Authors:Hemachandra Reddy. K,P. Ram Kishore Kumar Reddy,V.Ganesh,
Keywords:Flexible AC Transmission Systems,Grey Wolf Optimization,Kinetic Gas Molecular Optimization,Static VAR Compensator,Thyristor Controlled Series Compensator,Unified Power Flow Controllers,
AbstractVoltage instability is one of the major problems in the transmission line system it causes due to the dynamic load pattern and increasing load demand. Flexible AC transmission systems (FACTS) devices are used to maintain the voltage instability by controlling real and reactive power through the system. In transmission line system, the location and size of the FACTS devices are an important consideration to offer perfect real power flow in the bus system. In this paper, an optimal placement and sizing of the FACTS devices are carried out by combining the Kinetic Gas Molecular Optimization (KGMO) and Grey Wolf Optimization (GWO). There are three different FACTS devices are used in this research, such as Static VAR compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controllers (UPFC). The objective functions considered for the proposed hybrid KGMO-GWO method are installation cost, Total Voltage Deviation (TVD), Line Loading (LL) and real power loss. Moreover, the optimal placement using the hybrid KGMO-GWO method is validated using IEEE 30 bus system. The performance of the hybrid KGMO-GWO method is analyzed by means of TVD, power loss, installation cost and line loading. Additionally, the hybrid KGMO-GWO method is compared with two existing technique named as QOCRO and hybrid KGMO-PSO. The TVD of the hybrid KGMO-GWO is 0.1007 p.u., it is less when compared to the QOCRO and hybrid KGMO-PSO.
I. Agrawal, R., Bharadwaj, S.K. and Kothari, D.P., “Population based evolutionary optimization techniques for optimal allocation and sizing of Thyristor Controlled Series Capacitor”, Journal of Electrical Systems and Information Technology, vol. 5, pp: 484-501,2018.
II. Balamurugan, K., Muralisachithanandam, R. and Dharmalingam, V., “Performance comparison of evolutionary programming and differential evolution approaches for social welfare maximization by placement of multi type FACTS devices in pool electricity market”, International Journal of Electrical Power & Energy Systems, vol. 67, pp: 517-528, 2015.
III. Canbing, L.I., Liwu, X.I.A.O., Yijia, C.A.O., Qianlong, Z.H.U., Baling, F.A.N.G., Yi, T.A.N. and Long, Z.E.N.G., “Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy,” Journal of Modern Power Systems and Clean Energy, vol. 2, pp: 173-180, 2014.
IV. Sen, D., Ghatak, S.R. and Acharjee, P., “Optimal allocation of static VAR compensator by a hybrid algorithm”, Energy Systems, vol. 10, pp: 677-719, 2019.
V. Dash, S.P., Subhashini, K.R. and Satapathy, J.K., “Optimal location and parametric settings of FACTS devices based on JAYA blended moth flame optimization for transmission loss minimization in power systems. Microsystem Technologies, pp: 1-10, 2019.
VI. Dutta, S., Paul, S. and Roy, P.K., “Optimal allocation of SVC and TCSC using quasi-oppositional chemical reaction optimization for solving multi-objective ORPD problem,” Journal of Electrical Systems and Information Technology, vol. 5, pp: 83-98, 2018.
VII. Ersavas, C. and Karatepe, E., “Optimum allocation of FACTS devices under load uncertainty based on penalty functions with genetic algorithm”, Electrical Engineering, VOL. 99, pp: 73-84, 2017.
VIII. Gitizadeh, M., Khalilnezhad, H. and Hedayatzadeh, R., “TCSC allocation in power systems considering switching loss using MOABC algorithm”, Electrical Engineering, vol. 95, pp: 73-85, 2013.
IX. Ghahremani, E. and Kamwa, I., “Optimal placement of multiple-type FACTS devices to maximize power system loadability using a generic graphical user interface,” IEEE Transactions on Power Systems, vol. 28, pp.764-778, 2012.
X. Hemachandra Reddy K, P. Ram Kishore Kumar Reddy and V. Ganesh, “Optimal Allocation of Multiple Facts Devices with Hybrid Techniques for Improving Voltage Stability”, International Journal on Emerging Technologies,vol. 10,pp. 76-84, 2019.
XI. Mondal, D., Chakrabarti, A. and Sengupta, A., “Optimal placement and parameter setting of SVC and TCSC using PSO to mitigate small signal stability proble,”. International Journal of Electrical Power & Energy Systems, vol. 42, pp: 334-340,2012.
XII. Kavitha, K. and Neela, R. “Optimal allocation of multi-type FACTS devices and its effect in enhancing system security using BBO, WIPSO & PSO,” Journal of Electrical Systems and Information Technology, vol. 5, , pp.777-793, 2018.
XIII. Panda, S., Patil R. N., “Location of Shunt FACTS Controllers for Transient Stability Improvement Employing Genetic Algorithm”, Electric Power Components and Systems, vol. 135, pp: 189-203, 2007.
XIV. Packiasudha, M., Suja, S. and Jerome, J., “A new Cumulative Gravitational Search algorithm for optimal placement of FACT device to minimize system loss in the deregulated electrical power environment”, International Journal of Electrical Power & Energy Systems, vol. 84, pp: 34-46,2017.
XV. Rahimzadeh, and Bina, M.T. “Looking for optimal number and placement of FACTS devices to manage the transmission congestion,” Energy conversion and management, vol. 52, pp.437-446,2011.
XVI. Safari, A., Bagheri, M. and Shayeghi, H., “Optimal setting and placement of FACTS devices using strength Pareto multi-objective evolutionary algorithm” Journal of Central South University, vol. 24, p: 829-839, 2017.