Multi-objective planning of fast charging stations and switched capacitor banks considering volt/VAr-controlled customer-owned DERs

• A multi-objective planning framework for FCSs and capacitor banks is proposed • A joint optimization from grid and EV user perspectives is introduced • Stochastic EV demand and DER generation are modeled via Monte Carlo • The impact of Volt/VAr control in customer-owned DERs is analyzed • A comparison of fixed and switched capacitor banks is performed In recent years, power systems have undergone significant changes, including the increasing integration of customer-owned distributed energy resources (DERs) and fast charging stations (FCSs), which may increase operational and investment costs for system operators. Therefore, the optimized planning of FCSs and reactive power support devices, such as capacitor banks, becomes essential to mitigate these impacts. However, uncertainties related to electric vehicle (EV) charging demand and the stochastic behavior of customer-owned DERs pose significant challenges for this planning problem. In this study, the Multi-objective Cuckoo Search (MOCS) and the Nondominated Sorting Genetic Algorithm II (NSGA-II), combined with the Fuzzy Decision-Making Method, are applied to optimize the planning of FCSs and capacitor banks, aiming to minimize investment, user, and power loss costs. The Monte Carlo method is employed to represent uncertainties in both customer-owned DER generation and EV charging demand. Additionally, different planning scenarios are analyzed, including the operation of customer-owned DERs under Volt/VAr control and the use of both static and switched capacitor banks for reactive power compensation. The proposed methodology is validated on the unbalanced IEEE 33-bus distribution system integrated with a 25-node traffic network. The results show that Fuzzy-NSGA-II and Fuzzy-MOCS allocate two and three FCSs, respectively, along with two and three capacitor banks, achieving a reduction of up to 21.41% in power loss costs compared with the system considering only customer-owned DERs. The results demonstrate that the proposed planning framework effectively mitigates the impacts of fast EV charging demand while improving the operational performance of the distribution system.