Optimization of a Megawatt Truck Charging Station with Local Battery Storage - A study on cost optimization and peak load management in megawatt charging systems
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Examensarbete på kandidatnivå
Bachelor Thesis
Bachelor Thesis
Modellbyggare
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This thesis evaluates the design and economic feasibility of a megawatt charging station
using a local battery energy storage system with a limited grid connection. The study
investigates when local battery storage should be used, how the number of chargers should
be dimensioned and which parameters have the largest impact on investment decisions.
The conclusions are based on a linear optimization model, which minimizes system cost
by sizing the system using connection and BESS, a simulation model that verifies the
optimization and determines the number of chargers needed and an investment calculation
that calculates the financial viability of the charging station.
The linear optimization results show that a higher battery cost leads to a smaller battery
system and a larger grid connection as battery energy capacity and power capacity decrease.
Additionally, with greater electricity price variation, it becomes more beneficial to
have a larger battery capacity. For the base case, the optimal configuration under assumptions
used in this study consisted of seven MCS chargers, two power distribution centers,
a grid connection of approximately 642 kW, a battery energy capacity of 647 kWh and a
battery power capacity of 264 kW. The simulation showed that eliminating queue time is
not economically justified, since the additional reduction in waiting cost from installing
another charger does not outweigh the additional investment cost. The investment calculation
indicates that the charging station is profitable under the assumptions made in
this study, with a positive NPV of 18.2 MSEK and a DPP below the assumed 10-year
battery lifetime. Therefore, the results indicate that a local battery storage system is
more beneficial when there are high charging peaks and a variation in electricity prices
present. However, profitability is sensitive to demand level, battery cost, electricity price
and retail price.
