Unions Power, Collective Bargaining and Optimal Monetary Policy

We study Ramsey policies and optimal monetary policy rules in a model with sticky prices and unionized labour markets. Collective wage bargaining and unions monopoly power dampen wage fluctuations and amplify employment fluctuations relatively to a DNK model. The optimal monetary policy must trade-off between stabilizing inflation and reducing inefficient unemployment fluctuations induced by unions' monopoly power. In this context the monetary authority uses inflation as a tax on unions' rents. The optimal monetary policy rule targets unemployment alongside inflation.

Implementation of Adaptive Critic-Based Neurocontrollers for Turbogenerators in a Multimachine Power System

This paper presents the design and practical hardware implementation of optimal neurocontrollers that replace the conventional automatic voltage regulator (AVR) and the turbine governor of turbogenerators on multimachine power systems. The neurocontroller design uses a powerful technique of the adaptive critic design (ACD) family called dual heuristic programming (DHP). The DHP neurocontroller\u27s training and testing are implemented on the Innovative Integration M67 card consisting of the TMS320C6701 processor. The measured results show that the DHP neurocontrollers are robust and their performance does not degrade unlike the conventional controllers even when a power system stabilizer (PSS) is included, for changes in system operating conditions and configurations. This paper also shows that it is possible to design and implement optimal neurocontrollers for multiple turbogenerators in real time, without having to do continually online training of the neural networks, thus avoiding risks of instability

Making the Power Grid More Intelligent

Summary form only given. This paper focuses on the applications of intelligent techniques for improving the performances of the power system controllers. Intelligent control techniques lay the foundation of the next generation of nonlinear controllers and have the advantage of further improving the controller\u27s performance by incorporating heuristics and expert knowledge into its design. Most of these techniques are independent of any mathematical model of the power system, which proves to be a considerable advantage

Excitation and Turbine Neurocontrol with Derivative Adaptive Critics of Multiple Generators on the Power Grid

Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multiple generators on the electric power grid are presented. The feedback variables are completely based on local measurements. Simulations on a three-machine power system demonstrate that the neurocontrollers are much more effective than conventional PID controllers, the automatic voltage regulators and the governors, for improving the dynamic performance and stability under small and large disturbance