Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices

Open access


The problem of improving the voltage profile and reducing power loss in electrical networks must be solved in an optimal manner. This paper deals with comparative study of Genetic Algorithm (GA) and Differential Evolution (DE) based algorithm for the optimal allocation of multiple FACTS (Flexible AC Transmission System) devices in an interconnected power system for the economic operation as well as to enhance loadability of lines. Proper placement of FACTS devices like Static VAr Compensator (SVC), Thyristor Controlled Switched Capacitor (TCSC) and controlling reactive generations of the generators and transformer tap settings simultaneously improves the system performance greatly using the proposed approach. These GA & DE based methods are applied on standard 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 observed 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. GA and DE based algorithm is then applied to find the amount of magnitudes of the FACTS devices. Finally the comparison between these two techniques for the placement of FACTS devices are presented.

[1] Hingorani N., Flexible AC Transmission. IEEE Spectrum 30(4): 40-45 (1993).

[2] Noroozian M., Anderson G., Power Flow Control by use of controllable Series Components. IEEE Trans. Power Delivery 8(3): 1420-1429 (1993).

[3] Iravani M., Dandeno P.L., Maratukulam D., Application of Static Phase Shifters in Power Systems. IEEE Trans Power Delivery 9(3):1600-1608 (1994).

[4] Nelson R., Bian J., Williams S., Transmission Series Power Flow Control. IEEE Trans. Power Delivery 10(1): 504-510 (1995).

[5] Okamoto H., Kurita A., Sekine Y., A Method For Identification Of Effective Locations Of VariableImpedance Apparatus On Enhancement Of Steady-State Stability In Large Scale Power Systems. IEEE Trans. Power System 10(3): 1401-1407 (1995).

[6] Lie T.T., Deng W., Optimal Flexible AC Transmission Systems (FACTS) devices allocation. Int. Journal of Electrical Power & Energy Systems 19(2): 125-134 (1997).

[7] Gotham D.J., Heydt G.T., Power Flow Control and Power Flow Studies for System with FACTSDevices, IEEE Trans. Power System 13(1): 60-65 (1998).

[8] Xiao Y., Song Y.H., Sun Y.Z., Power Flow Control Approach to Power Systems With EmbeddedFACTS Devices. IEEE Trans. Power System 17(4): 943-950 (2000).

[9] Xiao Y., Song Y.H., Chen-Ching Liu, Sun Y.Z., Available Transfer Capability Enhancement UsingFACTS Devices. IEEE Trans. Power System 18(1): 305-312 (2009).

[10] Galiana F.D., Almeida K., Assessment and Control Of The Impact Of FACTS Devices On PowerSystem Performance. IEEE Transactions on Power Systems 11(4): 1931-1936 (1996).

[11] Gerbex S., Cherkaoui R., Germond A.J., Optimal Location of Multi-Type FACTS Devices in a PowerSystem by Means of Genetic Algorithms. IEEE Trans. Power System 16(3): 537-544 (2001).

[12] Zaho Q., Jiang J., A TCSC damping controller design using robust control theory. Int. Journal of Electrical Power & Energy System 20(1): 25-33 (1998).

[13] Chung T.S., Li Y.Z., A Hybrid GA approach for OPF with Consideration of FACTS Devices. IEEE Power Engineering Review pp. 54-57 (2000).

[14] Dash P.K., Sharaf A.M., Hill E.F., An Adaptive Stabilizer For Thyristor Controlled Static Var CompensatorsFor Power Systems. IEEE Trans. Power System 4(2): 403-410 (1989).

[15] Hassan M.O., Cheng S.J., Zakaria Z.A., Steady-State Modeling of SVC and TCSC for Power FlowAnalysis. Int. MultiConference of Engineers and Computer Scientists 2009 II, IMECS (2009).

[16] Bhattacharyya B., Goswami S.K., Bansal R.C., Loss-Sensitivity Approach in Evolutionary Algorithmsfor Reactive Power Planning. Electric Power Components & Systems 37(3): 287-299 (2009).

[17] Tiwari P.K., Sood Y.R., Optimal Location of FACTS Devices in Power System Using Genetic Algorithm. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), pp. 1034-1040 (2009).

[18] Narayana Prasad Pandhy, Abdel Moamen M.A., Power flow control and solutions with multiple andmulti-type FACTS devices. Electric Power Systems Research 74: 341-351 (2005).

[19] Basu M., Optimal power flow with FACTS devices using differential evolution. Electrical Power and Energy Systems30: 150-156 (2008).

[20] Cai L.J., Optimal Choice and Allocation of FACTS Devices in Deregulated Electricty Market UsingGenetic Algorithms 0-7803-8718-X/04/2$ 20.00 © 2004 IEEE (2004).

[21] Goldberg D.E., Genetic Algorithms in search. Optimization & Learning, Addison-Wesley.

[22] Storn R., Price K., Differential Evolution - A simple and Efficient Heuristic for Global Optimizationover Continuous Spaces. Journal of Global Optimization 11: 341-359 (1997).

Archives of Electrical Engineering

The Journal of Polish Academy of Sciences

Journal Information

CiteScore 2016: 0.71

SCImago Journal Rank (SJR) 2016: 0.238
Source Normalized Impact per Paper (SNIP) 2016: 0.535


All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 92 92 8
PDF Downloads 37 37 4