Particle Swarm Optimization Based Interconnected Hydro-Thermal AGC System Considering GRC and TCPS
This paper represents performance of particle swarm optimisation (PSO) algorithm based integral (I) controller and proportional-integral controller (PI) for interconnected hydro-thermal automatic generation control (AGC) with generation rate constraint (GRC) and Thyristor controlled phase shifter (TCPS) in series with tie line. The control strategy of TCPS provides active control of system frequency. Conventional objective function integral square error (ISE) and another objective function considering square of derivative of change in frequencies of both areas and change in tie line power are considered. The aim of designing the objective function is to suppress oscillation in frequency deviations and change in tie line power oscillation. The controller parameters are searched by PSO algorithm by minimising the objective functions. The dynamic performance of the controllers I and PI, for both the objective functions, are compared with conventionally optimized I controller.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1097413Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1749
 Elgerd, O. I.─ Fosha, C.: Optimum megawatt frequency control of multiarea electric energy systems, IEEE Trans. Power App. System. 89 No. 4 (1970), 556-563.
 Cohn, N. : Techniques for improving the control of bulk power transfers on interconnected systems, IEEE Trans. Power App. System, 90 No. 6 (1971), 2409–2419.
 Karnavas, Y. L. ─ Papadopoulos, D. P. : AGC for autonomous power system using combined intelligent techniques, Inter. Journal Electric Power System Research, 62 (2002), 225–239.
 Reformat, M. ─ Kuffel, E. ─ Woodford, D. ─ Pedrycz, W. : Application of genetic algorithms for control design in power systems, IEE Proc., Gen. Trans. Distr., 145 No. 4 (1998), 345–354.
 Hiyama, T.: Design of decentralized load frequency regulators for interconnected power systems, IEE Proc., Gen. Trans. Distr., 129 No.1 (1982), 17–22.
 Moon, Y. H. ─ Ryu, H. S. ─ Lee, J. G. ─Song, K. B. ─ Shin, M. C. : Extended integral control for load frequency control with the consideration of generation rate constraints, Inter. Journal Electric Power Energy System, 24 ( 2002), 263–269.
 Malik, O. P ─ Hope. G. S ─Tripathy, S. C ─ Mital N: Decentralized Suboptimal Load-Frequency Control of a Hydro-Thermal Power System Using the State Variable Model, Electric Power Systems Research, 8 (1984/1985), 237-247.
 Ray, G ─ Prasad, A. N ─ Prasad, G. D: A New Approach to the Design of Robust Load-Frequency Controller for Large Scale Power Systems, Electric Power Systems Research 51 (1999), 13-22.
 Pan C. T─ Liaw C. M : An Adaptive Controller for Power Load- Frequency Control, IEEE Trans. Power Systems, 4 No. 1 (1989), 122- 128.
 Kothari, M. L. ─ Nanda, J ─ Kothari, D. P ─DAS, D : Discrete-mode automatic generation control of a two-area reheat thermal system with new area control error, IEEE Trans. Power Systems, 4 No. 2 ( 1989), 730–738.
 Parmar, K. P. S ─ Majhi, S ─ Kothari, D.P : Load frequency control of a realistic power system with multi-source power generation, Electrical Power and Energy Systems 42 (2012), 426–433.
 Zeynelgi, H. L. ─Demiroren, A. ─ Sengor, N.S: The application of ANN technique to automatic generation control for multi-area power system, Electric Power Energy System, 24 No.5 (2002), 345–354.
 Chaturvedi, D.K. ─ Satsangi, P.S. ─Kalra, P. K : Load frequency control: a generalized neural network approach, Electric Power Energy System, 121 No. 6 (1999), 405–415.
 Ghosal, S. P.: Optimization of PID gains by particle swarm optimization in fuzzy based automatic generation control, Electric Power System Research, 72 No. 3 (2004) , 203–212.
 Talaq J,.A L. ─Basri, F. : Adaptive fuzzy gain scheduling for load frequency control, IEEE Trans. Power System, 14 No. 1 (1999), 145– 150.
 Joseph, R. A. ─Das, D. ─ Patra, A.: AGC of a Hydrothermal System with Thyristor Controlled Phase Shifter in the Tie-Line, IEEE conf. 2006.
 I. W. G. on Power Plant Response to Load Changes : Mw response of fossil fuelled steam units, IEEE Trans. on Power App. and Systems, 92 No. 2 (Mar/Apr 1973), 455–463
 I. P. W. Group. : Hydraulic turbine and turbine control models for system dynamics, IEEE Trans. on Power Systems, 7 No. 1 (Feb 1992), 167–174.
 Pedersen, M.E.H. ---- Chipperfield, A.J.: Simplifying Particle Swarm Optimization. Applied Soft Computing, Vol. 10, No. 2. (2010), pp.618- 628.
 Fan, H.: A modification to particle swarm optimization algorithm, Engineering Computations. International Journal for Computer-Aided Engineering 19 (2002) pp.970–989.