How EVs can help drive a more sustainable energy future

Tesla South Mimms Supercharger and PowerPack

Electric Vehicles (EVs) have taken off in 2017 with governments, manufacturers and industry queuing up to announce bold commitments, product launches and sales figures. Suddenly, EVs have shifted from being a future technology, to a technology of the here and now.

The next decade will be critical for EVs, and their accelerating deployment will have a significant impact on infrastructure systems and markets. A lot of attention has been given to ‘worst-case’ scenarios but smart charging technology means EVs can be managed to the benefit of the system, accelerating our transition to a sustainable energy future and supporting low carbon growth. New analysis by Open Energi suggests that EVs could provide over 11GW of flexible capacity to the UK’s energy system by 2030.

Rise of EVs

The next decade will be incredibly important for EVs, and their deployment has been strengthened by manufacturer commitment, government influence and price curves. Manufacturers including Volvo, Jaguar, and Volkswagen to name a few have made bold statements, claiming the electrification of their product lines and assigning large budgets for R&D. Global EV line-up will almost double by 2020, as the release of Chevy’s Bolt, Tesla’s Model 3 and Nissan’s new Leaf lead EVs into the mainstream.

Governments such as France and the UK have agreed to ban sales of diesel vehicles by 2040. Other countries have set aggressive sales targets, for example China, who has set a 7m target in its 2025 Auto Plan. And all want to become world leaders in EV technology. Here in the UK, BEIS has announced funding for battery and V2G technology development with further funding announced in the Autumn Budget.

Technology development and manufacturing scale-up continues to drive prices down. Battery prices, which account for around 50% of the cost of an EV, have fallen more than 75% since 2010 and are expected to continue to do so at about 7% year on year to 2030. Analysis from both UBS and BNEF claims price parity will be achieved in Europe, US and China sometime in the 2020s, repeatedly accelerating the next million of sales.

The first million takes the longest: length of time, in months, to reach electric vehicle sales milestones
The first million takes the longest: length of time, in months, to reach electric vehicle sales milestones

EVs and electricity demand

According to BNEF, in 2040 54% of global new car sales and 33% of the global fleet will be electric, with a demand of up to 1,800 TWh (5% of projected global power consumption). In the UK, National Grid suggests around 9 million EVs will be on the road by 2030[1]. This uptake in EVs will have a significant effect on our electricity system.

Source: National Grid Future Energy Scenarios 2017 (Two Degrees)
Source: National Grid Future Energy Scenarios 2017 (Two Degrees)

 

Source: Bloomberg New Energy Finance
Source: Bloomberg New Energy Finance

Although EV charging will cause an increase in overall electrical energy demand, the greater challenge lies in where, when and how this charging takes place. The overall electricity demand change will be a single-digit percentage increase but if all this energy is consumed at the same time of day, it could result in double digit percentage increases in peak power demand. This creates challenges for generation capacity and for local networks, who could be put under strain to meet these surges in power demand.

There has been a lot of attention given to the worst-case impact EVs could have on the system – but less analysis of the benefit they could bring as a flexible grid resource controlled by smart charging. At Open Energi, we have used a bottom up approach to quantify the flexibility EVs could offer the UK’s energy system, and the opportunities it could create.

Flexibility scenarios

Different charging scenarios were designed based on the charging speeds currently available and their granular flexibility was quantified (see below for a full description of the methodology). Then, the time at which each of these scenarios is likely to occur was evaluated. Finally, using EV fleet forecasts, volume was attributed to each scenario and a set of future flexibility profiles produced.

EV speed table

EV charging scenarios table

By 2020, with around 1.6 million EVs on the road, Open Energi’s analysis suggests there could exist between 200 – 550 MW of turn-up and between 400 and 1.3GW of turn-down flexibility to be unlocked from smart-charging. The available flexibility would change throughout the day depending on charging patterns and scenarios. In 2030, with 9 million EVs on the road, this rises to up to 3GW of turn-up and 8GW of turn-down flexibility respectively.

EV flex profile 2020 down

EV flex profile 2020 up EV flex profile table

Opportunities: smart charging for flexibility

Smart charging technology turns EVs from a threat to grid stability into an asset that can work for the benefit of the system. Optimal night-dispatch for example, can ensure all vehicles are charged by the time they’ll be used the next day without compromising their local network infrastructure. Cars could help to absorb energy during periods of oversupply, and to ease down demand during periods of undersupply. On an aggregate basis, they can help the system operator, National Grid, with its real-time balancing challenge, and provide much needed flexibility to support growing levels of renewable generation. Suppliers could work with charge point operators to balance their trading portfolios and manage imbalance risk, helping to lower costs for consumers.

