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Revue de presse IoT / Data / Energie du 02/04/2017
Bonjour,
Voici la revue de presse IoT/data/energie du 2 avril 2017.
Cette semaine moins d’articles, mais de très intéressantes analyses sur le futur des
entreprises de distribution d’électricité. Un futur a composer avec plus de renouvelables,
de micro voire nano-grids, et des technologies qui vont dans le sens de la
désintermédiation. Avec en trame de fond (et en dernier article) l’importance du mix IOT x
data x intelligence artificielle.
C’est long mais ça vaut le coup, alors bonne lecture !
1. How Blockchain Tech Will Create a Distributed Future for the Energy Sector
2. Nanogrids, Microgrids, and Big Data: The Future of the Power Grid
3. Innovative Technologies Driving the Energy Revolution
4. Blockchain 2.0 dans l'énergie vue par France Stratégie
5. How Will Artificial Intelligence Improve the Internet of Things?
How Blockchain Tech Will Create a
Distributed Future for the Energy Sector
Source URL: http://bitcoinmagazine.com/articles/how-blockchain-tech-will-create-
distributed-future-energy-sector/
Mar 27, 20171:45 PM EST by Michael Scott
April 2016 saw a flurry of media attention around thefirst ever blockchain-managed
energy transaction in Brooklyn, NY.In this groundbreaking milestone, the owner of a roof
solar panel sold a few kilowatt-hours of excess energy to a neighbor utilizing an Ethereum
blockchain smart contract. Fueling this development via the Brooklyn microgrid was the
startup company LO3 Energy.
Today power and utility companies all over the world are now exploring various ways to
implement blockchain technology. Doing so could upend existing models of how energy
and utility markets function. Applied on a broader scale, it could be the spark that
transforms these legacy industries.
So what sort of problems is blockchain technology expected to address in this space?
For starters, the technology is seen as a means of overcoming some of the entry barriers
that restrict the delivery of electricity to more customers. Here the blockchain
infrastructure could foster a more open and transparent mechanism for codifying
transactions in the energy realm involving both generation and consumption.
Second, blockchain technology can provide companies in these industries with a more
efficient way to record and process data, potentially leading to a more synchronized
global distribution of energy. Customers would also be afforded a more streamlined and
accurate experience in terms of managing their bills and access to the activity taking
place on their accounts.
Third, the archaic and costly function of meter reading could effectively be eliminated
while at the same time boosting the accuracy of bills.
Finally, blockchain integration can provide a more effective system for assessing energy
sources and determining how that affects the pricing passed on to the consumer. Better
technology tools provide more accurate energy utilization and service data, ultimately
leading to better outcomes for the end customer.
The broader implications of this would include increased industry competition leading to
lower prices, streamlined energy distribution, reduced energy waste and better
relationships between utility companies and their customers.
For a deeper perspective on blockchain technology’s emerging impact on the power,
utilities and energy markets, Bitcoin Magazine turned to Thierry Mortier, Global Leader of
Technology and Innovation for Power and Utilities at Ernst & Young (EY).
Mortier says that the power sector is in the midst of shifting from a centralized model to a
more distributed model. He believes that in the future new digital peer-to-peer platforms
will emerge to eliminate the middleman and seamlessly connect energy producers directly
with the end power user.
“Blockchain technology will help facilitate this process by allowing transactions to be
recorded between two parties efficiently and in a verifiable and permanent way. It can also
be programmed to trigger transactions automatically. The technology promises to
radically speed up transactions and cut costs by establishing trust and the transfer of
value without the involvement of traditional intermediaries.”
Mortier goes on to note that, aside from some early demonstrations, the applicability of an
energy blockchain is still largely theoretical. He points to how blockchain enthusiasts are
drawn in by the growing complex web of transactions, the need to balance the
geographical mismatch between supply and demand, and significant security and trust
concerns given the proliferation of Internet of Things (IoT) connected devices.
Says Mortier: “Over 200 blockchain use cases have been identified already. Most pilots
are still in early stages across the energy value chain, primarily in the area of peer-to-peer
energy trading. EY is working with companies in the power and utilities sector to develop
use cases and prototypes.”
In addition to the aforementioned April 2016 development, where residents in Brooklyn,
New York, successfully traded renewable energy using a smart contract on the public
Ethereum blockchain platform, he says that in Australia, several pilots are under way,
allowing residents in Perth and South Western Australia to buy, sell or swap excess solar
energy with anyone connected to the Western Power network.
Furthermore, he says that Germany, with Berlin as the global hub of the technology, has a
strong presence, as does the U.K., building on the early investment of the financial
services sector in the technology. “Blockchain maturity seems to be driven by company
ambition rather than any national advantage at this stage,” says Mortier.
He is especially excited about the emergence of pre-programmed “smart contracts” that
can trigger transactions automatically.
“These smart contracts, for example, can be set to allow prosumers to feed surplus
energy into the grid through a blockchain-enabled meter. The flow of electricity is
automatically coded into the blockchain, and algorithms match buyers and sellers in real
time based on preferences. Smart contracts then execute when electricity is delivered,
triggering payment from buyer to seller. Removing financial transactions and the
execution of contractual commitments from central control brings a whole new level of
decentralization and transparency that the industry has never had before.”
Mortier also touts the rapidly growing prominence of energy trading, an area he says
appears to be moving toward a commercial solution more quickly than many of the
others.
In conclusion, Mortier says that there has been significant interest in tracking and tracing
resource types (green gas, for example) and in the peer-to-peer, prosumer-led trading.
But, outside of Bitcoin applications, he laments that there is a lack of proven use cases,
with difficulties involving security, scalability and frequency of transactions as factors that
need to be overcome.
“In three to five years’ time, it is quite possible that blockchain [technology] will radically
change the way parts of the power industry operate. To get there, blockchain [technology]
must overcome competition from existing solutions and prove its attractiveness to users.
Only if its applications have tangible, monetary or timely advantages will blockchain
[technology] be able convince enough participants to ditch their legacy systems for this
new platform.”
Nanogrids, Microgrids, and Big Data: The
Future of the Power Grid
Source URL: http://spectrum.ieee.org/energy/renewables/nanogrids-microgrids-and-
big-data-the-future-of-the-power-grid
Distributed generation and automated transactions will
change how we produce and consume electricity
Developing technology is like driving a race car:You push the machinery as fast as it’ll
go, and if you can avoid a crash, a prize awaits you at the finish line. For engineers, the
reward is sometimes monetary, but more often it’s the satisfaction of seeing the world
become a better place.
Thanks to many such engineers driving many such race cars, a lot of progress is about to
happen in an unexpected spot: the electricity sector. The power grid’s interlocking
technological, economic, and regulatory underpinnings were established about a century
ago and have undergone only minimal disruption in the decades since. But now the
industry is facing massive change.
Most observers are only vaguely aware of the magnitude of this overhaul, perhaps
because it’s a hard story to tell. It doesn’t translate well to a set of tweets. Many people
have come to think of the electric-utility business in much the same way they think of their
taxes—boring, tedious, and somehow, always costing more money.
What’s happening in this industry stems from technology improvements, economic
forces, and evolving public priorities. As the changes dig away at the very foundation of
the electricity sector, the results are likely to be anything but boring. Yet they may well
cost you more money.
For about a century, affordable electrification has been based on economies of scale, with
large generating plants producing hundreds or thousands of megawatts of power, which
is sent to distant users through a transmission and distribution grid. Today, many
developments are complicating that simple model.
At the top of the list is the availability of low-cost natural gas and solar power. Generators
based on these resources can be built much closer to customers. So we are now in the
early stages of an expansion of distributed generation, which is already lessening the
need for costly long-distance transmission. That, in turn, is making those new sources
cost competitive with giant legacy power plants.
Distributed generation has long been technically possible. What’s new now is that we are
nearing a tipping point, beyond which, for many applications, distributed generation will
be the least costly way to provide electricity.
While it certainly helps, the declining cost of renewables and gas-fired electricity is not all
that’s spurring this change. To be competitive, the entire distributed system will have to
work well as a whole. Quite a few technological advances are coming together to make
that possible: advanced control systems; more compact, smarter, and efficient electrical
inverters; smart electricity meters and the burgeoning Internet of Things; and the ever-
growing ability to extract actionable information from big data.
Global Total Installed Wind and Solar Capacity
Growth in wind and solar has been brisk. The two together represent roughly 10 percent
of the world’s installed capacity but contribute only about 4 percent of production.
Amid this changing scene, a picture is beginning to emerge of what a typical electrical
grid may well look like in 10 or 20 years in most of the developed world. Yes, generation
will be much more decentralized, and renewables such as solar and wind will proliferate.
But other aspects are also shifting. For example, the distribution network—the part of the
grid to which your home and business connect—will likely become more of a negotiating
platform than a system that just carries electricity from place to place.
Getting to this more sophisticated grid won’t be easy. Nevertheless, it’s coming. What will
it look like? Here is my best guess, based on my decades of experience as a government
official charged with helping electric utilities get access to emerging technologies. It is the
future I’m now working to help realize as an academic researcher.
The first thing to understand is that decentralization is going to be neither simple nor
universal. In some places, decentralization will prevail, with most customers generating
much of their own power, typically from solar photo​voltaics. Others might use small-scale
wind turbines. In regions where sunlight and wind are less plentiful, natural gas will
probably predominate. Intertwined among all of those, a continuously improving version
of the legacy grid will survive for decades to come.
