Citation
Alberto Puggelli, Alberto Sangiovanni-Vincentelli, Sanjit Seshia. "Robust Strategy Synthesis for Probabilistic Systems Applied to Risk-Limiting Renewable-Energy Pricing". Internal Conference on Computer-Aided Verification (CAV) 2014, 18, July, 2014; In Submission.

Abstract
The use of economic incentives has been proposed to manage user demand in smart grids that integrate renewable sources of energy to compensate for the intrinsic uncertainty in the prediction of the supply generation. We address the problem of synthesizing optimal energy pricing strategies, while quantitatively constraining the risk due to uncertainty for the network operator and guaranteeing quality-of-service for the users. We use Ellipsoidal Markov Decision Processes (EMDP) to model the decision-making scenario. These models are trained with measured data and allow to quantitatively capture the uncertainty in the prediction of energy generation. We then cast the constrained optimization problem as the strategy synthesis problem for EMDPs, with the goal to maximize the total expected reward constrained to properties expressed using the Probabilistic Computation Tree Logic (PCTL), and propose a novel sound and complete synthesis algorithm. An experimental comparison shows the effectiveness of our method with respect to previous approaches presented in the literature.

Electronic downloads

• https://www.src.org/library/publication/p069481/. (Link to paper on SRC website.)
• http://dx.doi.org/10.1145/2656045.2656069

• HTML

  Alberto Puggelli, Alberto Sangiovanni-Vincentelli, Sanjit
  Seshia. <a
  href="http://www.terraswarm.org/pubs/274.html"
  >Robust Strategy Synthesis for Probabilistic Systems
  Applied to Risk-Limiting Renewable-Energy Pricing</a>,
  Internal Conference on Computer-Aided Verification (CAV)
  2014, 18, July, 2014; In Submission.

• Plain text

  Alberto Puggelli, Alberto Sangiovanni-Vincentelli, Sanjit
  Seshia. "Robust Strategy Synthesis for Probabilistic
  Systems Applied to Risk-Limiting Renewable-Energy
  Pricing". Internal Conference on Computer-Aided
  Verification (CAV) 2014, 18, July, 2014; In Submission.

• BibTeX

  @inproceedings{PuggelliSangiovanniVincentelliSeshia14_RobustStrategySynthesisForProbabilisticSystemsApplied,
      author = {Alberto Puggelli and Alberto
                Sangiovanni-Vincentelli and Sanjit Seshia},
      title = {Robust Strategy Synthesis for Probabilistic
                Systems Applied to Risk-Limiting Renewable-Energy
                Pricing},
      booktitle = {Internal Conference on Computer-Aided Verification
                (CAV) 2014},
      day = {18},
      month = {July},
      year = {2014},
      note = {In Submission.},
      abstract = {The use of economic incentives has been proposed
                to manage user demand in smart grids that
                integrate renewable sources of energy to
                compensate for the intrinsic uncertainty in the
                prediction of the supply generation. We address
                the problem of synthesizing optimal energy pricing
                strategies, while quantitatively constraining the
                risk due to uncertainty for the network operator
                and guaranteeing quality-of-service for the users.
                We use Ellipsoidal Markov Decision Processes
                (EMDP) to model the decision-making scenario.
                These models are trained with measured data and
                allow to quantitatively capture the uncertainty in
                the prediction of energy generation. We then cast
                the constrained optimization problem as the
                strategy synthesis problem for EMDPs, with the
                goal to maximize the total expected reward
                constrained to properties expressed using the
                Probabilistic Computation Tree Logic (PCTL), and
                propose a novel sound and complete synthesis
                algorithm. An experimental comparison shows the
                effectiveness of our method with respect to
                previous approaches presented in the literature.},
      URL = {http://terraswarm.org/pubs/274.html}
  }
  

Posted by Alberto Puggelli on 20 Feb 2014.