Citation
Jonathon Martin, Ian Hiskens. "Corrective Model-Predictive Control in Large Electric Power Systems". IEEE Transactions on Power Systems, 2017.

Abstract
Enhanced control capabilities are required to coordinate the response of increasingly diverse controllable resources, including FACTS devices, energy storage, demand response and fast-acting generation. Model-predictive control (MPC) has shown great promise for accommodating these devices in a corrective control framework that exploits the thermal overload capability of transmission lines and limits detrimental effects of contingencies. This work expands upon earlier implementations by incorporating voltage magnitudes and reactive power into the system model utilized by MPC. These improvements provide a more accurate prediction of system behavior and enable more effective control decisions. Performance of this enhanced MPC strategy is demonstrated using a model of the Californian power system containing 4259 buses. Sparsity in modelling and control actions must be exploited for implementation on large networks. A method is developed for identifying the set of controls that is most effective for a given contingency. The proposed MPC corrective control algorithm fits naturally within energy management systems where it can provide feedback control or act as a guide for system operators by identifying beneficial control actions across a wide range of devices.

Electronic downloads

• 07536196.pdf · application/pdf · 1280 kbytes

• HTML

  Jonathon Martin, Ian Hiskens. <a
  href="http://www.cps-forces.org/pubs/220.html"
  >Corrective Model-Predictive Control in Large Electric
  Power Systems</a>, <i>IEEE Transactions on Power
  Systems</i>,  2017.

• Plain text

  Jonathon Martin, Ian Hiskens. "Corrective
  Model-Predictive Control in Large Electric Power
  Systems". <i>IEEE Transactions on Power
  Systems</i>,  2017.

• BibTeX

  @article{MartinHiskens17_CorrectiveModelPredictiveControlInLargeElectricPower,
      author = {Jonathon Martin and Ian Hiskens},
      title = {Corrective Model-Predictive Control in Large
                Electric Power Systems},
      journal = {IEEE Transactions on Power Systems},
      year = {2017},
      abstract = {Enhanced control capabilities are required to
                coordinate the response of increasingly diverse
                controllable resources, including FACTS devices,
                energy storage, demand response and fast-acting
                generation. Model-predictive control (MPC) has
                shown great promise for accommodating these
                devices in a corrective control framework that
                exploits the thermal overload capability of
                transmission lines and limits detrimental effects
                of contingencies. This work expands upon earlier
                implementations by incorporating voltage
                magnitudes and reactive power into the system
                model utilized by MPC. These improvements provide
                a more accurate prediction of system behavior and
                enable more effective control decisions.
                Performance of this enhanced MPC strategy is
                demonstrated using a model of the Californian
                power system containing 4259 buses. Sparsity in
                modelling and control actions must be exploited
                for implementation on large networks. A method is
                developed for identifying the set of controls that
                is most effective for a given contingency. The
                proposed MPC corrective control algorithm fits
                naturally within energy management systems where
                it can provide feedback control or act as a guide
                for system operators by identifying beneficial
                control actions across a wide range of devices.},
      URL = {http://cps-forces.org/pubs/220.html}
  }
  

Posted by Ian Hiskens on 28 Feb 2017.
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