MULTIOBJECTIVE ECONOMIC LOAD DISPATCH USING INTELLIGENT TECHNIQUES

Abstract

Power sector is one of the important infrastructures of a country, which is the prime mover of the overall economic development. The all India demand for electricity is increasing continuously across all segments of the economy such as agriculture, industry, commercial sector, domestic sector etc. Thermal power is the prime resource to meet the demand. Coal power generation increased 3% in 2018 (similar to the 2017 increase), and for the first time crossed the 10000 TWh. mark. Coal remains firmly in place as the largest source of power of overall generation. To meet the demand of all sectors, generation of electrical power is essential. Economic Load Dispatch problem is an optimization problem which minimizes the total fuel cost of all committed plants while meeting the demand and losses. Real life problems may be nonlinear, non-differentiable and discontinuous. These cannot be solved using classical optimization techniques. Classical techniques have the tendency of settling down at local minima instead of the global best solutions. Therefore, intelligent techniques are being used to solve real life problems. But their computational efficiency is very slow and suffer from poor convergence. To overcome the limitation of Intelligent techniques, some improvements /modifications need to be carried out. The optimal power system operation is achieved when various objectives of power systems: cost of generation, system transmission losses, environmental emission etc. simultaneously achieve their minimum value. But these objectives may be conflicting in nature and cannot be handled by conventional single objective optimization techniques. Single objective optimization techniques give the best value of objective under consideration whereas the values of other objectives may not be acceptable at all. Therefore, Multiobjective approach has been used to solve such problems. vi

In this research work, economic load dispatch (ELD) and multiobjective economic load dispatch (MELD) problem have been solved using intelligent techniques i.e. genetic algorithm (GA) and basic particle swarm optimization (BPSO). Using improvement and many modifications in basic particle swarm optimization (BPSO) new improved / modified algorithms i.e. initial selection based particle swarm optimization (IPSO IS), adaptive social acceleration constant based particle swarm optimization (ASACPSO) and feasibility oriented particle swarm optimization (FOPSO) have been developed, which have resulted in significant reduction in computational effort. Also, the Pareto – Front for MELD problem has been achieved in a single run (rather in a partial run) using FOPSO for IEEE 5, 14 and 30 bus systems considering cost of generation, system transmission losses and environmental emission. MELD problem for IEEE 5, 14 and 30 bus systems, considering cost of generation, system transmission losses and environmental emission is formulated using weighting method and Noninferior set has been generated by basic particle swarm optimization (BPSO). MELD problem for IEEE 5, 14 and 30 bus systems, considering cost of generation, system transmission losses is also formulated using constraint method and Noninferior set has been generated by genetic algorithm. In this research work a sincere effort has been made to improve the computational efficiency of intelligent techniques in general and to solve ELD and MELD problem in particular. Many improvements and modifications have been carried out in BPSO, which have resulted in significant reduction of computational effort.