Tag: demand response

3 Ways Electric Cars Are Changing More Than the Way We Drive

Part 1 of 3 on the Future of Transportation and the Internet of Things

The world is moving away from cars based on the internal combustion engine (ICEs). The future is electric. With Tesla leading the way on what’s possible with electric vehicles, more traditional auto manufacturers are following suit.

Volvo has announced that all of its cars will have electric motors by 2019. Aston Martin is planning the same by 2025. General Motors plans to have at least 20 electric vehicles (EVs) by 2023. The list goes on.

Much of the pressure is coming from countries banning ICE sales in the not-too-distant future (The Netherlands by 2025; China, India and Germany by 2030; France and the UK by 2040). Industry and consumers, however, want electric as well.

When everybody wants something, it tends to happen. The question is, what will be the ramifications? One safe bet is that the market for your ICE -based car will be drying up quickly – so think about selling now. But beyond concerns for personal finance, we can also expect EVs to have a dramatic impact in a number of areas including climate conditions in cities, the automotive industry in general, and energy distribution worldwide.

Lower emissions

The obvious benefit of electric cars – the reason countries, industries, and individuals everywhere are pushing for them – is lower emissions. One of the cities most concerned about emissions is Beijing. Back in 2015, the notoriously thick smog of the city disappeared quickly when authorities banned driving  for two weeks in preparation for a World War II commemoration parade. The day after driving resumed, the smog returned.

Today, Beijing is planning to replace the city’s nearly 70,000 taxis with EVs. Doubtless, this is a step in the right direction. Yet, while Beijing tends to get the lion’s share of press coverage when it comes to smog, other cities face similar challenges. From Paris to Mexico City and all around the world, lower emissions from electric vehicles will help to improve health for citizens locally and fight climate change globally.

Industry change

The automotive industry is not just General Motors, Volkswagen, Toyota and the rest. It’s also made up of countless suppliers of parts and components. But when you move from a traditional ICE to the electric engine, you lose about 90% of the parts. Electric engines are just simpler.

This means that for companies in the automotive supplier ecosystem, much of the market is going away soon. The simplicity of electric engines will also be felt further down the value chain. Service centers, for example, will feel the hit.  Many of these centers – particularly the large chains – use the inexpensive 3,000-mile oil change as a loss-leader to upsell customers on needed maintenance. But without oil in the electric engine – and without as much need for maintenance – many of these chains will have to rethink their business models to survive.

New energy horizons

One of the most significant impacts of EVs will be on the way energy is distributed – because in addition to being modes of transportation, EVs will also act as energy sources that can plug directly into the grid.

This will help address the challenge of “demand response.” The problem to solve here is one of grid stability in the era of renewable energy. Traditionally, large centrally located energy generation plants –  coal, gas, and nuclear – have churned out a steady supply of energy that results in a fairly stable grid.

However, the renewable energy paradigm – based mostly on solar and wind – is neither centralized nor steady. Rather it is distributed across rooftops, solar farms, and mountain tops. And it is variable according to weather conditions.

With renewables, in other words, utilities have less control over the supply side of the equation – meaning how and when energy is generated. This has the potential to lead to instability on the electricity grid. If you can’t manage the supply, then you have to use demand side management, also known as demand response. This can be done using through incentives, and the technology is advancing such that increasingly the process is becoming automated.

By providing a storage mechanism that can both take energy in and send it out, car batteries on EVs can act as frequency regulators for the grid. This is a big deal that has the potential to change energy distribution forever.

At night, say, when the wind is blowing, a car battery can store energy generated by wind turbines. Or, in the middle of the afternoon when everybody wants air conditioning on a hot day, the same batteries can distribute some of their energy. This leads to improved grid stability.

Industry convergence

Let’s just note, however, that the entities with the closest relationships to the owners of the batteries so critical to grid stability would not be the utilities but EV manufacturers. What’s stopping Elon Musk from enticing Tesla customers from sharing their batteries? Tesla could enable its customers provide energy from their batteries – and then sell it on the grid for a profit. Customers make money. Tesla makes money. Utility companies make money. Everybody is happy.

