Abstract
The large-scale construction of fast charging stations (FCSs) for electrical vehicles (EVs) is helpful in promoting the EV. It creates a significant challenge for the distribution system operator to determine the optimal planning, especially the siting and sizing of FCSs in the electrical distribution system. Inappropriate planning of fast EV charging stations (EVCSs) cause a negative impact on the distribution system. This paper presented a multi-objective optimization problem to obtain the simultaneous placement and sizing of FCSs and distributed generations (DGs) with the constraints such as the number of EVs in all zones and possible number of FCSs based on the road and electrical network in the proposed system. The problem is formulated as a mixed integer non-linear problem (MINLP) to optimize the loss of EV user, network power loss (NPL), FCS development cost and improve the voltage profile of the electrical distribution system. Non-dominated sorting genetic algorithm II (NSGA-II) is used for solving the MINLP. The performance of the proposed technique is evaluated by the 118-bus electrical distribution system.
Highlights
One of the greatest challenges in developed and developing countries is reducing the greenhouse gas emissions due to fossil fuel vehicles with internal combustion engines (ICEs) and electrical power generation from fossil fuels
A large number of electric vehicles (EVs) simultaneously connected to the grid causes more network power loss (NPL) and large voltage deviation at far away buses from the sources
To improve the bus voltage profile in the presence of EV charging stations (EVCSs) in distribution network, this paper considered simultaneous placement of distributed generations (DGs) and fast charging stations (FCSs)
Summary
One of the greatest challenges in developed and developing countries is reducing the greenhouse gas emissions due to fossil fuel vehicles with internal combustion engines (ICEs) and electrical power generation from fossil fuels. This paper newly presents the simultaneous placement of both FCSs and DGs to minimize the investment cost of CSs and DG units, specific energy consumption of EV user loss, voltage deviation and power losses in the coupled electrical distribution system and transportation network. 4) As per our knowledge, first time, an efficient multiobjective non-dominated sorting genetic algorithm II (NSGA-II) is proposed for finding Pareto-optimal solution of the optimal number of FCSs, DGs and its simultaneous location and sizing for minimizing station development cost (SDC), specific energy consumption of EVs, distribution system bus voltage deviation and power losses in a coupled electrical distribution system and transportation network. We present the formulation of the objective function to minimize FCS development cost, cost of specific energy consumption of EVs, Electrical NPL cost, DG power generation cost and maximum voltage deviation (MVD) in the electrical distribution network. Choosing the displacement rather than distance in this approach to obtained CSs are still optimal for the optimal road network
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