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A project to analyze how much of our mobility energy demand (induced by electric vehicles) we can cover by using only pv installed on our own home.

Python 100.00%

ev_homepv's Introduction

EV-Home-PV

A project to analyze how much of our mobility energy demand (induced by electric vehicles) we can cover by using only pv installed on our own home.

The generated outputs in data/output have the following fields:

  • generated_by_pv: PV generation by segment including kW restriction from E-Car
  • charged_from_pv_unrestricted: PV generation by segment without restriction
  • needed_by_car: Energy demand of car
  • charged_from_pv: PV → car
  • charged_from_outside: Grid → car

All these data are available per timestep.

Scenarios 2 + 3 simulate a charging curve. Thus, there are additional state variables that describe the state of charge for the car (and for scenario 3 a description of the SoC of the battery, marked as S3).

  • kWh_start: Car SoC at the beginning of the segment
  • kWh_end: Car SoC at the end of the segment
  • max_kWh: Maximal charge of the car in kWh (constant)
  • battery_start: State of charge of battery at beginning of segment (S3)
  • battery_end: State of charge of battery at end of segment (S3)
  • battery_used_by_car: Battery → car
  • total_segment_consumption_kWh: Energy that was used by a car in a segment

As a general rule, kWh_start - kWh_end + charged_from_pv + charged_from_outside + min(total_segment_consumption_kWh, max_kWh) == 0. In scenario 3, battery_used_by_car is included in charged_from_pv.

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