This transforms the automobile industry into an energy industry. At SAP we talk a lot about digital transformation as a response to digital disruption. This is disruption at its most dramatic.

Elon Musk has stated aims to make 500,000 Tesla’s in 2018. Let’s say he falls disastrously short and only hits half his target. Let’s also assume an average 80 kilowatt hour (kWh) battery size in the EVs – (Tesla cars today have battery sizes ranging from 60 -110 kWh). 250,000 cars x 80 kWh – and you’ll see that this fleet would have the capacity of 20 gigawatt hours of storage. For comparison, a gigawatt is roughly the output of a nuclear power plant. So, Tesla will be producing the equivalent of 20 nuclear power plants worth of storage, at least, per year.

Electric vehicle manufacturers will be able to aggregate the energy on their networks, and sell access to their “virtual power plants”. It is a whole new world.

Stay tuned for more on how the transportation industry is changing forever.

 

Photo credit Tesla

Internet of Things, renewables and storage – a perfect storm for utilities’ digital transformation

Without doubt it is a time of great turbulence in the electric utilities space.

In most regions globally, wind and solar are now our cheapest sources of electricity generation, even without subsidies.

As a consequence of this, wind has overtaken nuclear, hydro and coal to become the second largest source of electricity generation in EU in 2016 [PDF]. And at the same time in the US, the solar market is smashing records and grew 95% in 2016 alone.

Then there is storage. Costs here have been tumbling too. So much so that Morgan Stanley predicts the storage market to grow from the roughly $400m in 2016, to a market size of $2-4bn by 2020. This will have big implications for utilities’ ability to add more variable generators (renewables) to their mix without destabilising the grid.

Speaking of grid stabilisation, the refrain up until now has been that for every MW of renewables built, a MW of gas had to also be built as a backstop (for days with no wind, or overcast days, or nights). However, this too has changed. Last August First Solar ran a tests with CAISO (the California grid operator) to test a solar farm’s ability to smooth out grid fluctuations. The results of the test demonstrated that solar farms are able to meet, and sometimes exceed, the frequency regulation response usually provided by natural-gas-fired peaker plants.

Things are changing on the consumption side of the house too.

solarinstall2016

Source: GTM Research / SEIA U.S. Solar Market Insight report

As can be seen from the chart above, installations of residential PV are rising, as is home storage, and another form of potential consumption and storage (v2g), the electric car, saw sales rise by 37% in the US in 2016.

Then there is the whole digitisation of the grid. Now all new equipment is being built with inbuilt ‘smarts’ and connectivity, and even older infrastructure can be retrofitted, so with the advent of the smart grid, we will finally have the possibility of the Electricity 2.0 vision I was talking up back in 2008/09. This is a smart grid where appliances in the commercial or residential worlds can ‘listen’ for pricing signals from the grid, and adjust their behaviour accordingly, taking in electricity when it is plentiful, and switching to alternative sources/lowering consumption when electricity is in high demand.

With the cost of generation dropping, with no end in sight, the cost of storage similarly falling, as I have posited previously, there is a strong possibility that utilities will have to switch to broadband-like ‘all-you-can-eat’ business models with the utilities differentiating, and making their revenue on added services.

Everything is changing for the electric utility industry – and so, against that backdrop, and the fact that I will be presenting on IoT and Utilities at the upcoming International SAP for Utilities Conference in Lisbon, I decided to have a chat with IDC Research Director Marcus Torchia, about the implications for utilities of these huge changes.

We had a great discussion, and many of the themes we touched on, I will be talking about at the Utilities event in Lisbon.

You can check out our chat in the video above, play it in the audio below, or listen to it on the IoT Heroes podcast site.

Technology is moving us to a world where energy is cheaper, smarter, and less carbon intensive

Screen Shot 2016-05-03 at 11.51.40

The graph above is a graph of electricity demand on the Spanish electricity grid taken from the demand page of the grid management company Red Electrica de España.

