Narayanan Kumarappan

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There is a general consensus that the movement of electricity price is crucial for electricity market. The binary electricity price classification method is as an alternative to numerical electricity price forecasting due to high forecasting errors in various approaches. This paper proposes a binary classification of day-ahead electricity prices that could(More)
This paper presents new hybrid genetic algorithm (GA) to solve the combined economic and emission dispatch (CEED) problem. Focus is on the reduction of single pollutant nitrogen oxide (NO/sub x/). The equality constraints of power balance; the inequality generator capacity constraints and the prohibited zone constraints are considered. Here real coded GA is(More)
A number of factors determined the outcome of electricity prices and exhibits a very complicated and irregular fluctuation. The accurate forecasting of various approaches is high in forecasting errors. In this work an application of probabilistic neural networks (PNN) mode is applied to national electricity market of Singapore (NEMS), i.e. Asia's first(More)
Global electricity market deregulation makes compatible changes and new challenges in power system operation planning problem. Maintenance is required for the generating unit to reduce the risk of capacity outage and to improve availability of units and thereby extending equipment lifetime. Modified particle swarm optimization (MPSO) for the generator(More)