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This paper presents a new approach to solve the short-term unit commitment problem using An Evolutionary Programming Based tabu search method with cooling and banking constraints. Numerical results are shown comparing the cost solutions and computation time obtained by using the evolutionary programming method and other conventional methods like dynamic programming, lagrangian relaxation.

A new multilevel inverter with less no of power switches is proposed. This is based on cascaded H-bridge topology. The design and analysis of 31-level reduced switch inverter with different modes of operation are presented in this paper. The proposed inverter is asymmetric in nature and it uses unequal DC voltage sources. PD-PWM modulation technique has been used here to get proper switching. The proposed idea has been validated through simulation and the received results provides better efficiency, less low order harmonics and less switching losses.

This paper presents a hybrid particle swarm optimization based genetic algorithm and hybrid particle swarm optimization based evolutionary programming for solving long-term generation maintenance scheduling problem. In power system, maintenance scheduling is being done upon the technical requirements of power plants and preserving the grid reliability. The objective function is to sell electricity as much as possible according to the market clearing price forecast. While in power system, technical viewpoints and system reliability are taken into consideration in maintenance scheduling with respect to the economical viewpoint. It will consider security constrained model for preventive maintenance scheduling such as generation capacity, duration of maintenance, maintenance continuity, spinning reserve and reliability index are being taken into account. The proposed hybrid methods are applied to an IEEE test system that consist 24 buses with 32 generating unit system.