6,283 research outputs found
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Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets
Presents an overview and analysis of the possible approaches to bringing an active demand side into electricity markets. Part of a series of research reports that examines energy issues facing California
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Advanced Metering and Demand Responsive Infrastructure: A Summary of the PIER / CEC Reference Design, Related Research and Key Findings
A Reliable and Cost-Efficient Auto-Scaling System for Web Applications Using Heterogeneous Spot Instances
Cloud providers sell their idle capacity on markets through an auction-like
mechanism to increase their return on investment. The instances sold in this
way are called spot instances. In spite that spot instances are usually 90%
cheaper than on-demand instances, they can be terminated by provider when their
bidding prices are lower than market prices. Thus, they are largely used to
provision fault-tolerant applications only. In this paper, we explore how to
utilize spot instances to provision web applications, which are usually
considered availability-critical. The idea is to take advantage of differences
in price among various types of spot instances to reach both high availability
and significant cost saving. We first propose a fault-tolerant model for web
applications provisioned by spot instances. Based on that, we devise novel
auto-scaling polices for hourly billed cloud markets. We implemented the
proposed model and policies both on a simulation testbed for repeatable
validation and Amazon EC2. The experiments on the simulation testbed and the
real platform against the benchmarks show that the proposed approach can
greatly reduce resource cost and still achieve satisfactory Quality of Service
(QoS) in terms of response time and availability
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Meter Scoping Study
This report presents a summary of metering technology and cost information from past studies in an attempt to identify key barriers to more widespread implementation
HIL: designing an exokernel for the data center
We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or
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Connecticut Light and Power C&LM Programs/Residential Load Management Services Program: 2002 Summer and Winter Thermostat Pilot Programs Impact Evaluation Report
Load Shifting in the Smart Grid: To Participate or Not?
Demand-side management (DSM) has emerged as an important smart grid feature
that allows utility companies to maintain desirable grid loads. However, the
success of DSM is contingent on active customer participation. Indeed, most
existing DSM studies are based on game-theoretic models that assume customers
will act rationally and will voluntarily participate in DSM. In contrast, in
this paper, the impact of customers' subjective behavior on each other's DSM
decisions is explicitly accounted for. In particular, a noncooperative game is
formulated between grid customers in which each customer can decide on whether
to participate in DSM or not. In this game, customers seek to minimize a cost
function that reflects their total payment for electricity. Unlike classical
game-theoretic DSM studies which assume that customers are rational in their
decision-making, a novel approach is proposed, based on the framework of
prospect theory (PT), to explicitly incorporate the impact of customer behavior
on DSM decisions. To solve the proposed game under both conventional game
theory and PT, a new algorithm based on fictitious player is proposed using
which the game will reach an epsilon-mixed Nash equilibrium. Simulation results
assess the impact of customer behavior on demand-side management. In
particular, the overall participation level and grid load can depend
significantly on the rationality level of the players and their risk aversion
tendency.Comment: 9 pages, 7 figures, journal, accepte
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