The data comes from April 26th this year through to Mar 3rd. The sever small graphs along the bottom are daily demand curves, going from Tuesday April 26th on the left, through to Monday May 3rd on the right. You can see that the demand curves for each day are virtually the same.

Saturday and Sunday are however, obvious due to the lower demand on those days, and if you are wondering why Monday the 3rd looks to be lower than the rest of the weekdays, it is because that Monday was a holiday in Spain.

The large graph on top is a zoomed-in look at the demand on one of those days – Friday April 29th. From that you can see that the demand starts to rise early in the morning with the peak occurring between 8-11am. Demand then falls off until late afternoon when people are cooking their evening meals, peaking around 9pm, and then falling until it starts again the following day.

The pattern varies slightly by day of the week, as well as by season, but overall while it is variable, it is also highly predictable.

Graph of predicted energy demand vs actual demand on Spanish grid on April 29th
Graph of predicted energy demand (Green) vs actual demand (yellow) on Spanish grid on April 29th this year – graph from REE

This can be problematic though when you have high penetrations of variable energy suppliers, such as wind and solar.

Here is the energy supplied to the system by wind, for example on April 29th

Energy supplied by wind on the Spanish grid on April 29th this year
Wind energy on the 29th of April on the Spanish grid

As you can see, it doesn’t map well with the demand, and this is challenging for grid management companies, especially with increasing pressure on them to decarbonise.

That can lead to circumstances where wind power ends up supplying 140% of your demand, as happened in the Netherlands last summer. Fortunately, the Netherlands has good interconnects, and so was able to sell this excess energy to its neighbouring countries. This won’t always be the case though, and will become a more common issue as the penetration of wind and solar increases globally.

 

Obviously, if you can’t manage the supply side of the grid, what about managing the demand – how achievable is that?

Interestingly, this is now becoming a real possibility. Already there are companies who aggregate the demand of large organisations with facilities for reducing demand, if required, and sell that reduced demand to utility companies. This can save the utility from having to build new generation sources to meet the increased demand at times of peak load.

Demand flexibility graph
Demand flexibility

What if this were more widespread?

Looking at the chart above, if we could shift the yellow demand line up during its overnight dip, and then reduce the yellow demand line during the morning and evening, this would make the grid more stable, and allow for the introduction of more variable generators (solar and wind) onto the system, as well as reducing the requirement for expensive ‘peaker plants’.

Sounds great Tom, how to do that?

Well price is always a great motivator. In Germany last week where there was an excess of energy on the system, so pricing went negative, meaning large customers were being paid to use it.

Negative pricing on the German energy market
Graph of negative pricing on the German electricity market

Reduced, or negative pricing is a better option than wind farm curtailment because curtailment lowers the income for the wind farms, making them a less attractive investment for renewables developers, while reduced pricing moves the demand to a more suitable time.

Now, with the advent of the Internet of Things, everything starts to be smart and connected. If our electricity devices can listen for realtime electricity signals from the grid, they can adjust their consumption accordingly.

Of course, not all loads in the home are movable  – not many people will decide to cook their evening meal at 3am just because the wind is blowing and energy is cheap.

However, many loads are eminently movable. Pool pumps, are a good example. And also many loads that have a heating or cooling component associated with them, such as an electric hot water heater. When it is well insulated it doesn’t matter when it heats the water. Similarly for fridges, freezers, ice bank air conditioning, and so on. These are straightforward and affordable forms of energy storage.

Dish washers, washing machines, clothes dryers can also be made to listen to electricity pricing, and adjust their behaviour accordingly. Often, when you put the dish washer on in the evening, you don’t care when it comes on, as long as the dishes are clean and dry when you get up the following morning.

As more of our appliances become connected and smart, this will become the norm. Obviously, for widespread adoption, this kind of behaviour has to be totally automated. If the device owner has to think about it, it won’t happen.

Smart grid appliance

And then there are the real storage options, using batteries. This can be in the form of batteries in electric vehicles using vehicle-to-grid technologies, in-home batteries such as the ones Tesla, and others sell, or reconditioned electric vehicle batteries – a market that is just starting to get going.