Of course, smart charging can only happen with the consent of the driver, and drivers will only consent if their car is charged and ready to go when they need it. This means deploying artificial intelligence and data insight to automate charging without affecting user experience, so that the technology can learn and respond to changing patterns of consumer behaviour and deliver an uninterrupted driver experience. Getting this right is key to aligning the future of sustainable energy and transport.

Dago Cedillos is Strategy and Innovation Lead at Open Energi

Methodology

Open Energi’s methodology consists of a bottom up approach, looking at the different charging scenarios and quantifying the flexibility from each of them. The time at which each of these scenarios is likely to occur has been analysed. Finally, using EV fleet forecasts, based on National Grid Future Energy Scenario forecasts (2017, Two Degrees), we’ve attributed volume to each scenario and generated a flexibility profile.

Charging speeds

We formulated our charging scenarios based on the different charging speeds and the capabilities of each. Charging speeds are currently referred to as Slow, Fast and Rapid as set out below.

EV speed tableScenarios

Based on these speeds, we built some scenarios considering the use-cases. Slow charging is likely to be used at home, Fast charging in public spaces and Rapid in public spaces and forecourts. We assumed typical plug-in durations for these charging scenarios.

EV charging scenarios table

Main assumptions

Considering the charging scenarios, calculations were performed on the turn-up and turn-down capabilities of each. An important element of this analysis, the average daily energy requirement per vehicle, was based on the following assumptions:

  • Average daily miles travelled per vehicle: 20.54 (based on UK National Transport Survey’s VMT)
  • A conservative assumption of 20kWh/100km (the Chevy bolt can travel 238 miles on a 60kWh battery)

EV electricity demand table
This leads to the figures in table (above), which align closely with National Grid’s Future Energy Scenarios 2017 when using their fleet forecasts.

Extracting flexibility

Different likely situations were built for each scenario, using 7kWh as a simple rule of thumb of what an EV would require as charge per day. For example, for the ‘Long’ scenario: using a 3kW (B) slow charger, energy to be charged (A) was evaluated for the different likely situations (J). Potential turn-up (F) and turn-down (H) was defined and saturation/underperformance parameters (G & I) were introduced for this flexibility. That is, to charge (A) using speed (B), there would only be (I) hours of turn-down flexibility (H) in an optimal case before underperformance (i.e. not fully charging the vehicle). This was repeated across all scenarios using the range of charging speeds, plug-in durations and rates of charge eligible for each to quantify flexibility.

Energy to charge table
The average flexibility potential for each possibility was calculated as a kW value, as the product of (F) & (G) and (H) & (I) divided by plug-in time (D). This was the estimated average kW value of flexibility for a vehicle under the option in the scenario. Max, mid and min flexibility values were defined for each scenario based on the options calculated per scenario.

Flexibility profiles

Having the average flexibility per vehicle for each scenario, this was then converted into a flexibility profile considering the following assumptions:

  • Long scenario (home charging) likely to take place during the night.
  • Medium scenario (workplace charging) likely to take place during office hours.
  • Short scenario (shopping/dining) likely to take place during early morning, lunch and after office hours.
  • Ultra-short scenario (forecourts) likely to take place during early morning, lunch and after office hours.

Time of day tableAttributing vehicle volume to each scenario was then performed as follows. Data from the Department of Transport[2] indicates that approximately 50-55% of households owning a vehicle have access to off-street parking. Open Energi assumed the following share of vehicles per scenario[3]. Further work needs to be carried out to define how this share will evolve over time with the development of charging technology.

Share 2020 table
The aggregate flexibility for each hour which defines the profile was then calculated using the flexibility per vehicle and scenario, the scenario schedules, and the number of vehicles in each scenario and for each time period (2017, 2020, 2030 and 2040).

[1] National Grid Future Energy Scenarios 2017 (Two Degrees)

[2] Department of Transport survey: http://webarchive.nationalarchives.gov.uk/20111006052633/http:/dft.gov.uk/pgr/statistics/datatablespublications/trsnstatsatt/parking.html

[3] Open Energi identified a gap in data available to define these shares with accuracy, these will have to be reviewed over time.

