. Then, as before, in the case there is sufficient surplus, the EV is fully charged. On the other hand, if diff(t) is not enough to finish the charge, the EV modifies its charging power to adjust to the PV surplus. Once the charge has been completed for the sampling period t, the simulation starts again from the first phase (connector D), analysing the situation of the next sampling period (t + 1).

- Both EVs still have energy remaining to be charged to their maximum power;
- The EV on connector 1 (y_1) is almost charged and its remaining energy is less than EV_max_en_SP, while the EV on the second connector (y_2) can still be charged to maximum power;
- In contrast to case two, the EV at connector 1 (y_1) still has a considerable amount of charge left, and the EV at connector 2 (y_2) is at the end of its charge;
- Both EVs are at the end of their charge and consume less than EV_max_en_SP.

#### 3.5. Charging Cost Calculation

**Figure 7.**Division of EV consumption between PV surplus and grid. The letters A and E are connectors that link the existing flowchart to the other flowcharts above.

#### 3.6. Self-Consumption Rate Calculation

## 4. Results and Discussion

#### 4.1. Influence of the Three Tariff Systems for One Day in Detail

#### 4.1.1. Day Example to Understand the Phenomenon

#### 4.1.2. Different Characteristic Days Analysis

#### 4.2. Analysis of the Effect of the Three TSs on the SCR over One and Six Months

#### 4.3. Comparison of the SCR Increase in the Three TSs with the Original Charge

#### 4.4. Analysis of the Economic Savings of the Three TS

## 5. Conclusions and Future Works

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 10.**Basic consumption, PV production, and EV consumption under TS1 influence for 19 March 2022.

**Figure 11.**Grid consumption, PV energy surplus, and EV consumption under TS1 influence for 19 March 2022.

**Figure 12.**Basic consumption, PV production, and EV consumption under TS2 influence for 19 March 2022.

**Figure 13.**Grid consumption, PV energy surplus, and EV consumption under TS2 influence for 19 March 2022.

**Figure 14.**Basic consumption. PV production and EV charging consumption under TS3 influence for 19 March 2022.

**Figure 15.**Grid consumption, PV energy surplus, and EV consumption under TS3 influence for 19 March 2022.

**Figure 16.**Charging pattern and charging information under the influence of the three proposed tariffs for 9 February 2022.

**Figure 17.**Charging pattern and charging information under the influence of the three proposed tariffs for 6 April 2022.

**Figure 19.**(

**a**) Percentage of SCRs by ranges for the original charge; (

**b**) percentage of SCRs by ranges with the TS1; (

**c**) percentage of SCRs by ranges with the TS2; (

**d**) percentage of SCRs by ranges with the TS3.

SCR | Charging Price | ||
---|---|---|---|

EV1 | EV2 | ||

Basic consumption | 51.13% | - | - |

Original EV charge | 56.54% | EUR 3.19 | EUR 20.34 |

EV charge with TS1 | 76.32% | EUR 2.18 | EUR 11.38 |

EV charge with TS2 | 77.96% | EUR 1.99 | EUR 10.99 |

EV charge with TS3 | 78.90% | EUR 1.77 | EUR 10.72 |

Month | SCR Values (%) | SCR Increase/Basic Consumption | |||||||
---|---|---|---|---|---|---|---|---|---|

Basic | Original Charge | TS1 | TS2 | TS3 | Original Charge | TS1 | TS2 | TS3 | |

November | 92.09 | 94.20 | 95.07 | 95.54 | 98.01 | 1.2% | 1.8% | 4.3% | 1.2% |

December | 89.90 | 92.04 | 94.10 | 94.10 | 96.71 | 2.4% | 2.4% | 5.3% | 2.4% |

January | 84.42 | 87.58 | 95.27 | 96.51 | 97.73 | 10.4% | 11.8% | 13.3% | 10.4% |

February | 84.41 | 87.51 | 91.16 | 90.96 | 92.98 | 5.6% | 5.3% | 7.6% | 5.6% |

March | 79.87 | 82.43 | 87.90 | 88.07 | 89.32 | 8.4% | 8.5% | 10.3% | 8.4% |

April | 72.25 | 75.47 | 81.66 | 81.08 | 83.77 | 9.0% | 8.3% | 11.9% | 9.0% |

Mean | 83.82 | 86.54 | 90.86 | 91.04 | 93.09 | 6.2% | 6.4% | 8.8% | 6.2% |

Month | Mean Savings w/TS1 | Mean Savings w/TS2 | Mean Savings w/TS3 |
---|---|---|---|

November 2021 | 10% | 13% | 11% |

December 2021 | 14% | 24% | 26% |

January 2022 | 31% | 26% | 27% |

February 2022 | 29% | 23% | 25% |

March 2022 | 30% | 26% | 32% |

April 2022 | 21% | 21% | 30% |

Mean | 22% | 22% | 25% |

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**MDPI and ACS Style**

Etxegarai, G.; Camblong, H.; Ezeiza, A.; Lie, T.T.
Design of Three Electric Vehicle Charging Tariff Systems to Improve Photovoltaic Self-Consumption. *Energies* **2024**, *17*, 1806.
https://doi.org/10.3390/en17081806

**AMA Style**

Etxegarai G, Camblong H, Ezeiza A, Lie TT.
Design of Three Electric Vehicle Charging Tariff Systems to Improve Photovoltaic Self-Consumption. *Energies*. 2024; 17(8):1806.
https://doi.org/10.3390/en17081806

**Chicago/Turabian Style**

Etxegarai, Garazi, Haritza Camblong, Aitzol Ezeiza, and Tek Tjing Lie.
2024. "Design of Three Electric Vehicle Charging Tariff Systems to Improve Photovoltaic Self-Consumption" *Energies* 17, no. 8: 1806.
https://doi.org/10.3390/en17081806