Pricing Strategies for User-Provided Connectivity Services

User-provided connectivity (UPC) services offer a possible alternative, orcomplement, to existing infrastructure-based connectivity. A userallows other users to occasionally connect through its home base inexchange for reciprocation, or possibly compensation. This service modelexhibits strong positive and negative externalities. A large user basemakes the service more attractive, as it offers more connectivity options toroaming users, but it also implies a greater volume of (roaming) trafficpassing through a user\u27s home base, which can increase congestion. Theseinteractions make it difficult to predict the eventual success of such aservice offering, and in particular how to effectively price it. This paperinvestigates a two-price policy where the first price is an introductory price that expires onceservice adoption reaches a certain level. The paper uses a simplifiedanalytical model to investigate pricing strategies under this policy, and their sensitivity to changesin system parameters. The insight and practicalguidelines this yields are validated numerically under morerealistic conditions

Small-Scale Markets for Bilateral Resource Trading in the Sharing Economy

We consider a general small-scale market for agent-to-agent resource sharing, in which each agent could either be a server (seller) or a client (buyer) in each time period. In every time period, a server has a certain amount of resources that any client could consume, and randomly gets matched with a client. Our target is to maximize the resource utilization in such an agent-to-agent market, where the agents are strategic. During each transaction, the server gets money and the client gets resources. Hence, trade ratio maximization implies efficiency maximization of our system. We model the proposed market system through a Mean Field Game approach and prove the existence of the Mean Field Equilibrium, which can achieve an almost 100% trade ratio. Finally, we carry out a simulation study motivated by an agent-to-agent computing market, and a case study on a proposed photovoltaic market, and show the designed market benefits both individuals and the system as a whole

Market Methods for Supply and Demand Management in the Smart Grid

This study addresses the resource management problem in a large scale networked system with high flexibility. We consider the supply and demand management problem specifically in the context of the future Smart Grid. On the supply side, we design a secondary market to provide stochastic energy service via distributed renewable energy resources. The performance of the proposed market is evaluated in two circumstances, i.e. whether or not the extra energy penetration caused by the market changes the operation point of the power grid. On the demand side, we would like to take the advantages of the residential demand flexibility to relieve consumption peaks and stabilize the system. We conduct certain demand response in a market approach and further build a real experiment system to analyze the performance of such regime. The study of supply side market is referred to the subheading: Small-Scale Markets for a Bilateral Energy Sharing Economy followed by an extension of the corresponding market which brings in the concern that the increased energy penetration may change the operation point of the grid. As for the demand side study, design and analysis of such demand response market is under the subheading: Mean Field Games in Nudge Systems for Societal Networks and the real experiment built-up is presented in Incentive-Based Demand Response: Empirical Assessment and Critical Appraisal. We model the agent behaviour in both markets via game theoretic approach and analyze the equilibrium performance. We show that a Mean Field Game regime can be applied to accurately approximate these repeated game frameworks and socially desirable equilibria that benefit both system operator and agents exist