So, good news, technology is moving us inexorably to a world where energy is getting cheaper, smarter, and less carbon intensive.

EPRI releases open, standards based software, to connect smart homes to the smart grid

Smart Appliance Screen

Automated Demand Response (ADR) is something we’ve talked about here on GreenMonk for quite a while now. And in other fora, back, at least as far as 2007.

What is Automated Demand Response? Well, demand response is the process whereby electricity consumers (typically commercial) reduce their usage in response to a signal from the utility that they are in a period of peak demand. The signal often takes the form of a phone call.

Automated demand response, as you would imagine, is when this procedure is automated using software signals (often signals of price fluctuation). The development of ADR technologies received a big boost with the development of the OpenADR standard, and in 2010 the subsequent formation of the OpenADR Alliance to promote its use.

Consequently, EPRI‘s recent announcement that it has developed automated demand response software, is to be welcomed.

In their announcement EPRI say the new software will:

provide a common way for devices and appliances on the electric grid to respond automatically to changes in price, weather, and demand for power, a process called automated demand response (ADR).

ADR makes it possible to translate changes in wholesale markets to corresponding changes in retail rates. It helps system operators reduce the operating costs of demand response (DR) programs while increasing its resource reliability. For customers, ADR can reduce the cost of electricity by eliminating the resources and effort required to achieve successful results from DR programs.

The EPRI ADR software was certified by the OpenADR Alliance. “Making this software freely available to the industry will accelerate the adoption of standards-based demand response” said Mark McGranaghan, vice president of Power Delivery and Utilization at EPRI.

This software has the potential to finally bring the smart grid into the home, allowing smart appliances to adjust their behaviour depending on the state of the grid. Some manufacturers have been fudging this functionality already with a combination of internet connected devices and cloud computing resources (see Whirlpool 6th Sense device above). And others, like GE are planning to bring older appliances into the connected fold, by sending out wifi modules that add new sensor capabilities.

(Cross-posted @ GreenMonk: the blog)

The coming together of the Internet of Things and Smart Grids

I was asked to speak at the recent SAP TechEd && d-code (yes, two ampersands, that’s the branding, not a typo) on the topic of the Internet of Things and Energy.

This is a curious space, because, while the Internet of Things is all the rage now in the consumer space, the New Black, as it were; this is relatively old hat in the utilities sector. Because utilities have expensive, critical infrastructure in the field (think large wind turbines, for example), they need to be able to monitor them remotely. These devices use Internet of Things technologies to report back to base. this is quite common on the high voltage part of the electrical grid.

On the medium voltage section, Internet of Things technologies aren’t as commonly deployed currently (no pun), but mv equipment suppliers are more and more adding sensors to their equipment so that they too can report back. In a recent meeting at Schneider Electric’s North American headquarters, CTO Pascal Brosset announced that Schneider were able to produce a System on a Chip (SoC) for $2, and as a consequence, Schneider were going to add one to all their equipment.

And then on the low voltage network, there are lots of innovations happening behind the smart meter. Nest thermostats, Smappee energy meters, and SmartThings energy apps are just a few of the many new IoT things being released recently.

Now if only we could connect them all up, then we could have a really smart grid.

The slides for this talk are available on SlideShare.

(Cross-posted @ GreenMonk: the blog)

Here comes the sun… IBM and solar forecasting


Concentrating solar power array

For decades now electricity grids have been architected in the same way with large centralised generation facilities pumping out electricity to large numbers of distributed consumers. Generation has been controlled, and predictable. This model is breaking down fast.

In the last decade we have seen a massive upsurge in the amount of renewable generation making its way onto the grid. Most of this new renewable generation is coming from wind and solar. Just last year (2013), almost a third of all newly added electricity generation in the US came from solar. That’s an unprecedented number which points to a rapid move away from the old order.

This raises big challenges for the grid operators and utilities. Now they are moving to a situation where generation is variable and not very predictable. And demand is also variable and only somewhat predictable. In a situation where supply and demand are both variable, grid stability can be an issue.

