25,410 research outputs found
Holistic Measures for Evaluating Prediction Models in Smart Grids
The performance of prediction models is often based on "abstract metrics"
that estimate the model's ability to limit residual errors between the observed
and predicted values. However, meaningful evaluation and selection of
prediction models for end-user domains requires holistic and
application-sensitive performance measures. Inspired by energy consumption
prediction models used in the emerging "big data" domain of Smart Power Grids,
we propose a suite of performance measures to rationally compare models along
the dimensions of scale independence, reliability, volatility and cost. We
include both application independent and dependent measures, the latter
parameterized to allow customization by domain experts to fit their scenario.
While our measures are generalizable to other domains, we offer an empirical
analysis using real energy use data for three Smart Grid applications:
planning, customer education and demand response, which are relevant for energy
sustainability. Our results underscore the value of the proposed measures to
offer a deeper insight into models' behavior and their impact on real
applications, which benefit both data mining researchers and practitioners.Comment: 14 Pages, 8 figures, Accepted and to appear in IEEE Transactions on
Knowledge and Data Engineering, 2014. Authors' final version. Copyright
transferred to IEE
Cooperation and Storage Tradeoffs in Power-Grids with Renewable Energy Resources
One of the most important challenges in smart grid systems is the integration
of renewable energy resources into its design. In this work, two different
techniques to mitigate the time varying and intermittent nature of renewable
energy generation are considered. The first one is the use of storage, which
smooths out the fluctuations in the renewable energy generation across time.
The second technique is the concept of distributed generation combined with
cooperation by exchanging energy among the distributed sources. This technique
averages out the variation in energy production across space. This paper
analyzes the trade-off between these two techniques. The problem is formulated
as a stochastic optimization problem with the objective of minimizing the time
average cost of energy exchange within the grid. First, an analytical model of
the optimal cost is provided by investigating the steady state of the system
for some specific scenarios. Then, an algorithm to solve the cost minimization
problem using the technique of Lyapunov optimization is developed and results
for the performance of the algorithm are provided. These results show that in
the presence of limited storage devices, the grid can benefit greatly from
cooperation, whereas in the presence of large storage capacity, cooperation
does not yield much benefit. Further, it is observed that most of the gains
from cooperation can be obtained by exchanging energy only among a few energy
harvesting sources
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Scenarios for the development of smart grids in the UK: synthesis report
‘Smart grid’ is a catch-all term for the smart options that could transform the ways society produces, delivers and consumes energy, and potentially the way we conceive of these services. Delivering energy more intelligently will be fundamental to decarbonising the UK electricity system at least possible cost, while maintaining security and reliability of supply.
Smarter energy delivery is expected to allow the integration of more low carbon technologies and to be much more cost effective than traditional methods, as well as contributing to economic growth by opening up new business and innovation opportunities. Innovating new options for energy system management could lead to cost savings of up to £10bn, even if low carbon technologies do not emerge. This saving will be much higher if UK renewable energy targets are achieved.
Building on extensive expert feedback and input, this report describes four smart grid scenarios which consider how the UK’s electricity system might develop to 2050. The scenarios outline how political decisions, as well as those made in regulation, finance, technology, consumer and social behaviour, market design or response, might affect the decisions of other actors and limit or allow the availability of future options. The project aims to explore the degree of uncertainty around the current direction of the electricity system and the complex interactions of a whole host of factors that may lead to any one of a wide range of outcomes. Our addition to this discussion will help decision makers to understand the implications of possible actions and better plan for the future, whilst recognising that it may take any one of a number of forms
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