According to the U.S. Energy Information Administration (EIA), in the first 11 months of
2016, some 48.82 million megawatt-hours of distributed solar energy were produced in
the country, up 46 percent from the year before. That’s still a tiny proportion, though. In
2016, about 1.4 percent of electricity in the United States came from the sun via solar
panels, including both utility-scale plants and distributed ones, according to the EIA. But
solar is growing fast because of its increasingly favorable economics. For example, in
Chile’s most recent power auction, 120 MW of solar power was the lowest-cost option, at
US $29.10 per megawatt-hour.
Many analysts expect that grid-connected, distributed solar power will be fully cost
competitive with conventional forms of generation by the end of this decade. In the
meantime, a dizzying array of government incentives, which vary from region to region
(even within one country) are helping the technology to take off.
Ultimately, the lowest-cost form of generation will dominate. But figuring out what the
lowest-cost option actually is will be tricky because it will depend on both local conditions
and local decisions.
For example, regulators are increasingly convinced that the burning of fossil fuels leads to
significant societal costs, both from the direct exposure of those living near some power
plants to their noxious emissions and from ​greenhouse gas induced climate change.
Historically, these costs were difficult to quantify. So they were typically borne not by the
producers or consumers of the electricity but by the victims—for example, farmers whose
crops were damaged.
There is growing public interest in understanding the true cost of pollution and possibly
shifting more of it to electricity producers and possibly consumers as well. Fortunately, we
now have the modeling and computational capabilities to begin to put a reasonable lower
limit on those costs, which gives us a defensible way to reallocate them.
Although the best strategies for reallocating those costs are still being debated, the
benefits of distributed renewable generation are already very apparent—as is the
feasibility. Data collected during the Pecan Street Project, funded by the U.S. Department
of Energy, indicates that a house in Austin, Texas, outfitted with solar panels typically
generates 4 or 5 kilowatts during the midday hours of a sunny day in summer, which
exceeds the amount of power the home typically uses during such a period.
Illustration: MCKIBILLO
A typical smart home has an energy-management system that takes into account time of
day and other factors to minimize electricity costs. In a future microgrid, the individual
energy-management systems of a group of homes will communicate to maximize
efficiency, lower costs, and regulate demand.
Whether or not rooftop solar makes sense for a particular homeowner, however, depends
on the initial cost, maintenance costs, subsidies, the cost of grid power, and the selling
price of the excess electricity generated.
The U.S. Department of Energy’s SunShot initiative has as its goal making solar power
cost competitive—without subsidies—by 2030. (A Chinese government agency has a
similar agenda.) Specifically, SunShot’s goal is to reduce the cost of distributed,
residential solar power to 5 U.S. cents per kilowatt-hour by 2030; it costs about 18 cents
today. Today, a 6-kW rooftop residential solar system in the United States typically costs
between $15,000 and $20,000; the exact figure depends on where you live. According to
data from the EIA, the average retail cost of electricity delivered by the grid in the United
States is 12.5 cents per kilowatt-hour. So at 18 cents, rooftop-generated solar is not yet,
on average, competitive with grid-delivered electricity. But many governments, for
example U.S. state governments, subsidize the purchase of solar-power systems to make
them competitive.
Meanwhile, many utilities are experimenting with ​alternative-ownership options. One is
community solar, in which individual consumers buy a small number of panels in a
relatively large, utility-scale system. They then get monthly credits for the electricity
generated without having panels on their roofs. Another experiment, being run by CPS
Energy, in San Antonio, uses rooftop solar, but CPS Energy owns the equipment and pays
the homeowner for the use of the roof.
One challenge with distributed solar is storage. Most solar-panel owners are using the
grid as the functional equivalent of storage: They sell excess power to the grid when they
can and buy back from the grid to compensate for shortfalls. This is usually the simplest
and cheapest way to even out differences in production and consumption. Nevertheless,
many people—most notably, Elon Musk—are betting the economics will soon favor
batteries. Musk’s ​electric-car company, Tesla, sells a battery for home use called
Powerwall 2, which costs $5,500 and offers 14 kWh of storage, enough to run an average
home overnight. However, adding the costs of battery storage to a solar installation to go
off grid makes the costs of power significantly higher than those of ordinary electricity
from the grid.
Comparing the options for expanding the use of solar power is not straightforward,
however, because much depends on how the grid will evolve. For example, right now, the
grid could not handle a changeover to 100 percent solar (even in areas where it would
make sense, like the southwestern United States or the North African desert). The grid we
have today was designed around sources whose output generally varies little from day to
day. But the U.S. DOE, under its ENERGISE program, is striving to develop, by 2030, the
control, protection, and other technologies needed to enable an entirely solar-powered
grid.
The grid will evolve in other ways, too, and quickly. One of the most important trends,
already well under way, is the increasing use of microgrids. A microgrid is a group of
connected power sources and loads. It can be as small as an individual house (often
dubbed a nanogrid) or as large as a military base or college campus. Microgrids can
operate indefinitely on their own and can quickly isolate themselves if a disturbance
destabilizes the larger grids to which they are normally connected.
This is an important feature during both natural and man-made disasters. Consider what
happened when Hurricane Ike hit the Houston-Galveston area of Texas in 2008: Blackouts
were widespread, but 95 percent of the outages were caused by damage to less than 5
percent of the grid. The grid effectively distributed the effects of what was only modest
equipment damage.
Illustration: MCKIBILLO
A residential microgrid connects a group of homes that have their own power sources and
energy storage. The homes communicate with each other wirelessly and connect to the
main grid at a distribution transformer. In an electrical disturbance, the microgrid can
protect itself by disconnecting from the main grid at that transformer.
This isolating capability of microgrids also promises enhanced cybersecurity. That’s
because microgrids can help keep localized intrusions local, making the grid a much less
appealing target for hackers.
When disaster strikes, whatever its cause, microgrids can limit the consequences. If it is
not physically damaged, a microgrid can operate as long as it has access to a source of
power, whether that’s natural gas, the sun, or wind.
In the long term, with the timing depending as much on economics and regulation as
technology, it is quite possible that the grid will evolve into a series of adjoining
microgrids. Utilities have proposed to build such microgrid “clusters” in, among other
places, Chicago, Pittsburgh, and Taiwan, a tropical island where grids are prone to storm
damage. These adjoining microgrids would share power with one another and with the
legacy grid to minimize energy cost and to maximize availability.
In an era of adjoining microgrids that are privately owned and operated, what will become
of the utility company? There are at least two possibilities. It might simply supply power to
the microgrids that need it, rather than doing that for individual customers. Or it might
manage microgrids and their connections with one another and to the legacy grid. Across
the United States, the concept of a utility is already being reinvented in some places as
more competition is introduced. Microgrids are going to accelerate that trend.
The spread of distributed generation and the rise of microgrids will also be shaped by two
other factors: the expansion of the Internet of Things and the growing influence of big
data.
The Internet of Things is a boon for distributed generation because it is giving rise to
industries that are ​mass-producing sensors, microcontrollers, software, and other gear
that will be easily and cheaply adaptable for use in future, data-driven grids and
microgrids. How will these things be used? Imagine a residential solar-power system of
the near future. It will have “customer equipment”—solar panels, a smart inverter, and a
storage battery and systems to manage loads dynamically. From time to time, the power
output of that installation will be lower than usual, because of, say, a heavily overcast day.
But it would be easy to design a control system, based on readily available IoT
components, that could communicate with similar systems in surrounding houses. These
systems would work together, for example, to turn air conditioners on or off ahead of or
behind schedule, or alter their thermostats by half a degree, to accommodate intermittent,
unexpected shortfalls in capacity. What would enable this plan to work is the fact that
most modern homes are well insulated, so it takes time before the internal temperature
changes enough to trigger the HVAC system. The reason why homes would be grouped
together in this scheme is that it would make the task easier: In the group, some
homeowners would be willing to sacrifice a lot of comfort, some less. But the power
needs of the group of houses would be relatively predictable and manageable, from the
utility’s standpoint.
Most consumers do not want to make frequent and detailed decisions on energy use. So
imagine a device—let’s call it an energy thermostat—that permits you to set a range of
comfortable temperatures, rather than entering a single one. The wider you set the range,
the less you’ll pay for power. The grid or microgrid operator would use the range—yours
and everybody else’s—to dynamically match supply and demand on a minute-by-minute
basis. On a hot afternoon, with demand at its peak, the temperature in your home would
be at the top of the range.
A distribution substation connects the microgrid to the distribution network and therefore
to the main grid, through a set of transformers and disconnect switches.
Electric utilities will also begin making greater and much more effective use of big data.
Utilities have been using data since the very beginning: When Thomas Edison opened the
Pearl Street power station, in New York City in 1882, it had indicator lights to show when
the load had increased or decreased enough to warrant adjustments to the dynamo
producing the DC power. But that system clearly was not scalable. If a utility had to
readjust its generators every time a customer came online, the industry would have died
out long ago.
Having a large number of loads makes the aggregate demand predictable—and
manageable. This happy condition obviously depends on there being little correlation of
usage from house to house and business to business. But just suppose that at 3:00 p.m.
on a hot summer day, everyone in a medium-size city turned off their air conditioners at
the very same second, waited 15 minutes, and then turned them all back on again at
exactly the same time. That would almost certainly cause a massive blackout.
With big-data tools, it may no longer be necessary to depend on consumers’ actions
being only loosely similar. It should be possible to understand how to adjust production
and consumption to enhance system behavior. For example, with the energy-thermostat
concept outlined above, the system operator needs to have not only the appropriate
controllers but also access to real-time data to determine the risk of system failure when
load-management actions are taken.
