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Summary In this paper, a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the distributed generations (DGs). Bus voltage profile improvement, line flow capacity, and active and reactive power loss minimization are considered as multi‐objectives to optimize under‐distribution load enhancement. The addition of multi‐DGs to the distribution system, which is already having DGs, is studied under increased load demand. Renewable energy resources such as wind, solar, fuel cell, and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection‐based distribution load is considered in DGs modeling in power systems. Active and reactive losses and voltage profiles are studied for all combinations of DGs. To optimize the objective function, a new optimization technique called shuffled bat algorithm is proposed. The proposed methodology is tested on 38‐bus and 69‐bus radial distribution systems with 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi‐objectives considered. Copyright © 2015 John Wiley & Sons, Ltd.

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Fast Decoupled Load Flow (FDLF) solution has gained wide spread acceptance in power industry, owing to its simplicity and computational efficiency, but very little attention has been paid for implementation of Thyristor Controlled Series Compensator (TCSC) models in FDLF solutions. This paper addresses the TCSC model implementation in FDLF solution for power flow control. The TCSC firing angle is taken as the state variable, which is combined with nodal voltage angles of the entire network in a unified iterative process while keeping the matrices B' and B" constant. The feasibility of the proposed approach is demonstrated and the results of the implementation is tested on IEEE 14 and IEEE 30 bus systems for power flow control in specific branches. The results prove the computational efficiency of FDLF over the NRLF models with TCSC and found to be promising.

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 multiobjective 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.

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