# Planning of High-Power Charging Stations for Electric Vehicles: A Review
## 4 Modelling and Planning
### Optimization
#### 4.2.5 DSO-Oriented Planning  
* Grid Expansion Costs: these are evaluated in few articles: [84] includes substation expansions (power dependent) and feeder upgrades (length and power dependent). * Energy Losses: many studies include losses in the electric network [25; 58; 59; 60; 61; 63] due to charging-discharging behavior. This factor is usually counted as a cost through electricity price ([61]), but also as energy units, as in [55], which implemented a multi-objective optimization. In contrast, the authors of [65] make use of three indices to maximize the power quality, minimize active and reactive power losses, and finally impose a penalty on substantial voltage deviations. However, it should be noted that economic losses due to an added charging demand of EVs in the electric system do not translate into a significant change in the cost function. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Ref** & **Year** & **Charging Station** & **Installation** & **O\&M** & **Land** & **Penalty** \\ \hline  
\hline \end{tabular}
\end{table} 
Table 4: Planning: service provider oriented. There is a body of literature that analyzes grid impacts from high-power charging on the distribution system but does not assess the monetary cost of it. In [135], the dynamic voltage stability of distribution grids is investigated using a modified version of the IEEE 13-bus system. Study [136] investigates the integration of high-power CI into low- and medium voltage grids, providing a detailed view of the electrical grid and challenges/possibilities related to the integration of high-power charging. This approach is applied to two electrical networks: a simple system composed of nine buses and a 69-node radial network. In [60], the authors are the first to include the hourly grid load to precisely estimate grid losses for the minimization of grid costs related to FCSs. In this case, an AC power flow is implemented in a network of 13 buses. The analysis in [59] focuses on added power losses through harmonic distortion injection in a 47-bus Malaysian radial distribution system. The authors conclude that significant power losses can occur without a proper harmonic pollution mitigation. The authors of [137] compare how different modes of transport can impact the grid, taking into account demand side management, such as ripple control. In the user case, a light rail transit is compared to the electric demand that would result from the electrification of a small portion of the urban ICEV fleet. The authors conclude that the impacts of the EV on the local grid could be insignificant if they are well managed through demand side management (DSM), whereas light rail transit would require upgrades to some substations. Instead, if no DSM strategy is applied, the power level required by the EV fleet is seven times higher than that required by the rail transit. The study provides an interesting perspective comparing two transportation systems, one public and one private, that are equivalent in terms of the passenger kilometers provided daily. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ref** & **Year** & **U** & **P** &
\begin{tabular}{c} **CT** \\ **WC** \\ \end{tabular} & **CC** \\ \hline
[20] & 2016 & & & & ✓ \\
[21] & 2016 & & & ✓ & ✓ \\
[22] & 2019 & ✓ & & ✓ & ✓ \\
[23] & 2019 & & & ✓ & ✓ \\
[24] & 2018 & ✓ & ✓ & & \\
[28] & 2016 & ✓ & & & \\
[30] & 2018 & & ✓ & & \\
[38] & 2017 & & & & ✓ \\
[41] & 2016 & ✓ & & & ✓ \\
[43] & 2017 & ✓ & & ✓ & \\
[48] & 2019 & & & ✓ & \\
[81] & 2020 & & & ✓ & \\
[82] & 2020 & & ✓ & & \\
[50] & 2017 & ✓ & & & \\
[51] & 2019 & & & ✓ & \\
[52] & 2019 & & & ✓ & \\
[54] & 2016 & & & & ✓ \\
[55] & 2016 & & & & ✓ \\
[57] & 2016 & & & ✓ & \\
[58] & 2019 & ✓ & & & \\
[59] & 2018 & ✓ & & & \\
[60] & 2017 & ✓ & & & \\
[62] & 2016 & ✓ & & & ✓ \\
[63] & 2014 & ✓ & & & \\
[67] & 2018 & ✓ & & & \\
[119] & 2019 & ✓ & ✓ & & \\
[132] & 2020 & ✓ & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}  
* CT: charging time, WC: waiting cost, CC: charging coverage.  
\end{table} 
Table 5: Planning: final user oriented.