Utilities in many areas have embarked on this path using various customer incentives to
permit, say, time-of-day pricing or some other form of load management by the utility
rather than by the consumer. But we are now taking just baby steps. Big-data tools will
soon let us take larger strides and may well one day let us run. It may be possible to use
real-time operational data to optimize the performance of large sections of the grid and to
predict future performance.
Although my main goal is to describe a hopeful vision that many of us in the utility
business have for the electric grid, I would be remiss if I did not point out some of the
challenges. These include financial ones, regulatory ones, and technical ones. And they
come in all shapes and sizes.
One of the most fundamental is slow growth. To pay for costly system upgrades, utilities
in the past would have relied heavily on growth in demand, and therefore sales. But
improvements in efficiency, which consumers seek (and rightly so), have slowed growth in
demand to the extent that it is now increasing at a rate lower than that of the growth in
gross domestic product. And the figures are sobering: In 2014, the U.S. DOE predicted
that in the period from 2012 to 2040, the demand for electricity will grow by only
0.9 percent per year. So, utilities cannot expect to fund the required system changes in
the same ways as they have in the past, through growth.
Other shifts in the industry will only exacerbate these money woes. For example, in the
past utilities could count on key pieces of equipment lasting a long time. But smart grids
depend on electronic components, such as smart meters, controlled by software, which
have shorter lifetimes and require much more frequent upgrades.
The biggest unknown is how swiftly the regulatory process can adapt. If it can’t move
quickly enough to keep up with the technology, expect agonizingly slow change. And
what if governments try to prop up outmoded technologies with subsidies? That could
drag out the process further. On the other hand, some would argue that regulators should
slow the rate of change. Though the arguments for that are worthy of political discussion,
I’m certainly not in that camp.
Historically, regulations have been driven mainly by legal and economic considerations
rather than by technical ones. But now, with the pace of technology outrunning other
factors, regulators in the United States and Europe are reacting to this new state of affairs
in many different ways. My view is that the staffing of regulatory agencies will need to
become more technically savvy if we are to navigate these turbulent waters while
continuing to provide electric power with the lowest cost and highest reliability.
I’m confident that in the end, we’ll have electrical grids that are less costly, more
sustainable, and more user friendly than the ones that came before. The United States’
National Academy of Engineering recently selected electrification as the top engineering
accomplishment of the 20th century. But electrification now needs to be reengineered to
meet the needs and opportunities of the 21st century. This is our chance to show that we
are as good as our forebears of two, three, or four generations ago at technology,
regulation, public policy, finance, and the management of change in general. And to leave
to posterity a legacy as fine and enduring as the one that was left to us.
About the Author
Robert Hebner is the director of the Center for Electromechanics at the University of
Texas at Austin.
Innovative Technologies Driving the
Energy Revolution
Source URL: http://breakingenergy.com/2017/03/31/innovative-technologies-driving-
energy-revolution-solar-power-measurement-efficiency/
Two explosive growth markets are renewable energy (RE) and the Internet of Things (IoT)
technologies and both play a crucial role in creating value. The emphasis on how software
and analytics can drive energy savings along with renewable energy and energy
conservation measures (ECM) will be examined. Companies, like Arkados, exist that
operate in the solar (through its recently announced acquisition of SolBright Renewable
Energy), LED lighting, and IoT markets.
Market
The IoT market is demonstrating substantial growth. According to McKinsey, the IoT
market should grow from $900 million in 2015 to $3.7 billion by 2020. One of the key
drivers of the IoT market is smart building applications where energy savings provides the
return on investment (ROI). IoT applications play a leading role in renewable energies in
including solar and wind.
Global investment spending in the solar PV markets was $161 billion in 2015, according
to Bloomberg New Energy Finance. GTM Research and the Solar Energy Industry
Association (SEIA) indicated that the US solar industry grew 95% to 42.4 gigawatts (GW)
in 2016. According to the SEIA, the US solar market installed 14.6 GW of solar PV in
2016. In the global market, approximately 73 GW of solar was added in 2016.
However, when solar is measured against conventional energy sources such as natural
gas and coal, solar represents approximately 1% of the energy generation in the US
according to DOE. Despite the successful growth of solar in the US market, there is
substantial upside for further growth. Fueling the solar market growth are falling PV panel
costs and the extension of tax credits. Solar PV panel costs are at grid parity in most
states. Solar power generation at a cost of approximately $0.13 per kWh is close to the
US national average rate at $0.115 per kWh.
Technology Positioning
Solar costs at grid parity should be great news for commercial and residential
applications as well as for the utility industry itself. However, renewable energy has
limitations, and therefore, new technologies employing IoT devices and analytics can
further enhance the market for solar and drive higher energy efficiency. These
technologies apply to buildings and utility markets where tools and technology are
required to better manage electric supply and demand. This image depicts how IoT can
be employed in various objects to enhance energy data.
One issue for renewable energies is that their ability to generate power is intermittent.
Because renewable energy is intermittent, energy storage is a crucial component to
enable the distributed grid where electric supply has to match demand. Energy storage is
a critical component of the distributed grid architecture. The ability to store energy is
important to improve RE value and to provide power when RE sources are not available.
The US grid was built to generate electricity from fuels such as natural gas, coal, hydro
and nuclear and transmit electric to substation for distribution to customers. Utilities
globally are implementing micro and distributed generation grids meaning they are
introducing electric generation at end points in the network. Solar generates energy and
without the ability to derive granular insight in energy supply and demand, energy can be
wasted. This is one area of focus for IoT connected devices and analytical software.
In addition, Net Metering, a process that credits the owners of solar generation systems
for power added to the grid, helps solar become more attractive for customers. Several
states including Arizona, California, Colorado, Connecticut, Delaware, Maryland,
Massachusetts, New Hampshire, New Jersey, New York, Ohio, Oregon, and Pennsylvania
have implemented net metering.
Arkados, and other like companies, are employing IoT devices and software to enhance
value of renewable energy and facility operations. These technologies include energy and
environmental sensors that enable diagnostic feedback loops to compare energy
efficiency to facility conditions and set points.
Part of the process is educational to demonstrate the feasibility and viability into an
organization. Some concepts are simple such as performance bench-marking to identify
aberrant conditions or major areas of concern. Key metrics include energy density in kW
and kWh per square foot. Facility load factors and equipment load signature are also
helpful is comparing procedural operating hours to measured operating hours by
equipment.
Some of the approaches include fog analytics such as pushing intelligence to the edge of
the network using IoT devices to capture granular detail and enable local processing and
control. The concept is to push context awareness to the sensors and collect data in the
process. This process includes remote control on lighting and equipment. The real
benefits from IoT and analytics are huge including reducing costs, increasing energy
efficiency, asset protection, and predictive maintenance.
Value
The value of energy savings must be within a two-year payback to gain acceptance by
the market. In other words, the RE and ECM investment ROI should be greater than 50%.
To achieve energy savings insight, generate data from an array of sensors at a granular
level. Meaning continuous monitoring of sensor data that can be used to enhance energy
performance. Typical energy savings initiatives would include cutting back at peak kW
demand and duration and can be used to substantially reduce energy costs. Conditioning
less outside air is effective in reducing HVAC costs. Modulating outside air intake using
demand control ventilation employing CO2 sensors is an effective energy savings
method. Demand Control Ventilation has been able to demonstrate HVAC efficiency
gains of 24%.
Automated measurement and verification (M&V) systems provide mechanism to deploy
demand response. Some studies suggest demand response has the potential to reduce
energy costs by 40%. Monitoring based commissioning (MBCx) can save money simply
by measuring consumption to set point changes in and facility environmental conditions.
The futuristic approach is to combine energy monitoring with sales and installation of LED
lighting and solar PV systems.
Conclusion
Energy savings and efficiency gains measure the value created through IoT and analytics.
With the rise of both of these initiatives, consumers should be more aware of their energy
consumption in the near future as more of this technology is available to them. Software
developed by companies provides a means of enhancing the benefits of solar and LED
lighting by gaining insight into energy consumption in addition to enabling efficiency
optimization using diagnostic feedback loops. Today, consumers should focus on
leveraging software and IoT capabilities to drive sustainability and improve energy
efficiency for solar and LED lighting initiatives.
Blockchain 2.0 dans l'énergie vue par
France Stratégie
Source URL: https://www.energystream-wavestone.com/2017/03/blockchain-energie-
france-strategie/
Le jeudi 9 mars, nous avons eu l’opportunité d’assister à une table ronde organisée par
France Stratégie autour de la blockchain, ses enjeux et les obstacles qu’elle rencontre
dans le secteur de l’énergie. Pierre Paperon (fondateur de l’Observatoire Blockchains des
Energies) était le principal intervenant de cette conférence.
Compte-rendu d’une matinée riche en enseignements.
Vers une blockchain 2.0
Initialement, la blockchain permet de sécuriser des transactions par le chiffrement des
données et de faciliter les échanges en supprimant les tiers de confiance entre de
multiples utilisateurs. De ce fait, elle permet de faire des échanges directement de pair à
pair (peer-to-peer) et donc de se passer de plus en plus d’intermédiaires durant les
transactions.
Cette blockchain 1.0 se développe aujourd’hui et ses champs d’action s’élargissent. A un
niveau de maturité naissant, on parle alors de blockchain 2.0. Mais quelles sont ses
fonctions concrètement ?
