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A Generalized Framework for Chance-constrained Optimal Power Flow. (arXiv:1803.08299v1 [math.OC])
来源于:arXiv
Deregulated energy markets, demand forecasting, and the continuously
increasing share of renewable energy sources call---among others---for a
structured consideration of uncertainties in optimal power flow problems. The
main challenge is to guarantee power balance while maintaining economic and
secure operation. In the presence of Gaussian uncertainties affine feedback
policies are known to be viable options for this task. The present paper
advocates a general framework for chance-constrained OPF problems in terms of
continuous random variables. It is shown that, irrespective of the type of
distribution, the random-variable minimizers lead to affine feedback policies.
Introducing a three-step methodology that exploits polynomial chaos expansion,
the present paper provides a constructive approach to chance-constrained
optimal power flow problems that does not assume a specific distribution, e.g.
Gaussian, for the uncertainties. We illustrate our findings by means of a
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