Consider an electricity market populated by competitive agents using thermal generating units. Generation often emits pollution which a planner may wish to constrain through regulation. Furthermore, generators’ ability to transmit energy may be naturally restricted by the grid’s facilities....

Computing the solution to a stochastic optimal control problem is difficult. A method of approximating a solution to a given stochastic optimal control problem using Markov chains was developed in [1]. This paper describes a suite of MATLAB functions implementing this method of approximating a...

A powerful method for computing Nash equilibria in constrained, multi-player games is created when the relaxation algorithm and the Nikaido-Isoda function are used together in a suite of MATLAB routines. This paper updates the MATLAB suite described in \cite{Berridge97} by adapting them to...

Computing a numerical solution to a periodic optimal control problem is difficult. A method of approximating a solution to a given (stochastic) optimal control problem using Markov chains was developed in [3]. This paper describes an attempt at applying this method to a periodic optimal control...

This paper describes a suite of MATLAB routines devised to provide an approximately optimal solution to an infinite-horizon stochastic optimal control problem. The suite is an updated version of that described in [Kra01b]. Its routines implement a policy improvement algorithm to optimise a...

Consider an electricity market populated by competitive agents using thermal generating units. Such generation involves the emission of pollutants, on which a regulator might impose constraints. Transmission capacities for sending energy may naturally be restricted by the grid facilities. Both...

In this report, we outline a method for approximating a Markovian (or feedback-Nash) equilibrium of a dynamic game, possibly subject to coupled-constraints. We treat such a game as a "multiple" optimal control problem. A method for approximating a solution to a given optimal control problem via...