La blockchain 2.0 intègre les “smart contracts” ou “contrats à exécution automatique” qui
sont des clauses programmées pour exécuter des actions spécifiques. Le contrat est
prédéfini à l’avance sous forme de code informatique par les deux parties. Lorsque les
conditions spécifiées dans le contrat sont remplies, la transaction est réalisée
automatiquement par la blockchain sans intervention humaine. Il est important de noter
que les smart contracts ne peuvent pas être modifiés a posteriori de leur implémentation
sur la blockchain. Il est donc crucial de s’assurer que le contrat ne comporte pas de faille
exploitable par un acteur malveillant. Ce genre de faille a notamment été exploitée lors du
hack de The DAO[1].
Quels cas d’usage dans le secteur de l’énergie ?
La disparition des tiers de confiance fait de la blockchain une technologie prometteuse en
faveur de la décentralisation de l’industrie de l’énergie. Cette décentralisation englobe
l’ensemble des acteurs actuels, en réinstaurant cependant une dynamique locale plus
forte. Les usages de la blockchain sont particulièrement pertinents pour deux aspects de
la gestion de l’énergie : la production et le stockage.
Revue des principaux use-cases envisagés de la blockchain dans le secteur de l’énergie :
Production d’énergie
L’achat d’électricité se fait généralement via un fournisseur qui agit comme instance
centrale de gestion de la production et de la consommation. Les échanges à une échelle
locale seraient facilités par l’utilisation d’une blockchain : les producteurs, rémunérés par
des jetons convertibles en crypto-monnaie ou en « crédits énergie » seraient directement
en contact avec les consommateurs. Ce système est d’ores et déjà mis en place dans le
quartier de Brooklyn à New York. L’optimisation de l’utilisation de batteries domestiques
est aussi envisagée.
De la même façon que pour l’électricité, des réseaux de gaz locaux pourraient voir le jour
grâce à la blockchain (apparition d’un crypto-m3).
Conversion énergétique
Lors d’un pic de production d’électricité (qui a pour effet de déstabiliser le réseau),
l’énergie excédante peut être utilisée afin de chauffer de l’eau ou de produire du gaz
(power-to-gaz).Ce surplus d’énergie pourrait être géré par une blockchain et un smart
contract : en cas de pic de production, une installation serait automatiquement redirigée
vers un circuit de chauffage ou de production de gaz.
Gestion des déchets
L’utilisation de nano-méthaniseurs est également très prometteuse : ceux-ci se mettraient
automatiquement en marche en cas de forte demande en gaz. Ces nano-méthaniseurs
pourraient être installés chez des particuliers (10 kg de compost produisent 5 m3 de
méthane). Un système de récompense pourrait également être mis en place à l’échelle
d’une commune : les citoyens participant au tri sélectif seraient récompensés par une
crypto-monnaie convertible en devise réelle ou en crédits énergie.
Si la blockchain a dans un premier temps attiré l’attention des acteurs du secteur
financier, ses apports dans l’énergie sont aussi conséquents. Elle pourrait constituer un
véritable vecteur de développement de la décentralisation du marché énergétique et
instaurer un fonctionnement sans tiers de confiance qui privilégie les économies locales.
Cela pourrait s’avérer particulièrement dangereux pour certains grands acteurs actuels
(notamment les fournisseurs).
De nouveaux acteurs et une nouvelle chaîne de valeur
De nouveaux acteurs apparaîtront avec l’émergence de la blockchain. En effet, une mise
en commun des ressources à travers un troc 2.0 est envisageable.
La question de la souveraineté de la blockchain est donc cruciale : le statut de l’opérateur
(privé, public) et son rôle précis dans la gestion du registre partagé sont à définir. Il devra
notamment s’assurer de l’adossement des crypto-monnaies à des monnaies réelles (cf.
Tramonex Ltd au Royaume-Uni, qui adosse une quinzaine de crypto-monnaies au pound)
et du bon fonctionnement de la blockchain.
Quid de la législation ?
Outre la question des opérateurs, de nombreuses interrogations émergent en termes de
législation.
La première concerne l’encadrement juridique de la blockchain car à ce jour, aucune loi ni
norme n’existent à son sujet. Il existe donc un vide juridique qui représente une menace
dans la mesure où les limites – contraintes à son exploitation ne sont pas fixées. Pour
pallier ce vide, l’évolution jurisprudentielle est capitale. De plus, de nombreux enjeux
métiers apparaissent : qui doit s’assurer de la conformité de la blockchain d’un point de
vue juridique ? Le juriste deviendra-t-il développeur ou le développeur deviendra-t-il
juriste ? Enfin, il y a également un enjeu lié à la propriété industrielle. Il est important de
souligner que nous assistons aujourd’hui à la montée du « patent trolling[3] », notamment
aux Etats-Unis. Cela nous amène donc à nous poser la question suivante : devons-nous
déposer des brevets pour éviter d’être bloqués par la suite ou pour innover ?
La technologie blockchain à un niveau industriel n’étant pas encore assez mature, ces
quatre grandes questions demeurent aujourd’hui sans réponse. Cependant, nous devons
nous y intéresser dès aujourd’hui afin de préparer le futur de la blockchain en France.
Conclusion
La blockchain est une technologie qui suscite de nombreux débats et sur laquelle les avis
divergent. Apporte-t-elle plus de souplesse dans les échanges ou plus de complexité ?
Quel est son coût ? Est-elle si avantageuse pour tous les secteurs et cas d’usages ?
La blockchain est vouée à se répandre – notamment dans le secteur de l’énergie – et il y a
de nombreuses opportunités pour la France car notre futur sera rempli d’objets
connectés. Il est crucial pour la France de prendre le virage blockchain avant que d’autres
pays ne se l’approprient. La Chine est en position de précurseur : elle héberge plus de
50% de la puissance de calcul du bitcoin, envisage la création d’une crypto-monnaie
adossée au yuan et a explicitement inscrit la blockchain dans son plan quinquennal. Les
Etats-Unis, quant à eux, n’ont pas encore pris de mesures importantes. En revanche, la
France semble prendre le virage : le 13 juillet 2016, la CRE a publié une ordonnance à
propos de l’autoconsommation qui se projette vers une réglementation pour la
blockchain.
[1] Pour plus d’informations au sujet de The DAO, voir :
http://www.coindesk.com/understanding-dao-hack-journalists/
[2] Le patent trolling est la pratique d’un groupement d’avocats déposant un grand
nombre de brevets non exploités, en vue d’empêcher toute autre entreprise souhaitant
utiliser une technologie en lien avec ce brevet et n’en disposant pas, de développer sa
solution. Il existe donc une menace, notamment américaine, si l’on souhaite se
développer sur la blockchain sur le volet de la propriété industrielle.
How Will Artificial Intelligence Improve
the Internet of Things?
Source URL: http://www.iotevolutionworld.com/iot/articles/430775-how-will-artificial-
intelligence-improve-internet-things.htm
By Special Guest Megan Ray Nichols, Special Correspondent, Science Writer March 28,
2017
From DVRs and smart fridges to smartphones and voice-activated technology, the
Internet of Things (IoT) is quickly becoming part of our daily lives. These devices are
capable of collecting thousands of bytes of data every single day, and companies are
hoarding that data in the hopes that predictive algorithms will be able to glean some
insight from them. How will artificial intelligence improve the Internet of Things?
The Introduction of AI
Artificial intelligence has gotten a very bad reputation, courtesy of science-fiction novels
and movies. When most people think of AI, their mind conjures images of HAL 9000 from
“2001: A Space Odyssey” or Skynet from the “Terminator” series. While a truly sentient AI
might create a threat if not properly regulated, machine-learning algorithms are the
foundation of artificial intelligence.
The idea behind machine learningis to create computers that can learn without being
programmed. It’s already being used on small scales — your Netflix show
recommendations, for example, are a basic form of machine learning. The program
analyzes the shows and movies you watch and uses that data to provide you with new
choices.
Incorporating AI into IoT
Machine learning is already taking its first steps into the world of IoT. Self-driving cars are
one of the biggest IoT devices, and even cars that only offer partial autopilot capabilities
like the Tesla rely heavily on machine learning. You can program a self-driving car so it
knows the basic rules of the road and how to handle the most common obstacles it might
come across. When you introduce other drivers into the mix, though, it is impossible to
program for every possible variable.
That is why machine learning in IoT is vital. A Tesla, fresh off the production line, will have
all the information collected by all the other Teslas that are currently on the road. Any new
variable that is encountered can then be learned and shared with all connected cars,
making the autopilot mode that much safer for all Tesla drivers.
IoT, AI and Big Data
Big data is an industry buzzword that is applied to any large collection of data. It can be
anything from medical data collected by doctors and hospitals to usage data from IoT-
enabled devices and anything in between. A lot of that information is generally useless,
but things like usage and purchase habits can be used by industry leaders to predict
sales trends and other changes in the market before they happen.
The predictive algorithms that are currently being used are useful and allow computers to
make predictions, but they are limited by processing power and their ability to learn. A
traditional computer can process thousands of bytes of data. On the other hand, a
computer powered by artificial intelligence can process that data, find trends and follow
those trends to their conclusion.
Machine learning isn’t the perfect solution. Microsoft applied a basic version of the
program to a Twitter account, and in less than 24 hours Twitter trolls were able to turn the
AI chatbot into a racist mimic that sent nasty messages to everyone. A properly regulated
AI system could be an invaluable tool for the growing IoT industry. The two go together
like cake and ice cream, and they have the potential to change and shape every single
industry by predicting the changes in the market before they happen.