To counter this, a number of strategies are being looked at including demand response (managing the demand so it more closely mirrors the supply), storage (where excess generation is stored as heat, or potential energy, and released once generation drops and/or demand increases), and better forecasting of the generation from variable suppliers.

Some of the more successful work being done on forecasting generation from renewables is being undertaken by Dr Hendrik Hamann at IBM’s TJ Watson Research Center, in New York. Specifically Dr Hamann is looking at improving the accuracy of forecasting solar power generation. Solar is extremely complex to forecast because factors such as cloud cover, cloud opacity and wind have to be taken into account.
IBM Solar Forecaster
Dr Hamann uses a deep machine learning approach to tackle the many petabytes of big data generated by satellite images, ground observations, and solar databases. The results have been enviable apparently. According to Dr. Hamann, solar forecast accuracy using this approach is 50% more accurate than the next best forecasting model. And the same approach can be used to predict rainfall, surface temperature, and wind. In the case of wind, the forecast accuracy is 35% better than the next best model.

This is still very much a research project so there is no timeline yet on when (or even if) this will become a product, but if it does, I can see it being an extremely valuable tool for solar farm operators (to avoid fines for over-production, for example), for utilities to plan power purchases, and for grid management companies for grid stability purposes.

The fact that it is a cloud delivered (pun intended, sorry) solution would mean that if IBM brings it to market it will have a reduced cost and time to delivery, bringing it potentially within reach of smaller operators. And with the increase in the number of solar operators (140,000 individual solar installations in the U.S. in 2013) on the grid, highly accurate forecasting is becoming more important by the day.

(Cross-posted @ GreenMonk: the blog)

(Cross-posted @ GreenMonk: the blog)

The zero-emissions Nissan Leaf test drive

The Nissan Leaf

I love the idea of electric cars and have done for a long time.

Recently, one of my best friends Ray Flynn, proprietor of Flynns Garage (a Nissan Dealership in Carlow, Ireland), contacted me to let me know he is one of only 15 Nissan dealerships in Ireland who have been approved to sell the new all-electric Nissan Leaf. As such he had a limited number of slots available for a test drive and he wanted to know if I’d like one of them. I jumped at the chance!

The Leaf is a totally electric car relying completely on its 24 kW·h/90 kW lithium ion battery pack for power. The battery pack is rated to deliver 100 miles on a full charge but this can vary from about 62 miles (100 km) to almost 138 miles (222 km) depending on driving style, load, traffic conditions, weather (i.e. wind, atmospheric density) and accessory use.

Nissan Leaf under the hood

Nissan Leaf under the hood

The car is a five seater with a spacious interior. It is very responsive to drive. My own car is a 2008 Toyota Prius and this is a much nippier car than the Prius. It handles well on the road and because there are 300kg of batteries under the floor, the car sticks to the road on corners!

Charge time varies on the type of charging (normal or fast) and whether the battery is fully depleted or only partially. Using a standard 220/240 volt 30 amp supply the battery can be fully charged in 8 hours. Fast charging using a 440V level 3 charger charges to 80% in around 20 minutes – these are typically the kinds of chargers you will see deployed in places like McDonalds, Tesco’s and motorway café’s I assume.

Nissan Leaf interior

Nissan Leaf interior

There is a lot of technology built in to the car. It is connected to a global data center which provides support, information and entertainment at all times. The GPS navigation system delivers a constantly updating display of your range as well as showing all the charging stations on your route and it allows you to book a charging station to ensure that it is available when you arrive.

Mobile phone apps will allow remote turning on of aircon and heating as well as setting charging times to coincide with time of use rates from utilities…

There’s gold in them thar bills!

Graph of power consumption
Photo credit Urban Jacksonville

The output from smart meters is incredibly granular. Far more so than is obvious from the smart meter output graph above.

In conversations with Dr Monica Sturm (Director of Siemen’s Center of Competence, Metering Services) last November (2008) she confirmed to me that it is possible to identify individual devices in someone’s home down to make, model and year of manufacture by looking at their energy profile – the output of their smart meter.

