Abstract
The purpose of this paper is to present a computational Analysis of various Artificial Intelligence based optimization Techniques used to solve OPF problems. The various Artificial Intelligence methods such as Genetic Algorithm(GA), Particle Swarm Optimization(PSO), Bacterial Foraging Optimization(BFO), ANN are studied and analyzed in detail. The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost and transmission loss etc. or maximizes social welfare, load ability etc. while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, power flow limits, output of various compensating devices etc. Traditionally, Classical optimization methods were used effectively to solve optimal power flow. But, recently due to the incorporation of FACTS devices and deregulation of power sector the traditional concepts and practices of power systems are superimposed by an economic market management and hence OPF have become more complex. So, in recent years, Artificial Intelligence (AI) methods have been emerged which can solve highly complex OPF problems at faster rate.
Highlights
Growing demand of the power and complexity of the power system network, power system study has become a significant tool for a power system operator in order to take corrective actions in time
Once the steady-state of the system is known, it is possible to estimate the amount of power generation necessary to supply the power demand plus the power losses in the system lines, the voltage levels must be kept within the boundaries and overloaded operations, besides the operations in the stability limit must be avoided
The results show that the optimal dispatch solutions determined by Particle Swarm Optimization (PSO) lead to lower active power loss that found by other methods, which confirms that the PSO is well capable of determining the global or near global optimum dispatch solution
Summary
Growing demand of the power and complexity of the power system network, power system study has become a significant tool for a power system operator in order to take corrective actions in time. I = Y * E Where, matrix Y is square, sparse, and symmetrical (in the absence of phase shifters or mutual couplings represented by non-bilateral network branches).With the increase of the Complexity and non linearity of the power system different Conventional optimization technique has emerged such as Ymatrix Iterative Load Flow Methods, Z-matrix Load Flow Methods, Newton Raphson Method, Fast Decoupled Method etc. It has been noted the OPF problem with series compensation may be a non Convex and non linear problem which leads to Conventional optimization methods stuck to local minimum. The paper presents the detail analysis of different above techniques
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