Imagine running a business that produces wearable technology and being able to predict
the type of devices that were going to sell best during the next quarter. You could
potentially make more money on sales, and save money by reducing the production of
items that are less likely to sell. IoT paired with artificial intelligence could reduce or
eliminate excess product inventory.
As long as the system is properly regulated, machine learning could shape the way we
look at the world, and is already changing the way we use our connected devices.
Megan Ray Nichols is a blogger and freelance science writer. She writes weekly on her
blog Schooled By Science where she explores the latest scientific news. Subscribe to her
blog today, or follow her on Twitter @nicholsrmegan.

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Revue de presse IoT / Data / Energie du 02/04/2017

  • 1. Revue de presse IoT / Data / Energie du 02/04/2017 Bonjour, Voici la revue de presse IoT/data/energie du 2 avril 2017. Cette semaine moins d’articles, mais de très intéressantes analyses sur le futur des entreprises de distribution d’électricité. Un futur a composer avec plus de renouvelables, de micro voire nano-grids, et des technologies qui vont dans le sens de la désintermédiation. Avec en trame de fond (et en dernier article) l’importance du mix IOT x data x intelligence artificielle. C’est long mais ça vaut le coup, alors bonne lecture ! 1. How Blockchain Tech Will Create a Distributed Future for the Energy Sector 2. Nanogrids, Microgrids, and Big Data: The Future of the Power Grid 3. Innovative Technologies Driving the Energy Revolution 4. Blockchain 2.0 dans l'énergie vue par France Stratégie 5. How Will Artificial Intelligence Improve the Internet of Things? How Blockchain Tech Will Create a Distributed Future for the Energy Sector Source URL: http://bitcoinmagazine.com/articles/how-blockchain-tech-will-create- distributed-future-energy-sector/ Mar 27, 20171:45 PM EST by Michael Scott April 2016 saw a flurry of media attention around thefirst ever blockchain-managed energy transaction in Brooklyn, NY.In this groundbreaking milestone, the owner of a roof solar panel sold a few kilowatt-hours of excess energy to a neighbor utilizing an Ethereum blockchain smart contract. Fueling this development via the Brooklyn microgrid was the startup company LO3 Energy. Today power and utility companies all over the world are now exploring various ways to implement blockchain technology. Doing so could upend existing models of how energy and utility markets function. Applied on a broader scale, it could be the spark that transforms these legacy industries. So what sort of problems is blockchain technology expected to address in this space? For starters, the technology is seen as a means of overcoming some of the entry barriers that restrict the delivery of electricity to more customers. Here the blockchain infrastructure could foster a more open and transparent mechanism for codifying transactions in the energy realm involving both generation and consumption.
  • 2. Second, blockchain technology can provide companies in these industries with a more efficient way to record and process data, potentially leading to a more synchronized global distribution of energy. Customers would also be afforded a more streamlined and accurate experience in terms of managing their bills and access to the activity taking place on their accounts. Third, the archaic and costly function of meter reading could effectively be eliminated while at the same time boosting the accuracy of bills. Finally, blockchain integration can provide a more effective system for assessing energy sources and determining how that affects the pricing passed on to the consumer. Better technology tools provide more accurate energy utilization and service data, ultimately leading to better outcomes for the end customer. The broader implications of this would include increased industry competition leading to lower prices, streamlined energy distribution, reduced energy waste and better relationships between utility companies and their customers. For a deeper perspective on blockchain technology’s emerging impact on the power, utilities and energy markets, Bitcoin Magazine turned to Thierry Mortier, Global Leader of Technology and Innovation for Power and Utilities at Ernst & Young (EY). Mortier says that the power sector is in the midst of shifting from a centralized model to a more distributed model. He believes that in the future new digital peer-to-peer platforms will emerge to eliminate the middleman and seamlessly connect energy producers directly with the end power user. “Blockchain technology will help facilitate this process by allowing transactions to be recorded between two parties efficiently and in a verifiable and permanent way. It can also be programmed to trigger transactions automatically. The technology promises to radically speed up transactions and cut costs by establishing trust and the transfer of value without the involvement of traditional intermediaries.” Mortier goes on to note that, aside from some early demonstrations, the applicability of an energy blockchain is still largely theoretical. He points to how blockchain enthusiasts are drawn in by the growing complex web of transactions, the need to balance the geographical mismatch between supply and demand, and significant security and trust concerns given the proliferation of Internet of Things (IoT) connected devices. Says Mortier: “Over 200 blockchain use cases have been identified already. Most pilots are still in early stages across the energy value chain, primarily in the area of peer-to-peer energy trading. EY is working with companies in the power and utilities sector to develop use cases and prototypes.” In addition to the aforementioned April 2016 development, where residents in Brooklyn, New York, successfully traded renewable energy using a smart contract on the public Ethereum blockchain platform, he says that in Australia, several pilots are under way, allowing residents in Perth and South Western Australia to buy, sell or swap excess solar energy with anyone connected to the Western Power network. Furthermore, he says that Germany, with Berlin as the global hub of the technology, has a strong presence, as does the U.K., building on the early investment of the financial
  • 3. services sector in the technology. “Blockchain maturity seems to be driven by company ambition rather than any national advantage at this stage,” says Mortier. He is especially excited about the emergence of pre-programmed “smart contracts” that can trigger transactions automatically. “These smart contracts, for example, can be set to allow prosumers to feed surplus energy into the grid through a blockchain-enabled meter. The flow of electricity is automatically coded into the blockchain, and algorithms match buyers and sellers in real time based on preferences. Smart contracts then execute when electricity is delivered, triggering payment from buyer to seller. Removing financial transactions and the execution of contractual commitments from central control brings a whole new level of decentralization and transparency that the industry has never had before.” Mortier also touts the rapidly growing prominence of energy trading, an area he says appears to be moving toward a commercial solution more quickly than many of the others. In conclusion, Mortier says that there has been significant interest in tracking and tracing resource types (green gas, for example) and in the peer-to-peer, prosumer-led trading. But, outside of Bitcoin applications, he laments that there is a lack of proven use cases, with difficulties involving security, scalability and frequency of transactions as factors that need to be overcome. “In three to five years’ time, it is quite possible that blockchain [technology] will radically change the way parts of the power industry operate. To get there, blockchain [technology] must overcome competition from existing solutions and prove its attractiveness to users. Only if its applications have tangible, monetary or timely advantages will blockchain [technology] be able convince enough participants to ditch their legacy systems for this new platform.” Nanogrids, Microgrids, and Big Data: The Future of the Power Grid Source URL: http://spectrum.ieee.org/energy/renewables/nanogrids-microgrids-and- big-data-the-future-of-the-power-grid Distributed generation and automated transactions will change how we produce and consume electricity Developing technology is like driving a race car:You push the machinery as fast as it’ll go, and if you can avoid a crash, a prize awaits you at the finish line. For engineers, the reward is sometimes monetary, but more often it’s the satisfaction of seeing the world become a better place. Thanks to many such engineers driving many such race cars, a lot of progress is about to happen in an unexpected spot: the electricity sector. The power grid’s interlocking
  • 4. technological, economic, and regulatory underpinnings were established about a century ago and have undergone only minimal disruption in the decades since. But now the industry is facing massive change. Most observers are only vaguely aware of the magnitude of this overhaul, perhaps because it’s a hard story to tell. It doesn’t translate well to a set of tweets. Many people have come to think of the electric-utility business in much the same way they think of their taxes—boring, tedious, and somehow, always costing more money. What’s happening in this industry stems from technology improvements, economic forces, and evolving public priorities. As the changes dig away at the very foundation of the electricity sector, the results are likely to be anything but boring. Yet they may well cost you more money. For about a century, affordable electrification has been based on economies of scale, with large generating plants producing hundreds or thousands of megawatts of power, which is sent to distant users through a transmission and distribution grid. Today, many developments are complicating that simple model. At the top of the list is the availability of low-cost natural gas and solar power. Generators based on these resources can be built much closer to customers. So we are now in the early stages of an expansion of distributed generation, which is already lessening the need for costly long-distance transmission. That, in turn, is making those new sources cost competitive with giant legacy power plants. Distributed generation has long been technically possible. What’s new now is that we are nearing a tipping point, beyond which, for many applications, distributed generation will be the least costly way to provide electricity. While it certainly helps, the declining cost of renewables and gas-fired electricity is not all that’s spurring this change. To be competitive, the entire distributed system will have to work well as a whole. Quite a few technological advances are coming together to make that possible: advanced control systems; more compact, smarter, and efficient electrical inverters; smart electricity meters and the burgeoning Internet of Things; and the ever- growing ability to extract actionable information from big data. Global Total Installed Wind and Solar Capacity
  • 5. Growth in wind and solar has been brisk. The two together represent roughly 10 percent of the world’s installed capacity but contribute only about 4 percent of production. Amid this changing scene, a picture is beginning to emerge of what a typical electrical
