2015 54th IEEE Conference on Decision and Control (CDC) 2015
DOI: 10.1109/cdc.2015.7402711
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Scenario-based model predictive operation control of islanded microgrids

Abstract: Abstract-We propose a model predictive control (MPC) approach for the operation of islanded microgrids that takes into account the stochasticity of wind and load forecasts. In comparison to worst case approaches, the probability distribution of the prediction is used to optimize the operation of the microgrid, leading to less conservative solutions. Suitable models for time series forecast are derived and employed to create scenarios. These scenarios and the system measurements are used as inputs for a stochas… Show more

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Cited by 45 publications
(56 citation statements)
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“…Fig. 3c depicts the internal frequencies and active power ratios of the MG, controlled with strategy (20). It can be observed that the steady state frequency error of unit 1 and at the busbar goes to zero.…”
Section: ) Pinning Gain At All Units No Consensus-based Exchange Ofmentioning
confidence: 96%
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“…Fig. 3c depicts the internal frequencies and active power ratios of the MG, controlled with strategy (20). It can be observed that the steady state frequency error of unit 1 and at the busbar goes to zero.…”
Section: ) Pinning Gain At All Units No Consensus-based Exchange Ofmentioning
confidence: 96%
“…Note that only the internal frequencyω i is available to every unit. Furthermore, ω d ∈ R is the frequency set point, k i ∈ R >0 the droop coefficient, P d i ∈ R the active power set point from a higher control level, e.g, energy management [20], and ξ i ∈ R is the control input. The measured active power P m i ∈ R is obtained by filtering the power output P i in (1) by a first order low pass filter with time constant τ i ∈ R >0 .…”
Section: Droop Controlled Unitsmentioning
confidence: 99%
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