Optimal dispatch of active and reactive power using cuckoo search method

Abstract

This paper deals with application of evolutionary algorithm (EA) to solve optimal power flow problem in an efficient manner. In this paper a new approach using cuckoo search (CS) method is proposed for solving OPF problem by optimal setting of control variables. Cuckoo search method is a bio-inspired algorithm based on brooding behaviour of cuckoo birds. This algorithm can search for a global solution using multiple paths. Different objective functions as fuel cost minimization and power loss minimization has been considered for optimal active & reactive power dispatch respectively. The proposed method is implemented and evaluated on the IEEE 30-bus system. The simulation results of the proposed approach are compared to others those reported in the literature. The results demonstrate the potential of the proposed approach and show its effectiveness and robustness to solve the OPF problem.

Solution of Combined Economic Emission Dispatch with Demand Side Management Using Meta-heuristic Algorithms

“…This system consists of 22 load-buses and 48 lines. Generators are connected at bus numbers 2,5,8,11,13. Standard values of coefficients for fuel cost and emission dispatch of CO2 gas, SO2 gas and NOX gas are given in Table ( 4) and Table (5) respectively [22].…”

“…A fraction of worst nest are abandoned and replaced by new solutions by probability (Pa). (8). Compare the fitness value of current and previous iteration F(t) > F(t-1) (9).…”

“…Some of conventional algorithms viz. Linear programming (LPP), Interior point (IP), Gradient method (GM), have been proposed to solve the different problems of power system successfully [4][5][6][7][8], but there are some problems associated with these algorithms found in literature are, local optimum solution, limited in solving unimodel and smooth objectives only [9][10]. The objective function of CEED is non-differential as well as nonlinear one [11].…”

Solution of an ELD problem with valve-point effect using artificial intelligence techniques

“…Here, λ is the "skew parameter" which can be in the range of 1 to 3. It can have infinite variance with infinite mean [21].…”

“…The CS algorithm has been used as an optimization tool in solving various single and multi-objective OPF problems [15][16]. Second technique is particle swarm optimization (PSO) which has been used to solve various engineering problems [18][19][20][21][22]. This paper proposes two evolutionary optimization techniques namely Cuckoo Search (CS) method and Modified PSO (MPSO) to solve ELD for the electric power system.…”