Abstract
In this paper, an optimal sizing and placement framework (OSPF) is performed for electric parking lots integrated with wind turbines in a 33-bus distribution network. The total objective function is defined as minimizing the total cost including the cost of grid power, cost of power losses, cost of charge and discharge of parking lots, cost of wind turbines as well as voltage deviations reduction. In the OSPF, optimization variables are selected as electric parking size and wind turbines, which have been determined optimally using an intelligent method named arithmetic optimization algorithm (AOA) inspired by arithmetic operators in mathematics. The load following strategy (LFS) is used for energy management in the OSPF. The OSPF is evaluated in three cases of the objective function such as minimizing the cost of power losses, minimizing the network voltage deviations, and minimizing the total objective function using the AOA. The capability of the AOA is compared with the well-known particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms for solving the OSPF in the last case. The findings show that the power loss, voltage deviations, and power purchased from the grid are reduced considerably based on the OSPF using the AOA. The results show the lowest total cost of energy and also minimum network voltage deviation (third case) by the AOA in comparison with the PSO and ABC with a higher convergence rate, which confirms the better capability of the proposed method. The results of the first and second cases show the high cost of power purchased from the main grid as well as the high total cost. Therefore, the comparison of different cases confirms that considering the cost index along with losses and voltage deviations causes a compromise between different objectives, and thus the cost of purchasing power from the main network is significantly reduced. Moreover, the voltage profile of the network improves, and also the minimum voltage of the network is also enhanced using the OSPF via the AOA.
Highlights
In the last decade, the use of electric vehicles in the transportation industry has been widely welcomed in various countries
The results confirmed the better performance of the optimal sizing and placement framework (OSPF) via arithmetic optimization algorithm (AOA) in the operation of the distribution network compared with the ant lion optimizer (ALO) [36] and MOHTLBOGWO [30] in achieving lower power loss and more minimum voltage
The OSPF was presented for the allocation of electric parking lots and wind turbines in a distribution network with the load following strategy
Summary
The use of electric vehicles in the transportation industry has been widely welcomed in various countries. An optimal sizing and placement framework (OSPF) for electric parking lots with wind turbines is performed on 33-bus distribution networks to minimize the cost of losses, wind turbine power, battery charging and discharging, and purchasing power from the main grid. The cost of power losses, the cost of purchasing power from the main network, and network voltage conditions are investigated before and after problem solution, and the effect of the optimal application of electric parking lots has been evaluated This framework is very effective for distribution network operators to understand the sizing and placement of parking lots as integrated renewable energy resources in the distribution network. Where Limiti is the maximum allowable power passing through line i
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