A survey on present applications of stochastic optimization in the power industry is presented. In particular, the motivation for changing over from deterministic to stochastic optimization models, the theory of stochastic optimization and the implementation of risk aversion is described. Furthermore, several characteristic applications in the power industry, such as short-term unit commitment, middle-term portfolio optimization, long-term investment planning and emissions-trading, are discussed
© Springer International Publishing Switzerland 2016. This chapter presents major modelling and simu...
International audienceManagement of electricity production to control cost while satisfying demand, ...
A large scale stochastic linear programming model, called s-MTSIM, has been developed to solve the u...
We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. ...
The DASH model for Power Portfolio Optimization provides a tool which helps decision-makers coordina...
We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. ...
Optimization models have been widely used in the power industry to aid the decision-making process o...
In this thesis steps are described to determine the locations of new wind mills which minimize energ...
This paper introduces the optimization algorithm selection for the bids formation in deregulated mar...
A formulation for the commitment of electric power generators under a deregulated electricity market...
The topicality of the task of power systems regimes optimization is significantly improved under the...
We present a mathematical model with stochastic input data for mean-risk optimization of electricity...
We develop a two-stage stochastic integer programming model for the simultaneous optimization of pow...
This paper addresses the scenario reduction for stochastic optimization applied to short-term tradin...
Using a stochastic programming approach, we consider portfolio management problems in the electricit...
© Springer International Publishing Switzerland 2016. This chapter presents major modelling and simu...
International audienceManagement of electricity production to control cost while satisfying demand, ...
A large scale stochastic linear programming model, called s-MTSIM, has been developed to solve the u...
We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. ...
The DASH model for Power Portfolio Optimization provides a tool which helps decision-makers coordina...
We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. ...
Optimization models have been widely used in the power industry to aid the decision-making process o...
In this thesis steps are described to determine the locations of new wind mills which minimize energ...
This paper introduces the optimization algorithm selection for the bids formation in deregulated mar...
A formulation for the commitment of electric power generators under a deregulated electricity market...
The topicality of the task of power systems regimes optimization is significantly improved under the...
We present a mathematical model with stochastic input data for mean-risk optimization of electricity...
We develop a two-stage stochastic integer programming model for the simultaneous optimization of pow...
This paper addresses the scenario reduction for stochastic optimization applied to short-term tradin...
Using a stochastic programming approach, we consider portfolio management problems in the electricit...
© Springer International Publishing Switzerland 2016. This chapter presents major modelling and simu...
International audienceManagement of electricity production to control cost while satisfying demand, ...
A large scale stochastic linear programming model, called s-MTSIM, has been developed to solve the u...