This kind of information is absolute gold and don’t think the utility companies aren’t starting to wake up to the fact. They are, and they are not alone. Why else do you think Google have jumped into this space with their PowerMeter offering. Not to be outdone, Microsoft have also stepped in with their Hohm product.

It won’t be long before Apple joins the fray with a sleekier, sexier iHome application!

For the utilities themselves, there are data protection issues to be worked through but once they are (and they will be), the utilities will use this data to help make up for the earnings lost as customers become more energy efficient (consuming less expensive energy).

One revenue model you will start to see emerge is utility companies selling appliances (and possibly even cars!). How will it work?

Because the utility company will have full visibility of our energy consumption, they will see when your devices are inefficient/faulty. I can very easily envisage receiving a communication from my utility company in the not-too-distant future along the lines of:

Dear Mr Raftery (actually, as I am based in Spain it would be more likely to be Estimado Sr. Raftery but let’s stick with the English version),

We notice from your energy profile that you own a 2004 Indesit BAN12NFS fridge freezer. Our records show that in the last 3 months the compressor in that freezer has become much less efficient and it is now costing you €25 a month just to run that one appliance.

We have partnerships with service companies who could try to repair the compressor in that fridge freezer for you, or alternatively, we have a special offer this month on new energy efficient fridge freezers.

We can have a brand new fridge freezer installed in your home before the end of the week. We can take away your old one for responsible disposition. And all this will won’t cost you a penny, in fact it will save you €10* per month off your current bill!

So, to summerize, if you call our hotline now on 555-123 4567 you can save €10 off your monthly bill, have a brand new fridge-freezer installed free and reduce your CO2 emissions by 12kg a year.

What are you waiting for?

*We charge you €15 per month for the new fridge thus saving you €10 per month off your current bill. Terms and conditions apply.

That’s just one possible scenario of how the utility companies will make use of smart meter data to generate alternative revenue streams for themselves – can you think of others?

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Klaus Heimann espouses SAP’s smart utility of 2020 at International SAP for Utilities conference

I attended the 7th International SAP for Utilities event in Munich last week.

Having attended the SAP for Utilities event in San Antonio last year, I had reasonably high expectations from this conference and I wasn’t disappointed. At the San Antonio event SAP talked very much about the ‘State of the Now’ talking up their, then recently launched, Energy Capital Management software. At this event however, Head of SAP Service Industries, Klaus Heimann keynoted introducing SAP’s vision for the utility company of 2020!

In what was a very forward-looking address, Klaus confidently predicted that:

In two years time this will no longer be a Utilities conference, it will be en Energy conference

This must have had a lot of the people in the room squirming in their seats because, as Klaus himself said, “Utilities are not known as being good at change!”

But change they must.

Just a few of the upcoming major changes utility companies are going to have to cope with include the growing imperative to move to a greater penetration of renewables in the generation mix, the impending explosion in the numbers of electric vehicles to be charged, and the need to roll-out smart grids and take in distributed generation.

Klaus’ vision for the utility company of 2020 is summarised in the video interview I conducted with him above, but briefly he talked of an energy market vastly more complex than today’s. An energy market:

  • where customers can be consumers and producers (via micro-generation)
  • where customers may have shares in a wind-farm which sells electricity to the local utility
  • where customers receive rebates on kWh’s saved during times of peak demand (compared to avg previous day’s use at same time, for example)
  • where utilities will have special renewable-only power offerings (I wish they had that now)
  • where utilities will need to be able to bill customers for energy used to charge electric vehicles, away from home (at the office) or even in different countries and
  • where utilities will need to be able to offer real-time consumption information, generation data and a control interface to the customer’s appliances

Nothing too earth-shattering in that list to be honest. But, when put against the types of changes utilities have gone through in the last 100 years, this is an enormous upheaval. This is probably a good time to be a change management consultant in the utilities sector ;-)

For this vision to become real (and any utilities who don’t start to move in this direction can start writing their own obituaries now), there needs to be massive changes in utilities communications infrastructures and their data handling capabilities.

With big change, comes big opportunities so it is not surprising to see SAP are all over this and helping the utilities visualise where they need to go.

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