The smart grid is an
electricity grid augmented with digital technologies
that automate the management of electricity delivery.
The smart grid is
envisioned to be a main enabler of sustainable, clean, efficient, reliable, and
secure energy supply.
One of the milestones in the smart grid vision
will be programs for
customers to participate
in electricity markets through demand-side management
distributed generation; electricity markets will (directly or indirectly)
customers to adapt their demand to supply conditions, which in turn
will help to utilize intermittent energy resources such as
from solar and wind, and to reduce peak-demand.
Since wholesale electricity markets are not designed for individual
participation, retail brokers
could represent customer populations
in the wholesale market,
and make profit while contributing to the electricity grid's stability and reducing customer costs.
A retail broker will need to operate continually and make real-time
decisions in a complex, dynamic environment.
benefit from employing
an autonomous broker agent.
With this motivation in mind,
this dissertation makes five main contributions to the
areas of artificial intelligence, smart grids, and electricity markets.
First, this dissertation formalizes the problem of autonomous trading by a
retail broker in modern electricity markets.
Since the trading problem is intractable to solve exactly, this formalization
provides a guideline
for approximate solutions.
Second, this dissertation introduces a general algorithm for autonomous trading
in modern electricity markets, named LATTE (Lookahead-policy for Autonomous
Time-constrained Trading of Electricity). LATTE is a general framework that can
be instantiated in different ways that tailor it to specific setups.
Third, this dissertation contributes fully implemented and operational
autonomous broker agents, each using a different instantiation of LATTE. These
agents were successful in international competitions and controlled
experiments and can serve as benchmarks for future research in this
domain. Detailed descriptions of the agents' behaviors as well as their source
code are included in this dissertation.
Fourth, this dissertation contributes extensive empirical analysis which
validates the effectiveness of LATTE in different competition levels under a
variety of environmental conditions, shedding light on the main reasons for its
success by examining the importance of its constituent components.
Fifth, this dissertation examines the impact of Time-Of-Use (TOU) tariffs in
competitive electricity markets through empirical analysis. Time-Of-Use tariffs
are proposed for demand-side management both in the literature and
in the real-world.
The success of the different instantiations of LATTE demonstrates its generality
in the context of electricity markets. Ultimately, this dissertation
demonstrates that an autonomous broker can act effectively in modern electricity
markets by executing an efficient lookahead policy that optimizes its predicted
utility, and by doing so the broker can benefit itself, its customers, and the
Code available at: http://www.cs.utexas.edu/~urieli/thesis
Dissertation PDF linked under PDF below.
Slides linked under Slides below.
PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Code and binaries available at: http://www.cs.utexas.edu/~urieli/thesis.