  • 6. grid may well look like in 10 or 20 years in most of the developed world. Yes, generation will be much more decentralized, and renewables such as solar and wind will proliferate. But other aspects are also shifting. For example, the distribution network—the part of the grid to which your home and business connect—will likely become more of a negotiating platform than a system that just carries electricity from place to place. Getting to this more sophisticated grid won’t be easy. Nevertheless, it’s coming. What will it look like? Here is my best guess, based on my decades of experience as a government official charged with helping electric utilities get access to emerging technologies. It is the future I’m now working to help realize as an academic researcher. The first thing to understand is that decentralization is going to be neither simple nor universal. In some places, decentralization will prevail, with most customers generating much of their own power, typically from solar photo​voltaics. Others might use small-scale wind turbines. In regions where sunlight and wind are less plentiful, natural gas will probably predominate. Intertwined among all of those, a continuously improving version of the legacy grid will survive for decades to come. According to the U.S. Energy Information Administration (EIA), in the first 11 months of 2016, some 48.82 million megawatt-hours of distributed solar energy were produced in the country, up 46 percent from the year before. That’s still a tiny proportion, though. In 2016, about 1.4 percent of electricity in the United States came from the sun via solar panels, including both utility-scale plants and distributed ones, according to the EIA. But solar is growing fast because of its increasingly favorable economics. For example, in Chile’s most recent power auction, 120 MW of solar power was the lowest-cost option, at US $29.10 per megawatt-hour. Many analysts expect that grid-connected, distributed solar power will be fully cost competitive with conventional forms of generation by the end of this decade. In the meantime, a dizzying array of government incentives, which vary from region to region (even within one country) are helping the technology to take off. Ultimately, the lowest-cost form of generation will dominate. But figuring out what the lowest-cost option actually is will be tricky because it will depend on both local conditions and local decisions. For example, regulators are increasingly convinced that the burning of fossil fuels leads to significant societal costs, both from the direct exposure of those living near some power plants to their noxious emissions and from ​greenhouse gas induced climate change. Historically, these costs were difficult to quantify. So they were typically borne not by the producers or consumers of the electricity but by the victims—for example, farmers whose crops were damaged. There is growing public interest in understanding the true cost of pollution and possibly shifting more of it to electricity producers and possibly consumers as well. Fortunately, we now have the modeling and computational capabilities to begin to put a reasonable lower limit on those costs, which gives us a defensible way to reallocate them. Although the best strategies for reallocating those costs are still being debated, the benefits of distributed renewable generation are already very apparent—as is the feasibility. Data collected during the Pecan Street Project, funded by the U.S. Department of Energy, indicates that a house in Austin, Texas, outfitted with solar panels typically
  • 7. generates 4 or 5 kilowatts during the midday hours of a sunny day in summer, which exceeds the amount of power the home typically uses during such a period. Illustration: MCKIBILLO A typical smart home has an energy-management system that takes into account time of day and other factors to minimize electricity costs. In a future microgrid, the individual energy-management systems of a group of homes will communicate to maximize efficiency, lower costs, and regulate demand. Whether or not rooftop solar makes sense for a particular homeowner, however, depends on the initial cost, maintenance costs, subsidies, the cost of grid power, and the selling price of the excess electricity generated. The U.S. Department of Energy’s SunShot initiative has as its goal making solar power cost competitive—without subsidies—by 2030. (A Chinese government agency has a similar agenda.) Specifically, SunShot’s goal is to reduce the cost of distributed, residential solar power to 5 U.S. cents per kilowatt-hour by 2030; it costs about 18 cents today. Today, a 6-kW rooftop residential solar system in the United States typically costs between $15,000 and $20,000; the exact figure depends on where you live. According to data from the EIA, the average retail cost of electricity delivered by the grid in the United States is 12.5 cents per kilowatt-hour. So at 18 cents, rooftop-generated solar is not yet, on average, competitive with grid-delivered electricity. But many governments, for example U.S. state governments, subsidize the purchase of solar-power systems to make them competitive. Meanwhile, many utilities are experimenting with ​alternative-ownership options. One is community solar, in which individual consumers buy a small number of panels in a relatively large, utility-scale system. They then get monthly credits for the electricity generated without having panels on their roofs. Another experiment, being run by CPS
  • 8. Energy, in San Antonio, uses rooftop solar, but CPS Energy owns the equipment and pays the homeowner for the use of the roof. One challenge with distributed solar is storage. Most solar-panel owners are using the grid as the functional equivalent of storage: They sell excess power to the grid when they can and buy back from the grid to compensate for shortfalls. This is usually the simplest and cheapest way to even out differences in production and consumption. Nevertheless, many people—most notably, Elon Musk—are betting the economics will soon favor batteries. Musk’s ​electric-car company, Tesla, sells a battery for home use called Powerwall 2, which costs $5,500 and offers 14 kWh of storage, enough to run an average home overnight. However, adding the costs of battery storage to a solar installation to go off grid makes the costs of power significantly higher than those of ordinary electricity from the grid. Comparing the options for expanding the use of solar power is not straightforward, however, because much depends on how the grid will evolve. For example, right now, the grid could not handle a changeover to 100 percent solar (even in areas where it would make sense, like the southwestern United States or the North African desert). The grid we have today was designed around sources whose output generally varies little from day to day. But the U.S. DOE, under its ENERGISE program, is striving to develop, by 2030, the control, protection, and other technologies needed to enable an entirely solar-powered grid. The grid will evolve in other ways, too, and quickly. One of the most important trends, already well under way, is the increasing use of microgrids. A microgrid is a group of connected power sources and loads. It can be as small as an individual house (often dubbed a nanogrid) or as large as a military base or college campus. Microgrids can operate indefinitely on their own and can quickly isolate themselves if a disturbance destabilizes the larger grids to which they are normally connected. This is an important feature during both natural and man-made disasters. Consider what happened when Hurricane Ike hit the Houston-Galveston area of Texas in 2008: Blackouts were widespread, but 95 percent of the outages were caused by damage to less than 5 percent of the grid. The grid effectively distributed the effects of what was only modest equipment damage.
  • 9. Illustration: MCKIBILLO A residential microgrid connects a group of homes that have their own power sources and energy storage. The homes communicate with each other wirelessly and connect to the main grid at a distribution transformer. In an electrical disturbance, the microgrid can protect itself by disconnecting from the main grid at that transformer. This isolating capability of microgrids also promises enhanced cybersecurity. That’s because microgrids can help keep localized intrusions local, making the grid a much less appealing target for hackers. When disaster strikes, whatever its cause, microgrids can limit the consequences. If it is not physically damaged, a microgrid can operate as long as it has access to a source of power, whether that’s natural gas, the sun, or wind. In the long term, with the timing depending as much on economics and regulation as technology, it is quite possible that the grid will evolve into a series of adjoining microgrids. Utilities have proposed to build such microgrid “clusters” in, among other places, Chicago, Pittsburgh, and Taiwan, a tropical island where grids are prone to storm damage. These adjoining microgrids would share power with one another and with the legacy grid to minimize energy cost and to maximize availability. In an era of adjoining microgrids that are privately owned and operated, what will become of the utility company? There are at least two possibilities. It might simply supply power to the microgrids that need it, rather than doing that for individual customers. Or it might manage microgrids and their connections with one another and to the legacy grid. Across the United States, the concept of a utility is already being reinvented in some places as more competition is introduced. Microgrids are going to accelerate that trend. The spread of distributed generation and the rise of microgrids will also be shaped by two other factors: the expansion of the Internet of Things and the growing influence of big data. The Internet of Things is a boon for distributed generation because it is giving rise to
  • 10. industries that are ​mass-producing sensors, microcontrollers, software, and other gear that will be easily and cheaply adaptable for use in future, data-driven grids and microgrids. How will these things be used? Imagine a residential solar-power system of the near future. It will have “customer equipment”—solar panels, a smart inverter, and a storage battery and systems to manage loads dynamically. From time to time, the power output of that installation will be lower than usual, because of, say, a heavily overcast day. But it would be easy to design a control system, based on readily available IoT components, that could communicate with similar systems in surrounding houses. These systems would work together, for example, to turn air conditioners on or off ahead of or behind schedule, or alter their thermostats by half a degree, to accommodate intermittent, unexpected shortfalls in capacity. What would enable this plan to work is the fact that most modern homes are well insulated, so it takes time before the internal temperature changes enough to trigger the HVAC system. The reason why homes would be grouped together in this scheme is that it would make the task easier: In the group, some homeowners would be willing to sacrifice a lot of comfort, some less. But the power needs of the group of houses would be relatively predictable and manageable, from the utility’s standpoint. Most consumers do not want to make frequent and detailed decisions on energy use. So imagine a device—let’s call it an energy thermostat—that permits you to set a range of comfortable temperatures, rather than entering a single one. The wider you set the range, the less you’ll pay for power. The grid or microgrid operator would use the range—yours and everybody else’s—to dynamically match supply and demand on a minute-by-minute basis. On a hot afternoon, with demand at its peak, the temperature in your home would be at the top of the range. A distribution substation connects the microgrid to the distribution network and therefore to the main grid, through a set of transformers and disconnect switches. Electric utilities will also begin making greater and much more effective use of big data. Utilities have been using data since the very beginning: When Thomas Edison opened the Pearl Street power station, in New York City in 1882, it had indicator lights to show when the load had increased or decreased enough to warrant adjustments to the dynamo producing the DC power. But that system clearly was not scalable. If a utility had to readjust its generators every time a customer came online, the industry would have died out long ago. Having a large number of loads makes the aggregate demand predictable—and manageable. This happy condition obviously depends on there being little correlation of usage from house to house and business to business. But just suppose that at 3:00 p.m. on a hot summer day, everyone in a medium-size city turned off their air conditioners at the very same second, waited 15 minutes, and then turned them all back on again at exactly the same time. That would almost certainly cause a massive blackout. With big-data tools, it may no longer be necessary to depend on consumers’ actions being only loosely similar. It should be possible to understand how to adjust production and consumption to enhance system behavior. For example, with the energy-thermostat concept outlined above, the system operator needs to have not only the appropriate controllers but also access to real-time data to determine the risk of system failure when load-management actions are taken.