New EEF report: DSR should “be one of the first options” for electricity security

Metal company scores win-win of cash and cost savings

Under Theresa May’s Government BEIS has been tasked with delivering a comprehensive industrial strategy, ensuring that the UK has secure energy supplies that are reliable, affordable and clean, and tackling climate change.

The UK’s manufacturing sector has an important role to play but a report published this week by the manufacturers’ organisation, EEF, found that its members’ confidence in the Government’s handle on security of supply is tepid at best. Only one third of its members agreed with the statement that “the Government has a long-term strategy to ensure security of supply” and just 3.6% felt energy infrastructure had improved in the last two years.

The report “Upgrading Power: Delivering a flexible electricity system” makes a series of recommendations for Government to help manufacturers play a part in boosting UK energy security and improve how our electricity system operates. Demand Side Response (DSR) is identified as one of the first options that should be looked to in achieving electricity security.

As the authors note “Continuing to be over-reliant on supply side options and leaving DSR options untapped is rather like having the heating on at home, deciding it’s too warm and then opening a window rather than turning the heating down. Both actions will achieve the intended outcome but the former wastes energy and money.”

In a recent EEF survey only 9% of respondents took part in some form of DSR activity – compared with 29% in a recent cross-sector survey conducted by Ofgem – citing varied reasons from insufficient financial incentive to those that had utilised all of the available flexibility on their sites. However, by the far the most common reason given was the complexity of the system and resulting lack of understanding within manufacturing companies.

The report found that even manufacturing companies well versed in the DSR markets find the system bewildering and unwelcoming to new entrants. One company commented that “it is genuinely stressful to be in a regulatory environment alongside the big six”, further noting that energy companies have entire departments to deal with these markets, whilst even a large manufacturing company may have only one individual covering energy.

Those manufacturers who are engaged in DSR activities adopt a common approach and hierarchy to maximise potential savings and revenue streams. Where possible, companies will seek out opportunities to reduce exposure to higher power (wholesale) prices first, followed by minimising their network costs (Triads and Distribution red band charges) and finally participate in specific DSR products.

To help unlock the estimated 9.8GW of DSR flexibility available in the UK EEF recommends first increasing the number of businesses acting on straightforward price signals through time-of-use tariffs. Beyond this it calls on the Government, National Grid and Ofgem to look at what can be done to reduce the complexity of specific DSR services and regulatory barriers to entry.

Finally, it highlights the forthcoming ADE code of conduct for aggregators as an important step which will improve manufacturers confidence in these companies. Open Energi strongly supports this move. Aggregators occupy a position of trust and have a responsibility to educate businesses and be open and transparent about the benefits that exist.

Donna Hunt, Head of Sustainability at Aggregate Industries summed this up in a recent interview with edie, saying “businesses want to see what the value-case is. They need the confidence and trust in it. It’s not new technology but it’s perhaps not at scale yet. That’s a big reason why Aggregate Industries is proud to be out there talking about how it works. We should be doing more of it because we need a more responsive energy system that works for everyone.

“We need to prove that value-case, share knowledge and open doors. We just need there to be a level playing field between the aggregators to remove the confusion so people are clear about how they can engage.”

Unlocking the full potential of DSR is going to take time but National Grid is looking to source 30-50% of balancing services from DSR by 2020, creating a potential revenue stream for businesses of around £1 billion. As the world strives to find ways of delivering energy which is clean, affordable, and secure, the more that can be done to facilitate DSR participation – from business of all sectors – the better.

EEF Report: Demand Side Response Recommendations

  • The Government should investigate how to maximise the DSR benefits for manufacturers of smart meters, half-hourly settlement and time-of use tariffs.
  • National Grid, as part of its charging review and in consultation with industrial energy consumers, should seek to reform the Triad charging system to deliver greater predictability for industrial energy consumers.
  • The Government should explore the incorporation of DSR aims and related electricity cost reduction strategies into energy efficiency schemes such as ESOS.
  • National Grid, in collaboration with energy consumers and the Government, should seek to reform the ancillary market to reduce complexity and create greater transparency.
  • Ofgem should amend the Balancing Settlement Code rules to allow participation of DSR in the balancing market.
  • The Government should reform the Capacity Market to allow easier access for DSR assets in future auctions.

