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This study introduces a techno-economic planning strategy of reactive power (VAr) in power transmission systems. This planning strategy primarily has been focused on reactive power planning (RPP) through operating cost minimisation ensuring cost-oriented system security. The objective function (operating cost) is blended with four different components viz. cost due to real power loss, VAr generation cost, additional VAr compensation devices cost and line charging cost. FACTS (flexible AC transmission system) devices are installed at weak positions through different echelons to improve the system voltage stability. The authors also implemented the probabilistic hybridisation of crow search algorithm and JAYA to find out the optimal set of controlling parameters related to VAr. Finally, a sharp and minute analysis of the results has been done to validate the proposed strategy under multi-loading conditions. To understand the efficiency and efficacy the code profiling and simulation has been rendered on IEEE 30 bus and UPSEB 75 bus test system. [ABSTRACT FROM AUTHOR]

In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive Particle Swarm Optimization) and EPSO (Evolutionary Particle Swarm Optimization) are used for the optimal setting of the Var sources and FACTS devices. The result obtained with the proposed approach is compared with the result found by the conventional RPP (Reactive power planning) approach where shunt capacitors, transformer tap setting arrangements and reactive generations of generators are used as planning variables. It is observed that reactive power planning with FACTS devices yields much better result in terms of reducing active power loss and total operating cost of the system even considering the investment costs of FACTS devices. [ABSTRACT FROM AUTHOR]

In the present work, GSA (gravitational search algorithm) based optimization algorithm is applied for the optimal allocation of FACTS devices in transmission system. IEEE 30 & IEEE 57 test bus systems are taken as standards. Both active and reactive loading of the power system is considered and the effect of FACTS devices on the power transfer capacity of the individual generator is investigated. The proposed approach of planning of reactive power sources with the FACTS devices is compared with other globally accepted techniques like GA (Genetic Algorithm), Differential Evolution (DE), and PSO (Particle Swarm Optimization). From the results obtained, it is observed that incorporating FACTS devices, loadability of the power system increases considerably and each generator present in the system is being able to dispatch significant amount of active power under different increasing loading conditions where the steam flow rate is maintained corresponding to the base active loading condition. The active power loss & operating cost also reduces by significant margin with FACTS devices at each loading condition and GSA based planning approach of reactive power sources with FACTS devices found to be the best among all the methods discussed in terms of reducing active power loss and total operating cost of the system under all active and reactive loading situations. [ABSTRACT FROM AUTHOR]

Highlights: [•] Fuzzy based evolutionary algorithm. [•] FACTS devices for reactive power optimization. [•] FACTS devices for minimum operating cost of a power system. [Copyright &y& Elsevier]

This paper presents the application of Genetic Algorithm (GA) and Differential Evolution (DE) technique for the minimization of transmission loss and simultaneous reduction in the operating cost of the system using Flexible AC Transmission System (FACTS) devices. Three types of FACTS devices, Thyristor Controlled Series Compensator (TCSC), Static VAR Compensator (SVC) and Unified Power Flow Controller (UPFC) are considered for this purpose. Optimal placement of FACTS devices in the heavily loaded power system reduces transmission loss, control reactive power flow, improves voltage profile of all nodes and also reduces operating cost. The system is reactively loaded starting from base to 200% of base reactive load and the system performance is observed without and with FACTS devices. The proposed technique is applied on IEEE 30-bus system for the optimal setting of FACTS devices. Finally, how system performance is improved with the use of UPFC along with other series and shunt FACTS controller is illustrated. [ABSTRACT FROM AUTHOR]

In this paper Genetic Algorithm (GA) is used as an evolutionary techniques for the optimal placement of flexible AC transmission systems (FACTS) devices in an interconnected power system. Here two types of FACTS devices has been discussed namely, Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) for the economic operation and to reduce the transmission loss. Reactively loading of the system is taken from base to 200 % of base loading and the system performance is observed without and with FACTS devices. Optimal placement of FACTS devices in the system is determined by calculating active and reactive power flow in lines. FACTS devices along with reactive generation of generators and transformer tap setting are used for the power transfer capacity using GA. The proposed approach is applied on IEEE 14 and IEEE 30-bus test systems. Finally the effectiveness of the proposed GA based method of placement of FACTS devices is established by comparing the results with another standard method of optimization like Particle Swarm Optimization (PSO) technique. [ABSTRACT FROM AUTHOR]

This paper presents Particle Swarm Optimization (PSO) based approach for the allocation & coordinated operation of multiple FACTS (Flexible AC Transmission System) devices for the economic operation as well as to increase power transfer capacity of an interconnected power system under different loading condition. The PSO based approach is applied on IEEE 30-bus system. The system is reactively loaded starting from base to 200 % of base load. FACTS devices are installed in the different locations of the power system and system performance is noticed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. A Particle Swarm Optimization based algorithm is then applied to find the amount of magnitudes of the FACTS devices. This Particle Swarm Optimization based approach for the placement of FACTS devices Yields promising result both in terms of performance and economy which is clearly observed from the result obtained. [ABSTRACT FROM AUTHOR]