The work deals with the optimization of power flow problem through interconnected system. The work presents an algorithm for solving optimal power flow problem through the application of Differential Evolution (DE). The objective is to minimize the total fuel cost of thermal generating units having quadratic cost characteristics subjected to limits on generator real and reactive power outputs, bus voltages, transformer taps and power flow of transmission lines. The work introduces a conceptual overview and detailed explanation of Differential Evolution algorithm as well as shows how it can be used for solving optimal power flow problems.Inherent shortcoming of the traditional methods of finding the optimal power solution is discussed along with other evolutionary methods of finding optimal power solution. A comparative study of different evolutionary programming technique is done and it is shown that Differential Evolution offer a better result with greater repeatability and lesser time. The proposed method has been tested under simulated conditions on IEEE 30-bus system. The optimal power flow results obtained using Differential Evolution are compared with other Genetic Algorithm. It is shown that Differential Evolution total generation fuel cost is less expensive than those of evolutionary programming, Gradient projection method (GPM), SLP, QN.
Cite this article:
Aakansha Mercy Steele, Tarabhan Gupta. Optimal Power Flow using Differential Evolution. Int. J. Tech. 2018; 8(1): 33-40 doi: 10.5958/2231-3915.2018.00006.8