  • 11. Utilities in many areas have embarked on this path using various customer incentives to permit, say, time-of-day pricing or some other form of load management by the utility rather than by the consumer. But we are now taking just baby steps. Big-data tools will soon let us take larger strides and may well one day let us run. It may be possible to use real-time operational data to optimize the performance of large sections of the grid and to predict future performance. Although my main goal is to describe a hopeful vision that many of us in the utility business have for the electric grid, I would be remiss if I did not point out some of the challenges. These include financial ones, regulatory ones, and technical ones. And they come in all shapes and sizes. One of the most fundamental is slow growth. To pay for costly system upgrades, utilities in the past would have relied heavily on growth in demand, and therefore sales. But improvements in efficiency, which consumers seek (and rightly so), have slowed growth in demand to the extent that it is now increasing at a rate lower than that of the growth in gross domestic product. And the figures are sobering: In 2014, the U.S. DOE predicted that in the period from 2012 to 2040, the demand for electricity will grow by only 0.9 percent per year. So, utilities cannot expect to fund the required system changes in the same ways as they have in the past, through growth. Other shifts in the industry will only exacerbate these money woes. For example, in the past utilities could count on key pieces of equipment lasting a long time. But smart grids depend on electronic components, such as smart meters, controlled by software, which have shorter lifetimes and require much more frequent upgrades. The biggest unknown is how swiftly the regulatory process can adapt. If it can’t move quickly enough to keep up with the technology, expect agonizingly slow change. And what if governments try to prop up outmoded technologies with subsidies? That could drag out the process further. On the other hand, some would argue that regulators should slow the rate of change. Though the arguments for that are worthy of political discussion, I’m certainly not in that camp. Historically, regulations have been driven mainly by legal and economic considerations rather than by technical ones. But now, with the pace of technology outrunning other factors, regulators in the United States and Europe are reacting to this new state of affairs in many different ways. My view is that the staffing of regulatory agencies will need to become more technically savvy if we are to navigate these turbulent waters while continuing to provide electric power with the lowest cost and highest reliability. I’m confident that in the end, we’ll have electrical grids that are less costly, more sustainable, and more user friendly than the ones that came before. The United States’ National Academy of Engineering recently selected electrification as the top engineering accomplishment of the 20th century. But electrification now needs to be reengineered to meet the needs and opportunities of the 21st century. This is our chance to show that we are as good as our forebears of two, three, or four generations ago at technology, regulation, public policy, finance, and the management of change in general. And to leave to posterity a legacy as fine and enduring as the one that was left to us. About the Author
  • 12. Robert Hebner is the director of the Center for Electromechanics at the University of Texas at Austin. Innovative Technologies Driving the Energy Revolution Source URL: http://breakingenergy.com/2017/03/31/innovative-technologies-driving- energy-revolution-solar-power-measurement-efficiency/ Two explosive growth markets are renewable energy (RE) and the Internet of Things (IoT) technologies and both play a crucial role in creating value. The emphasis on how software and analytics can drive energy savings along with renewable energy and energy conservation measures (ECM) will be examined. Companies, like Arkados, exist that operate in the solar (through its recently announced acquisition of SolBright Renewable Energy), LED lighting, and IoT markets. Market The IoT market is demonstrating substantial growth. According to McKinsey, the IoT market should grow from $900 million in 2015 to $3.7 billion by 2020. One of the key drivers of the IoT market is smart building applications where energy savings provides the return on investment (ROI). IoT applications play a leading role in renewable energies in including solar and wind. Global investment spending in the solar PV markets was $161 billion in 2015, according to Bloomberg New Energy Finance. GTM Research and the Solar Energy Industry Association (SEIA) indicated that the US solar industry grew 95% to 42.4 gigawatts (GW) in 2016. According to the SEIA, the US solar market installed 14.6 GW of solar PV in 2016. In the global market, approximately 73 GW of solar was added in 2016. However, when solar is measured against conventional energy sources such as natural gas and coal, solar represents approximately 1% of the energy generation in the US according to DOE. Despite the successful growth of solar in the US market, there is substantial upside for further growth. Fueling the solar market growth are falling PV panel costs and the extension of tax credits. Solar PV panel costs are at grid parity in most states. Solar power generation at a cost of approximately $0.13 per kWh is close to the US national average rate at $0.115 per kWh. Technology Positioning Solar costs at grid parity should be great news for commercial and residential applications as well as for the utility industry itself. However, renewable energy has limitations, and therefore, new technologies employing IoT devices and analytics can further enhance the market for solar and drive higher energy efficiency. These technologies apply to buildings and utility markets where tools and technology are required to better manage electric supply and demand. This image depicts how IoT can be employed in various objects to enhance energy data.
  • 13. One issue for renewable energies is that their ability to generate power is intermittent. Because renewable energy is intermittent, energy storage is a crucial component to enable the distributed grid where electric supply has to match demand. Energy storage is a critical component of the distributed grid architecture. The ability to store energy is important to improve RE value and to provide power when RE sources are not available. The US grid was built to generate electricity from fuels such as natural gas, coal, hydro and nuclear and transmit electric to substation for distribution to customers. Utilities globally are implementing micro and distributed generation grids meaning they are introducing electric generation at end points in the network. Solar generates energy and without the ability to derive granular insight in energy supply and demand, energy can be wasted. This is one area of focus for IoT connected devices and analytical software. In addition, Net Metering, a process that credits the owners of solar generation systems for power added to the grid, helps solar become more attractive for customers. Several states including Arizona, California, Colorado, Connecticut, Delaware, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Ohio, Oregon, and Pennsylvania have implemented net metering. Arkados, and other like companies, are employing IoT devices and software to enhance value of renewable energy and facility operations. These technologies include energy and environmental sensors that enable diagnostic feedback loops to compare energy efficiency to facility conditions and set points. Part of the process is educational to demonstrate the feasibility and viability into an organization. Some concepts are simple such as performance bench-marking to identify aberrant conditions or major areas of concern. Key metrics include energy density in kW and kWh per square foot. Facility load factors and equipment load signature are also helpful is comparing procedural operating hours to measured operating hours by equipment. Some of the approaches include fog analytics such as pushing intelligence to the edge of the network using IoT devices to capture granular detail and enable local processing and control. The concept is to push context awareness to the sensors and collect data in the process. This process includes remote control on lighting and equipment. The real benefits from IoT and analytics are huge including reducing costs, increasing energy efficiency, asset protection, and predictive maintenance.
  • 14. Value The value of energy savings must be within a two-year payback to gain acceptance by the market. In other words, the RE and ECM investment ROI should be greater than 50%. To achieve energy savings insight, generate data from an array of sensors at a granular level. Meaning continuous monitoring of sensor data that can be used to enhance energy performance. Typical energy savings initiatives would include cutting back at peak kW demand and duration and can be used to substantially reduce energy costs. Conditioning less outside air is effective in reducing HVAC costs. Modulating outside air intake using demand control ventilation employing CO2 sensors is an effective energy savings method. Demand Control Ventilation has been able to demonstrate HVAC efficiency gains of 24%. Automated measurement and verification (M&V) systems provide mechanism to deploy demand response. Some studies suggest demand response has the potential to reduce energy costs by 40%. Monitoring based commissioning (MBCx) can save money simply by measuring consumption to set point changes in and facility environmental conditions. The futuristic approach is to combine energy monitoring with sales and installation of LED lighting and solar PV systems. Conclusion Energy savings and efficiency gains measure the value created through IoT and analytics. With the rise of both of these initiatives, consumers should be more aware of their energy consumption in the near future as more of this technology is available to them. Software developed by companies provides a means of enhancing the benefits of solar and LED lighting by gaining insight into energy consumption in addition to enabling efficiency optimization using diagnostic feedback loops. Today, consumers should focus on leveraging software and IoT capabilities to drive sustainability and improve energy efficiency for solar and LED lighting initiatives. Blockchain 2.0 dans l'énergie vue par France Stratégie Source URL: https://www.energystream-wavestone.com/2017/03/blockchain-energie- france-strategie/ Le jeudi 9 mars, nous avons eu l’opportunité d’assister à une table ronde organisée par France Stratégie autour de la blockchain, ses enjeux et les obstacles qu’elle rencontre dans le secteur de l’énergie. Pierre Paperon (fondateur de l’Observatoire Blockchains des Energies) était le principal intervenant de cette conférence. Compte-rendu d’une matinée riche en enseignements. Vers une blockchain 2.0
