Optimal generation expansion planning



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The conventional techniques of evaluating the utility expansion policies are based on the use of equivalent inverted load duration curves involving the numerical convolution processes. Thus there has always been an issue of trade-off between computational effort and accuracy of the desired solution. This dissertation presents a new approach for the long-range generation expansion planning, which provides a comparable accuracy with much less computational effort than the conventional one. A completely new analytical approach for the production costing model and reliability measures is developed by using the original load curve under the assumption of Gaussian probability distribution of random load fluctuations and plant outages. The analytical formulae are derived not only for operating costs and reliability measures, but also for their marginal values. A new algorithm to determine the optimal use of available hydro resources is developed based on the analytical production costing model and its extension is also presented for the generation planning problem. The long-range generation investment problem is formulated as an optimal control problem to determine optimally the annual investment in new generating capacity. This formulation reduces thw size of optimization problem in the order of magnitude to yearly Hamiltonian minimization problem, which is solved by using a version of the gradient projection method.



Electric power consumption--Forecasting, Electric power systems