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Chance-constrained scheduling model of grid-connected microgrid based on probabilistic and robust optimisation
2018
IET Generation, Transmission & Distribution
This study presents a chance-constrained scheduling model based on probabilistic and robust optimisation to handle the uncertainty of renewable energy generation and loads in microgrids. In order to generate appropriate scenarios, a large number of scenarios are generated by a Latin hypercube sampling Monte Carlo method and reduced by a fast forward selection algorithm. With the aggregated scenarios, a probabilistic scheduling model is established to obtain the expectation of schedules in
doi:10.1049/iet-gtd.2017.1039
fatcat:4h5hf2cpkjfpxityby2xrdd55a