Efficiency-risk tradeoffs in dynamic oligopoly markets with application to electricity markets

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 87-90).In an abstract framework, we examine how a tradeoff between efficiency and risk arises in different dynamic oligopolistic markets. We consider a scenario where there is a reliable resource provider and agents which enter and exit the market following a random process. Self-interested and fully rational agents can both produce and consume the resource. They dynamically update their load scheduling decisions over a finite time horizon, under the constraint that the net resource consumption requirements are met before each individual's deadline. We first examine the system performance under the non-cooperative and cooperative market architectures, both under marginal production cost pricing of the resource. The statistics of the stationary aggregate demand processes induced by the two market architectures show that although the non-cooperative load scheduling scheme leads to an efficiency loss - widely known as the "price of anarchy" - the stationary distribution of the corresponding aggregate demand process has a smaller tail. This tail, which corresponds to rare and undesirable demand spikes, is important in many applications of interest. With a better understanding of the efficiency-risk tradeoff, we investigate, in a non-cooperative setup, how resource pricing can be used as a tool by the system operator to tradeoff between efficiency and risk. We further provide a convex characterization of the Pareto front of different system performance measures. The Pareto front determines the tradeoff among volatility suppression of concerned measurements in the system with load scheduling dynamics. This is the fundamental tradeoff in the sense that system performance achieved by any load scheduling strategies induced by any specific market architectures is bounded by this Pareto front.by Qingqing Huang.S.M

Intelligent Decision Support System for Energy Management in Demand Response Programs and Residential and Industrial Sectors of the Smart Grid

This PhD thesis addresses the complexity of the energy efficiency control problem in residential and industrial customers of Smart electrical Grid, and examines the main factors that affect energy demand, and proposes an intelligent decision support system for applications of demand response. A multi criteria decision making algorithm is combined with a combinatorial optimization technique to assist energy managers to decide whether to participate in demand response programs or obtain energy from distributed energy resources

Energieeffizienz in Büroumgebungen

The increasing cost of energy and the worldwide desire to reduce CO2 emissions has raised concern about the energy efficiency of information and communication technology. Whilst research has focused on data centres recently, this thesis identifies office computing environments as significant consumers of energy. Office computing environments offer great potential for energy savings: On one hand, such environments consist of a large number of hosts. On the other hand, these hosts often remain turned on 24~hours per day while being underutilised or even idle. This thesis analyzes the energy consumption within office computing environments and suggests an energy-efficient virtualized office environment. The office environment is virtualized to achieve flexible virtualized office resources that enable an energy-based resource management. This resource management stops idle services and idle hosts from consuming resources within the office and consolidates utilised office services on office hosts. This increases the utilisation of some hosts while other hosts are turned off to save energy. The suggested architecture is based on a decentralized approach that can be applied to all kinds of office computing environments, even if no centralized data centre infrastructure is available. The thesis develops the architecture of the virtualized office environment together with an energy consumption model that is able to estimate the energy consumption of hosts and network within office environments. The model enables the energy-related comparison of ordinary and virtualized office environments, considering the energy-efficient management of services. Furthermore, this thesis evaluates energy efficiency and overhead of the suggested approach. First, it theoretically proves the energy efficiency of the virtualized office environment with respect to the energy consumption model. Second, it uses Markov processes to evaluate the impact of user behaviour on the suggested architecture. Finally, the thesis develops a discrete-event simulation that enables the simulation and evaluation of office computing environments with respect to varying virtualization approaches, resource management parameters, user behaviour, and office equipment. The evaluation shows that the virtualized office environment saves more than half of the energy consumption within office computing environments, depending on user behaviour and office equipment.Die steigenden Kosten von Energie und die weltweiten Bemühungen CO2-Emmissionen zu reduzieren, führt aktuell zu einer intensiven Untersuchung der Energieeffizienz von Informations- und Kommunikationstechnologien. Während ein großer Teil der aktuellen Forschung sich auf Rechenzentren fokussiert, betrachtet diese Arbeit Büroumgebungen mit ihren Rechnern und dem verbindenden Netzwerk. Eine energieeffiziente Architektur wird vorgeschlagen, die auf die Virtualisierung und Konsolidierung von Diensten setzt, ohne auf zentralisierte Rechenzentrumshardware oder Thin Clients angewiesen zu sein