Can planners control competitive generators?

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. The existence of both pollution standards and transmission constraints can impose several restrictions upon the joint strategy space of the agents. We propose a dynamic, game-theoretic model capable of analysing coupled constraints equilibria (also known as generalised Nash equilibria). Our equilibria arise as solutions to the planner’s problem of avoiding both network congestion and excessive pollution. The planner can use the coupled constraints’ Lagrange multipliers to compute the charges the players would pay if the constraints were violated. Once the players allow for the charges in their objective functions they will feel compelled to obey the constraints in equilibrium. However, a coupled constraints equilibrium needs to exist and be unique for this modification of the players’ objective functions ..[there was a “to” here, incorrect?].. induce the required behaviour. We extend the three-node dc model with transmission line constraints described in [10] and [2] to utilise a two-period load duration curve, and impose multi-period pollution constraints. We discuss the economic and environmental implications of the game’s solutions as we vary the planner’s preferences.

Structured Linearization of Discrete Mechanical Systems for Analysis and Optimal Control

Variational integrators are well-suited for simulation of mechanical systems because they preserve mechanical quantities about a system such as momentum, or its change if external forcing is involved, and holonomic constraints. While they are not energy-preserving they do exhibit long-time stable energy behavior. However, variational integrators often simulate mechanical system dynamics by solving an implicit difference equation at each time step, one that is moreover expressed purely in terms of configurations at different time steps. This paper formulates the first- and second-order linearizations of a variational integrator in a manner that is amenable to control analysis and synthesis, creating a bridge between existing analysis and optimal control tools for discrete dynamic systems and variational integrators for mechanical systems in generalized coordinates with forcing and holonomic constraints. The forced pendulum is used to illustrate the technique. A second example solves the discrete LQR problem to find a locally stabilizing controller for a 40 DOF system with 6 constraints.Comment: 13 page

Structured Linearization of Discrete Mechanical Systems for Analysis and Optimal Control

Variational integrators are well-suited for simulation of mechanical systems because they preserve mechanical quantities about a system such as momentum, or its change if external forcing is involved, and holonomic constraints. While they are not energy-preserving they do exhibit long-time stable energy behavior. However, variational integrators often simulate mechanical system dynamics by solving an implicit difference equation at each time step, one that is moreover expressed purely in terms of configurations at different time steps. This paper formulates the first- and second-order linearizations of a variational integrator in a manner that is amenable to control analysis and synthesis, creating a bridge between existing analysis and optimal control tools for discrete dynamic systems and variational integrators for mechanical systems in generalized coordinates with forcing and holonomic constraints. The forced pendulum is used to illustrate the technique. A second example solves the discrete LQR problem to find a locally stabilizing controller for a 40 DOF system with 6 constraints.Comment: 13 page

The invisible polluter: Can regulators save consumer surplus?

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 pollution standards and trans mission capacities can impose several constraints upon the joint strategy space of the agents. We propose a coupled constraints equilibrium as a solution to the regulator’s problem of avoiding both congestion and excessive pollution. Using the coupled constraints’ Lagrange multipliers as taxation coefficients the regulator can compel the agents to obey the multiple constraints. However, for this modification of the players’ payoffs to induce the required behaviour a coupled constraints equilibrium needs to exist and must also be unique. A three-node market example with a dc model of the transmission line constraints described in [8] and [2] possesses these properties. We extend it here to utilise a two-period load duration curve and, in result, obtain a two-period game. The implications of the game solutions obtained for several weights, which the regulator can use to vary the level of generators’ responsibilities for the constraints’ satisfaction, for consumer and producer surpluses will be discussed.

A primer on moral-hazard models

Bank supervision