Abstract
In this chapter, probability and stochastic programming methods are given. Firstly, the principle of probability and stochastic process is introduced, including random variables, multivariate random variables, the stochastic process and its time-varying probability distribution and correlation, the basic operation of multistate probability distribution, etc. Secondly, the basic theory of stochastic programming is introduced, including the probability index of risk value and conditional risk value, the mixed probability optimization model of stochastic and deterministic decision variables, the probability optimization solution method based on multistate probability distribution, the sequence operation of multistate probability distribution, and the fast Fourier calculation method. Finally, probability and stochastic programming methods are introduced. The probabilistic model, nonsequential production simulation model, and optimal planning model of renewable energy output, such as wind power/photovoltaic, which are often used in stochastic programming models, are given. The solution method of the probabilistic optimal planning model considering random variables is introduced.
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