عنوان مقاله [English]
نویسنده [English]چکیده [English]
The key of Reactive Power Planning (RPP), or Var planning and reactive power dispatch, are the optimal allocation of reactive power sources considering location and size. Traditionally, the locations for placing new Var sources were either simply estimated or directly assumed. Recent research works have presented some rigorous optimization based methods in RPP. The reactive power dispatch and planning is a large-scale non-convex, nonlinear programming (NLP) problem with real and discrete variables that presents a high degree of complexity for application in real electric power systems (EPS). This paper addresses an improved gravitational search algorithm (GSA) with strength Pareto front to find the feasible optimal solution of the RPP problem with various generator constraints in power systems. For practical generator operation, many nonlinear constraints of the generator, such as ramp rate limits, generation limits, transmission line loss and non-smooth cost functions are all considered using the proposed method. Effectiveness of the proposed method is demonstrated for two different systems, including 6 and 54 unit generating in comparison with the performance of the other recently optimization algorithms reported in the literature in terms of the solution quality and computation efficiency. The results analysis confirms that the proposed approach has an excellent capability to determine optimal solution of the RPP problems over the other existing methods and enhances efficiently the solutions quality of the power systems.
 Ajjarapu V., Lau P. L., Battula S.( 1994), “An optimal reactive power planning strategy against voltage collapse”. IEEE Trans. Power Syst., vol. 9, no. 2, pp. 906–917.
 Liu H., Jin L., McCalley J. D., Kumar R., Ajjarapu V., Elia N.( 2009),” Planning reconfigurable reactive control for voltage stability limited power systems”. IEEE Trans. Power Syst., vol. 24, no. 2, pp. 1029–1038.
 Dommel H.W., Tinny W.F. (1968),” Optimal power flow solutions”. IEEE Trans. Power App. Syst, PAS.87, pp. 1866–1876.
 Lee K.Y., Park Y.M., Ortiz J.L. (1985),”A united approach to optimal real and reactive power dispatch”. IEEE Trans. Power App. Syst, PAS. 104, pp. 1147–1153.
 Granville S.(1994),” Optimal reactive power dispatch through interior point methods”. IEEE Trans. Power Syst. vol. 9, no. 1, pp. 136–146.
 Lai L.L., Ma J.T. (1997),” Application of evolutionary programming to reactive power planning – comparison with nonlinear programming approach”. IEEE Trans. Power Syst. vol. 12, no. 1, pp. 198–206.
 Iba K. (1994),” Reactive power optimization by genetic algorithms”. IEEE Trans. on Power Syst. vol. 9, no. 2, pp. 685–692.
 Wu Q.H., Ma J.T. (1995),”Power system optimal reactive power dispatch using evolutionary programming”. IEEE Trans. Power Syst. vol. 10, no. 3, pp. 1243–1248.
 Lai L.L., Nieh T.Y., Vujatovic D., Ma Y.N., Lu Y.P., Yang Y.W., Braun H.( 2005),” Swarm intelligence for optimal reactive power dispatch”. Proceeding in IEEE/PES Trans. Distrib. Conf. Exhibition, Asia and Pacific, Dalian, China, pp. 1–5.
 Ghasemi A., Shayeghi H., Alkhatib H.(2013),” Robust Design of Multimachine Power System Stabilizers using Fuzzy Gravitational Search Algorithm”. Electrical Power and Energy Systems, vol. 51, pp. 190-200.
 Estevam C.R.N. Rider M.J. Amorim E. Mantovani J.R.S.(2010),” Reactive power dispatch and planning using a non-linear branch-and-bound algorithm”. IET Gener. Transm. Distrib. vol. 4, Iss. 8, pp. 963–973.
 Shayeghi H. Ghasemi A.(2012),” Optimal tuning of PID type stabilizer and AVR gain using GSA technique”. International Journal on “Technical and Physical Problems of Engineering” (IJTPE), vol. 4, no. 2, pp. 98-106.
 Shayeghi H., Ghasemi A. (2012),” Application of MOPSO for economic load dispatch solution with transmission losses”. International Journal on “Technical and Physical Problems of Engineering” (IJTPE), vol. 4, no. 1, pp. 27-34.