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Electric vehicles as distributed energy storage for local energy management

Electric vehicles as distributed energy storage for local energy management

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Even though the Li-ion battery price has dropped significantly in recent years, this storage technology is still quite expensive and, in order to avoid overspending, this study proposes using EV's batteries as Battery Energy Storage System. One of the main disadvantages of this scheme is that the total available battery's capacity is variable, but it is dependent on the EV's mobility. In this chapter, an optimization model is developed to minimize the electricity cost purchased from the utility grid by the building manager. This optimization model takes into account several parameters: the availability of the EVs parked at the parking lot (that affects the available storage capacity, which varies at each time period, as EVs come and go along the day), the total energy consumption demanded by the building, the self -PV generation and, finally, the retail energy prices. With this information, the optimization algorithm determines how the EV batteries' charge/ discharge of all parked vehicles should be managed to minimize the cost of electricity purchased from the grid.

Chapter Contents:

  • 9.1 Introduction
  • 9.2 System description
  • 9.2.1 Building PV generation and electricity consumption
  • 9.2.2 Grid electricity price
  • 9.2.3 Mobility information
  • 9.2.3.1 Parking occupation
  • 9.2.3.2 Initial available capacity
  • 9.3 Optimization modelling
  • 9.4 Scenarios and results
  • 9.5 Conclusions
  • References

Inspec keywords: power markets; energy management systems; battery storage plants; battery powered vehicles; optimisation; power grids

Other keywords: retail energy prices; available storage capacity; optimization model; electric vehicles; electricity purchase cost; distributed energy storage; self-PV generation; EV batteries; battery energy storage system; total energy consumption; local energy management; electricity cost minimization

Subjects: Optimisation techniques; Power system management, operation and economics; Transportation; Secondary cells

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