Design of Spider Monkey Optimization Algorithms for Solving Complex Power System Problems

Abstract

The power system is a complex interconnected network which can be subdivided newlinein generation, distribution, transmission, and load. In a power system, the main newlineaim is to transmit energy from one place to another at minimum losses and least newlinecost. In this work, selected problems related to power system are considered to newlineaccomplish the above task. The nature-inspired algorithms (or swarm intelligence newlinemotivated algorithms) (NIAs) have shown efficiency to solve many complex realworld newlineoptimization problems. The efficiency of NIAs is measured by their ability newlineto find adequate results within a reasonable amount of time, rather than an ability newlineto guarantee the optimal solution. This thesis presents solutions for complex newlinepower system optimization problems using a recent swarm intelligence motivated newlinealgorithm namely, spider monkey optimization (SMO) algorithm. But like other newlineswarm intelligence based algorithms, SMO also suffers from the problem of stagnation newlineand skipping the true solution. Therefore, in this thesis, to improve the newlineperformance of SMO, four new variants of SMO are proposed namely, limac¸on newlineinspired SMO (LSMO), power law local search based SMO (PLSMO), l´evy flight newlineSMO (LFSMO), and Fibonacci inspired SMO (FSMO). The SMO and all its newlineproposed variants are applied to solve the complex power system problems. newlineHere, LSMO is proposed and applied to solve capacitor placement and sizing newlineproblem. The problem is considered to reduce losses in transmission and distribution newlinepart of the power system. Further, the lower order system modeling newlineproblem is solved using the proposed PLSMO to obtain a better approximation newlinefor lower order systems which reflects almost original higher order system s newlinecharacteristics. Next, optimal power flow (OPF) problem is solved using proposed newlineLFSMO. The loads in electrical engineering may be varying in nature. For newlinesupplying these loads, with an aim of minimum losses in transmission and distribution, newlineadditional transmission lines may be added for expansion.