In the new restructured electricity power industry, a Generation Company (GENCO) with thermo-electric amenities faces the optimal problem of how to attain a maximum profit by considering the price uncertainties. In deregulated power markets, the maximization of profit is different from the minimization of cost because generation companies no longer have the obligation to serve the whole demand....

This chapter presents a stochastic unit commitment model for power systems and revisits parallel decomposition algorithms for these types of models. The model is a two-stage stochastic programming problem with first-stage binary variables and second-stage mixed-binary variables. The here-and-now decision is to find day-ahead schedules for slow thermal power generators. The wait-and-see decision...

The environmental concerns are having a significant impact on the operation of power systems. The traditional Unit Commitment problem, which to minimizes the fuel cost is inadequate when environmental emissions are also considered in the operation of power plants. This paper presents a Biased Random Key Genetic Algorithm (BRKGA) approach combined with non-dominated sorting procedure to find sol...

A work on neural network and fuzzy logic based technique for solving the problem of unit commitment in any electric utility is presented in this paper. The effectiveness of economic dispatch is well understood when the objective is to schedule the committed generators to meet the load, maintain voltages and frequency within prescribed tolerances and minimize operating cost without unduly stress...