Yusuke Okajima

A dynamic mechanism for LQG power networks with random type parameters and pricing delay

We consider a dynamic game model of power networks with generators and/or consumers, called agents, and one public commission, called utility; a game with a prescribed dynamic mechanism is performed such that each agent decides a private control to minimize its own cost functional, and the utility manages information transmissions between the utility and agents and decides command signals, called prices, to minimize a public cost functional. We discuss designs of the mechanism that integrates strategic determinations of private controls by the agents into the optimal public controls that achieve the optimal social welfare and rational agents can accept. The model of this paper is a generic linear Gaussian model of power networks, which is motivated by so-called average system frequency models; in each model of the agents, we includes the type parameter presenting each agents private information; we also consider the time delay in calculation of prices by utility. Assuming that each private cost functional as well as the public cost functional is quadratic, we derive formulas of the pricing schemes, and the incentive cost, inspired by the pivot function in the mechanism design theory literate from economics, that characterize our mechanism design in both formulations of the fixed horizon control and the receding horizon control cases.

Real time pricing and pivot mechanism for LQG power networks

We consider a dynamic game model of power networks with generators and/or consumers, called agents, and one public commission, called utility; a game with a prescribed dynamic mechanism is performed such that each agent decides a private control to minimize its own cost functional, and the utility manages information transmissions between the utility and agents and decides command signals, called prices, to minimize a public cost functional. We discuss designs of the mechanism that integrates selfish and strategic determinations of private controls by the agents into the optimal public controls that rational agents can accept. The model considered in this paper is the linear models of power networks, which is a special case of the model so-called average system frequency models, but we also include white Gaussian disturbances in each dynamic model of the agents in order to take account into the stochastic nature of renewable resources. Assuming that each private cost functional as well as the public cost functional is quadratic, we derive explicit formulas of the command signalling scheme, i.e., pricing scheme, and the incentive cost, inspired by the pivot function in the mechanism design theory literate from economics, that characterize our mechanism design in both formulations of the fixed horizon control and the receding horizon control cases.

Strategic behavior and market power of aggregators in energy demand networks

This paper considers optimization problems of energy demand networks including aggregators and investigates strategic behavior of the aggregators. The energy demand network including aggregators will be optimized through pricing. Under this optimization process, the aggregator acts as intermediate between energy supply sources and a large number of consumers and is expected to moderate tasks to solve a large scale optimization problem. We propose an optimization process that uses information exchange or aggregation by the aggregators, which is actually an intermediate model of the well-known two extremal models. From the consumers point of view, the aggregator is expected to have enough negotiation power on behalf of the consumers. This will be a main theme of this paper and we investigate strategic behavior of the aggregators. We suppose that the aggregator will try to pursue the benefit as well as market power by choosing the design parameter in its cost function. The strategic decision making by the aggregators could provide useful insights in qualitative analysis of the energy demand network, and the results of numerical example indicate that, for example, oligopoly by the aggregator may not be beneficial to the consumers.

Real-time pricing for LQG power networks with independent types: A dynamic mechanism design approach

Abstract We investigate dynamic integration mechanisms for a power network system using a technique from economic theory. We represent a power network consisting of agents who are the generators and consumers and one public commission, called the utility, as a dynamic game. The game has a prescribed dynamic mechanism and each agent exercises private control to minimize the costs according to a personal cost functional, while the utility chooses prices to minimize the costs according to a public cost functional and manages information transmission. The model of this paper is a generic linear Gaussian power network model in which each agent has a type parameter representing private information. In this setting, inspired by the pivot function from mechanism design theory in economics, we design dynamic mechanisms that integrate the strategic determination of private controls by rational agents into the optimal public controls with real-time pricing and monetary transfer costs. Two dynamic integration mechanisms, which together achieve all of social welfare maximization, incentive compatibility, and individual rationality, are proposed based on the cost functional and the Hamiltonian. The effectiveness of the proposed mechanisms are assessed through simulations. Specifically, we have shown that an agent’s fictitious report produces a loss for the agent’s benefit in the both cases of the cost functional and the Hamiltonian.

Proceedings of the IEEE Conference on Decision and Control

We consider a dynamic game model of power networks with generators and/or consumers, called agents, and one public commission, called utility. A game with a prescribed dynamic mechanism is performed such that each agent decides private control to minimize his own cost functional, and the utility decides prices to minimize a public cost functional and manages information transmissions. The model of this paper is a generic linear Gaussian model of power networks in which each agent has a type parameter with ones private information. In this setting, inspired by the incentive cost in the mechanism design theory from economics, we discuss designs of a mechanism that integrates strategic determinations of private controls by the rational agents into optimal public control that achieve social welfare maximization, Bayesian incentive compatibility and budget balance. Two dynamic balanced integration mechanisms are proposed in both formulations of the fixed horizon and the receding horizon cases.

Dynamic balanced integration mechanism for LQG power networks with independent types

We consider a dynamic game model of power networks with generators and/or consumers, called agents, and one public commission, called utility. A game with a prescribed dynamic mechanism is performed such that each agent decides private control to minimize his own cost functional, and the utility decides prices to minimize a public cost functional and manages information transmissions. The model of this paper is a generic linear Gaussian model of power networks in which each agent has a type parameter with ones private information. In this setting, inspired by the incentive cost in the mechanism design theory from economics, we discuss designs of a mechanism that integrates strategic determinations of private controls by the rational agents into optimal public control that achieve social welfare maximization, Bayesian incentive compatibility and budget balance. Two dynamic balanced integration mechanisms are proposed in both formulations of the fixed horizon and the receding horizon cases.