Download the full EEF report “Upgrading Power: Delivering a flexible electricity system”

 

 

How can machine learning create a smarter grid?

Dynamic Demand 2.0

Across the globe, energy systems are changing and creating unprecedented challenges for the organisations tasked with ensuring the lights stay on. In the UK, National Grid is facing shrinking margins, looming capacity shortages and unpredictable peaks and troughs in energy supply caused by increasing levels of renewable penetration.

At the recent Reinventing Energy Summit, Michael Bironneau, Head of Technology Development at Open Energi, explored how the same machine learning techniques that have let machines defeat chess and Go masters, can also be leveraged to orchestrate massive amounts of flexible demand-side capacity – from industrial equipment, co-generation and battery storage systems – towards the one goal of creating a smarter grid; one that is cleaner, cheaper, more secure and more efficient.

For World Cities Day 2016, Michael talked to Nikita Johnson of Re:work about utilising data science in energy, creating a smarter grid, political challenges, and more.
What are the main transformative technologies that will help create a smarter grid?
A smarter grid is one where we can integrate renewable energy efficiently without having to keep polluting power stations online to manage intermittency. This requires energy storage to act as a buffer, reducing demand when supply is too low or increasing it when it is too high.

The cheapest and cleanest type of energy storage comes from flexibility in our demand for energy. Open Energi’s Dynamic Demand platform unlocks small amounts of stored energy from commercial and industrial processes – such as refrigerators, bitumen tanks and water pumps – and aggregates and optimises it second by second, creating a virtual battery.

How can machine learning be applied to help balance the grid?
The most transformative application of machine learning for grid balancing comes from unlocking and utilising flexibility in demand-side power consumption. Such algorithms can find creative ways to reschedule the power consumption of many demand and generation assets in synchrony to keep the grid in balance while helping to minimise the cost of consuming that power for energy users.

With sufficient data, a ML model can look at a sequence of actions leading to the rescheduling of power consumption and make grid-scale predictions saying “this is what it would cost to take these actions”. The bleeding edge in deep reinforcement learning shows how, even with very large scale problems like this one, there are optimisation techniques we can use to minimise this cost beyond what traditional models would offer.

What are the regulatory and political challenges to achieving a national smart grid in the UK?
Whatever your role in the vibrant menu of demand side innovations that are offered across Europe, a shared goal for serving consumers is advocating for the framework of flexibility adequacy at the energy system level. This opens so many possibilities – to facilitate Electric Vehicles, mitigate renewable intermittency, replace aging coal infrastructure, and realise a smart grid.

The key is market access. Currently, the UK market favours existing power generators to a disproportionate extent. To fully realise the potential of demand-side flexibility to help balance the grid, save energy and offer lower costs for consumers, we need a level playing field. Without it, there is a very real risk that we will lead ourselves into multi-decade contracts for power plants, paying for a system which is already over capacity and which has no incentive to get any smarter.

How can energy companies work with engineers and data scientists to achieve a more efficient energy system?
One obstacle that prevents many ideas from taking off is the lack of data to support them. If energy companies made more anonymised half-hourly power data available, data scientists and engineers working on new smart grid technologies would be able to validate these ideas quickly and cheaply. In the same vein, it would be a major breakthrough for grid balancing if energy companies made available APIs for reporting and accessing flexibility; it would allow companies like us to unlock enormous amounts of demand-side capacity and put them to good use balancing not just the grid but also helping to optimise the market positions of those same energy companies.

This post originally appeared on Re:work’s blog on the 31st October 2016.

VIDEO: Optimising data architectures for IoT & Cloud

Tech image

Rapid data growth from a wide range of new data sources is significantly outpacing organizations’ abilities to manage data with existing systems. Today’s data architectures and IT budgets are straining under the pressure. In response, the center of gravity in the data architecture is shifting from structured transactional systems to cloud based modern data architectures and applications; with Hadoop at it’s core.

Join this live and on-demand video panel – featuring Open Energi’s Head of Technical Development, Michael Bironneau – as they discuss how the landscape is changing and offer insights into how organizations are successfully navigating this shift to capture new business opportunities while driving cost out.

Demand flexibility is putting consumers in control

Tarmac has installed Demand Side Response at around 70 sites UK wide

A smart power revolution is underway putting your business in control of how, when and from where it consumes its energy. At last week’s Energy Live 2016 Open Energi’s David Hill explored how technology can unlock demand flexibility to deliver maximum value from your assets  – connecting industrial equipment, batteries and self-generation – and coordinating their behaviour in real-time to turn the vision of a smarter grid into reality.

