Distributed chance-constrained optimal power flow based on primary frequency control
Pages 366 - 374
Abstract
We propose a fully distributed algorithm to solve the Chance Constrained Optimal Power Flow (CCOPF), with the advantages of ensuring the privacy and autonomy of the different operators and actors of the system. We present, in this paper, a two-step algorithm that, first, carries out a distributed sensitivity analysis to obtain the generalized generation distribution factors. With these sensitivity factors, the second step solves a distributed CCOPF based on an analytical formulation relying on the Primary Frequency Control (PFC) of generators and on wind farms, whose forecast errors are assumed to be Gaussian. This algorithm allows us to schedule margins and reserves to ensure the security of the system regarding wind farms deviation from forecast with probabilistic guarantees, and to assess the cost of this uncertainty. The proposed method has been implemented and tested on a two-bus test system with one wind farm, and on the IEEE 14-bus test system, with two wind farms. Simulation results showed that the proposed algorithm can efficiently solve the CCOPF in a fully distributed manner.
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Index Terms
- Distributed chance-constrained optimal power flow based on primary frequency control
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June 2018
657 pages
ISBN:9781450357678
DOI:10.1145/3208903
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Published: 12 June 2018
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