Overload Alleviation Using Natural Exponent Inertia Weight Particle Swarm Optimization

The electricity industry deregulation perplexes power systems operation, which is a prima and intricate system, whose circumstance of operation may not have constant value always. The electric industry has experience severe variations that have greatly concerned market of the energy. The exigence condition may befall in the power system because of unexpected contingencies. Contingencies may be unexpected increase of system load, the sudden disruption in the lines, generators, or breakdown in any components of the system. These may affect the system constraints to exceed the parameters which leads to a vulnerable system. This condition may lead in some complications for example overloading of line, voltage breakdown and the instability in angle. Overloading is an issue that may leads to exigence states in which the whole system may drive toward collapse. To alleviate overload in exigence condition is a vital problem in working of the power system. Therefore, during an exigence, operators of the system are required to do load shedding and the rescheduling of generator active power resolutions on system security concerns, to relieve constraints and maintain system steadiness. Distinctive metaheuristic optimization methods have been instigated to explain the transmission overload problems. The proposed work abstracts the relief of transmission lines overload during exigency situations by using Natural Exponent Inertia Weight Particle Swarm Optimization. PSO has come forth as a practicable optimization tool for managing non-linear programming complications. The efficacy of projected method was examined on standard IEEE 30 bus system and standard IEEE 57 bus system in MATLAB. Then, the outcomes are equated to the other computation techniques.