  • 15. Initialement, la blockchain permet de sécuriser des transactions par le chiffrement des données et de faciliter les échanges en supprimant les tiers de confiance entre de multiples utilisateurs. De ce fait, elle permet de faire des échanges directement de pair à pair (peer-to-peer) et donc de se passer de plus en plus d’intermédiaires durant les transactions. Cette blockchain 1.0 se développe aujourd’hui et ses champs d’action s’élargissent. A un niveau de maturité naissant, on parle alors de blockchain 2.0. Mais quelles sont ses fonctions concrètement ? La blockchain 2.0 intègre les “smart contracts” ou “contrats à exécution automatique” qui sont des clauses programmées pour exécuter des actions spécifiques. Le contrat est prédéfini à l’avance sous forme de code informatique par les deux parties. Lorsque les conditions spécifiées dans le contrat sont remplies, la transaction est réalisée automatiquement par la blockchain sans intervention humaine. Il est important de noter que les smart contracts ne peuvent pas être modifiés a posteriori de leur implémentation sur la blockchain. Il est donc crucial de s’assurer que le contrat ne comporte pas de faille exploitable par un acteur malveillant. Ce genre de faille a notamment été exploitée lors du hack de The DAO[1]. Quels cas d’usage dans le secteur de l’énergie ? La disparition des tiers de confiance fait de la blockchain une technologie prometteuse en faveur de la décentralisation de l’industrie de l’énergie. Cette décentralisation englobe l’ensemble des acteurs actuels, en réinstaurant cependant une dynamique locale plus forte. Les usages de la blockchain sont particulièrement pertinents pour deux aspects de la gestion de l’énergie : la production et le stockage. Revue des principaux use-cases envisagés de la blockchain dans le secteur de l’énergie : Production d’énergie L’achat d’électricité se fait généralement via un fournisseur qui agit comme instance centrale de gestion de la production et de la consommation. Les échanges à une échelle
  • 16. locale seraient facilités par l’utilisation d’une blockchain : les producteurs, rémunérés par des jetons convertibles en crypto-monnaie ou en « crédits énergie » seraient directement en contact avec les consommateurs. Ce système est d’ores et déjà mis en place dans le quartier de Brooklyn à New York. L’optimisation de l’utilisation de batteries domestiques est aussi envisagée. De la même façon que pour l’électricité, des réseaux de gaz locaux pourraient voir le jour grâce à la blockchain (apparition d’un crypto-m3). Conversion énergétique Lors d’un pic de production d’électricité (qui a pour effet de déstabiliser le réseau), l’énergie excédante peut être utilisée afin de chauffer de l’eau ou de produire du gaz (power-to-gaz).Ce surplus d’énergie pourrait être géré par une blockchain et un smart contract : en cas de pic de production, une installation serait automatiquement redirigée vers un circuit de chauffage ou de production de gaz. Gestion des déchets L’utilisation de nano-méthaniseurs est également très prometteuse : ceux-ci se mettraient automatiquement en marche en cas de forte demande en gaz. Ces nano-méthaniseurs pourraient être installés chez des particuliers (10 kg de compost produisent 5 m3 de méthane). Un système de récompense pourrait également être mis en place à l’échelle d’une commune : les citoyens participant au tri sélectif seraient récompensés par une crypto-monnaie convertible en devise réelle ou en crédits énergie. Si la blockchain a dans un premier temps attiré l’attention des acteurs du secteur financier, ses apports dans l’énergie sont aussi conséquents. Elle pourrait constituer un véritable vecteur de développement de la décentralisation du marché énergétique et instaurer un fonctionnement sans tiers de confiance qui privilégie les économies locales. Cela pourrait s’avérer particulièrement dangereux pour certains grands acteurs actuels (notamment les fournisseurs). De nouveaux acteurs et une nouvelle chaîne de valeur
  • 17. De nouveaux acteurs apparaîtront avec l’émergence de la blockchain. En effet, une mise en commun des ressources à travers un troc 2.0 est envisageable. La question de la souveraineté de la blockchain est donc cruciale : le statut de l’opérateur (privé, public) et son rôle précis dans la gestion du registre partagé sont à définir. Il devra notamment s’assurer de l’adossement des crypto-monnaies à des monnaies réelles (cf. Tramonex Ltd au Royaume-Uni, qui adosse une quinzaine de crypto-monnaies au pound) et du bon fonctionnement de la blockchain. Quid de la législation ? Outre la question des opérateurs, de nombreuses interrogations émergent en termes de législation. La première concerne l’encadrement juridique de la blockchain car à ce jour, aucune loi ni norme n’existent à son sujet. Il existe donc un vide juridique qui représente une menace dans la mesure où les limites – contraintes à son exploitation ne sont pas fixées. Pour pallier ce vide, l’évolution jurisprudentielle est capitale. De plus, de nombreux enjeux métiers apparaissent : qui doit s’assurer de la conformité de la blockchain d’un point de vue juridique ? Le juriste deviendra-t-il développeur ou le développeur deviendra-t-il juriste ? Enfin, il y a également un enjeu lié à la propriété industrielle. Il est important de souligner que nous assistons aujourd’hui à la montée du « patent trolling[3] », notamment aux Etats-Unis. Cela nous amène donc à nous poser la question suivante : devons-nous déposer des brevets pour éviter d’être bloqués par la suite ou pour innover ? La technologie blockchain à un niveau industriel n’étant pas encore assez mature, ces quatre grandes questions demeurent aujourd’hui sans réponse. Cependant, nous devons nous y intéresser dès aujourd’hui afin de préparer le futur de la blockchain en France. Conclusion
  • 18. La blockchain est une technologie qui suscite de nombreux débats et sur laquelle les avis divergent. Apporte-t-elle plus de souplesse dans les échanges ou plus de complexité ? Quel est son coût ? Est-elle si avantageuse pour tous les secteurs et cas d’usages ? La blockchain est vouée à se répandre – notamment dans le secteur de l’énergie – et il y a de nombreuses opportunités pour la France car notre futur sera rempli d’objets connectés. Il est crucial pour la France de prendre le virage blockchain avant que d’autres pays ne se l’approprient. La Chine est en position de précurseur : elle héberge plus de 50% de la puissance de calcul du bitcoin, envisage la création d’une crypto-monnaie adossée au yuan et a explicitement inscrit la blockchain dans son plan quinquennal. Les Etats-Unis, quant à eux, n’ont pas encore pris de mesures importantes. En revanche, la France semble prendre le virage : le 13 juillet 2016, la CRE a publié une ordonnance à propos de l’autoconsommation qui se projette vers une réglementation pour la blockchain. [1] Pour plus d’informations au sujet de The DAO, voir : http://www.coindesk.com/understanding-dao-hack-journalists/ [2] Le patent trolling est la pratique d’un groupement d’avocats déposant un grand nombre de brevets non exploités, en vue d’empêcher toute autre entreprise souhaitant utiliser une technologie en lien avec ce brevet et n’en disposant pas, de développer sa solution. Il existe donc une menace, notamment américaine, si l’on souhaite se développer sur la blockchain sur le volet de la propriété industrielle. How Will Artificial Intelligence Improve the Internet of Things? Source URL: http://www.iotevolutionworld.com/iot/articles/430775-how-will-artificial- intelligence-improve-internet-things.htm By Special Guest Megan Ray Nichols, Special Correspondent, Science Writer March 28, 2017 From DVRs and smart fridges to smartphones and voice-activated technology, the Internet of Things (IoT) is quickly becoming part of our daily lives. These devices are capable of collecting thousands of bytes of data every single day, and companies are hoarding that data in the hopes that predictive algorithms will be able to glean some insight from them. How will artificial intelligence improve the Internet of Things? The Introduction of AI Artificial intelligence has gotten a very bad reputation, courtesy of science-fiction novels and movies. When most people think of AI, their mind conjures images of HAL 9000 from “2001: A Space Odyssey” or Skynet from the “Terminator” series. While a truly sentient AI might create a threat if not properly regulated, machine-learning algorithms are the foundation of artificial intelligence. The idea behind machine learningis to create computers that can learn without being programmed. It’s already being used on small scales — your Netflix show
  • 19. recommendations, for example, are a basic form of machine learning. The program analyzes the shows and movies you watch and uses that data to provide you with new choices. Incorporating AI into IoT Machine learning is already taking its first steps into the world of IoT. Self-driving cars are one of the biggest IoT devices, and even cars that only offer partial autopilot capabilities like the Tesla rely heavily on machine learning. You can program a self-driving car so it knows the basic rules of the road and how to handle the most common obstacles it might come across. When you introduce other drivers into the mix, though, it is impossible to program for every possible variable. That is why machine learning in IoT is vital. A Tesla, fresh off the production line, will have all the information collected by all the other Teslas that are currently on the road. Any new variable that is encountered can then be learned and shared with all connected cars, making the autopilot mode that much safer for all Tesla drivers. IoT, AI and Big Data Big data is an industry buzzword that is applied to any large collection of data. It can be anything from medical data collected by doctors and hospitals to usage data from IoT- enabled devices and anything in between. A lot of that information is generally useless, but things like usage and purchase habits can be used by industry leaders to predict sales trends and other changes in the market before they happen. The predictive algorithms that are currently being used are useful and allow computers to make predictions, but they are limited by processing power and their ability to learn. A traditional computer can process thousands of bytes of data. On the other hand, a computer powered by artificial intelligence can process that data, find trends and follow those trends to their conclusion. Machine learning isn’t the perfect solution. Microsoft applied a basic version of the program to a Twitter account, and in less than 24 hours Twitter trolls were able to turn the AI chatbot into a racist mimic that sent nasty messages to everyone. A properly regulated AI system could be an invaluable tool for the growing IoT industry. The two go together like cake and ice cream, and they have the potential to change and shape every single industry by predicting the changes in the market before they happen. Imagine running a business that produces wearable technology and being able to predict the type of devices that were going to sell best during the next quarter. You could potentially make more money on sales, and save money by reducing the production of items that are less likely to sell. IoT paired with artificial intelligence could reduce or eliminate excess product inventory. As long as the system is properly regulated, machine learning could shape the way we look at the world, and is already changing the way we use our connected devices. Megan Ray Nichols is a blogger and freelance science writer. She writes weekly on her blog Schooled By Science where she explores the latest scientific news. Subscribe to her blog today, or follow her on Twitter @nicholsrmegan.