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Economic load dispatch
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This paper presents a method to solve the optimal generation and dispatch of electrical power with multiple fuel options at different power levels. In general, the cost function for each generator is considered by a single quadratic function of power, for the optimal generation and dispatch problem. However, it is more realistic to represent the generation cost function for fossil fired plants by non smooth cost function i.e. the total generation cost function has non differentiable points such as segmented piece-wise quadratic function and valve point loading. Some generating units utilize multiple fuels sources (such as gas, coal, oil etc) are faced with the problem of determining which is the most economical fuel to be selected. This problem has been solved by Hota & Das [17] considering equal incremental cost. In this method the program has to be run for a number of times for fuel combinations for different units and then to select the best one out of all combinations. This is
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Economic Load Dispatch Thesis
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The modern power system around the world has grown in complexity of interconnection and power demand. The focus has shifted towards enhanced performance, increased customer focus, low cost, reliable and clean power. In this changed perspective, scarcity of energy resources, increasing power generation cost, environmental concern necessitates optimal economic dispatch. In reality power stations neither are at equal distances from load nor have similar fuel cost functions. Hence for providing cheaper power, load has to be distributed among various power stations in a way which results in lowest cost for generation. Practical economic dispatch (ED) problems have highly non-linear objective function with rigid equality and inequality constraints. Particle swarm optimization (PSO) is applied to allot the active power among the generating stations satisfying the system constraints and minimizing the cost of power generated. The viability of the method is analyzed for its accuracy and rate of
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