David was joined by Steffan Eldred, Senior Energy Optimisation Manager at Tarmac, sharing their approach to demand flexibility.

Download a copy of the presentation.

The move to a low carbon economy coupled with rapid advances in technology and innovation are transforming electricity supply and demand. Grid agility and flexibility are essential as we move away from models of centrally dispatched generation and incorporate more intermittent renewable energy generation onto the system.

This flexibility can be provided in a variety of forms, from demand side response (DSR) and energy storage to new build gas generation. However, there is a clear merit order emerging in terms of both the carbon and consumer cost of these offerings.

DSR is the cheapest and cleanest form of flexibility. At its core, it is an intelligent approach to energy that enables aggregators to unlock flexibility in our demand for energy to build a smart, affordable and secure new energy economy.

Flexibility Merit Order shows Demand Side Response is lowest cost optionThe technology can be used to invisibly increase, decrease or shift users’ electricity consumption, enabling businesses and consumers to save on total energy costs and reduce their carbon footprints, while at the same time enabling National Grid to keep the system in balance.

It is part of a wider energy market picture that must focus on flexibility and achieving the lowest cost for consumers. If just 5 per cent of peak demand was met with flexible power, the response would be equivalent to the generation of a new nuclear power station, without the huge costs to consumers.

Tarmac is one business benefiting from this approach. The company has been a pioneer of DSR, partnering with Open Energi to install Dynamic Demand on over 200 bitumen tanks at 70 asphalt plans across the UK. What this means is the heating elements in each of those tanks, which keep the bitumen warm, can switch on or off in seconds to help National Grid balance electricity supply and demand.

Collectively Tarmac’s tanks are providing the grid with capacity that can be shifted in real-time, so they’re able to use more when there is a surplus – for example when it’s particularly windy – and less when there’s a shortfall. Its enabling Tarmac to help build a smarter, more responsive energy system which is paving the way for more renewable power and reducing the nation’s reliance on fossil fuelled power stations.

 

 

10 myths about Demand Side Response

Sainsbury's deliver demand side response from its stores UK wide

Demand Side Response  is a vital part of our transition to a zero carbon economy and has the potential to transform how we use and deliver energy. But there are some common misconceptions about how businesses can get involved and what it means for them. To help cut through these, Chris Kimmett, Commercial Director at Open Energi, tackles some of the most common myths about Demand Side Response (DSR).

Myth 1: It’s too disruptive

This myth is especially prevalent in the press where headlines such as “UK factories shut down to prevent winter blackouts” are not uncommon. But this is a very outdated perception and technology advances have changed the game completely. There are lots of processes that have a degree of flexibility, where technology can be used to temporarily increase or decrease consumption without impacting performance, for example heating, cooling and pumping.

Take the air conditioning in a typical office building. It will be designed to maintain the temperature between certain bands, for example 18-22 degrees centigrade. Turning the unit on or off for a short period won’t have any discernible impact on the temperature and technology can automate its response so as soon as it approaches its upper or lower limit it stops responding.

Some demand is genuinely inflexible, such as lighting. The good news is that as battery costs come down, businesses can use these to participate in different Demand Side Response schemes and switch to battery power during peak periods.

Myth 2: It’s all back-up diesel generators

It’s true that there is a lot of back up generation participating in certain DSR schemes. Short Term Operating Reserve (STOR) is a good example; 93% of the response comes from generation and 22% (743MW) of this is from diesel. That’s because there are a lot of organisations with back up diesel generators which for much of the time are under-used, so it makes sense to earn revenue from these where possible. However, there is also a significant and growing portion of real demand participating across a range of markets, coming from all kinds of different equipment, including fridges, pumps, chillers, motors, and fans. To date, we have connected over 60MW of demand flexibility from these types of assets across the UK, of which around a third is usually available at any one time.

Myth 3: There isn’t enough value to make it worthwhile

There are lots of businesses out there participating in DSR who would disagree with this statement. In a recent Energyst Media survey, 81% of businesses said they participated in DSR to generate revenue and National Grid’s PowerResponsive website features a range of case studies. These businesses are seeing significant value from participating in DSR, not just in terms of revenue, but also because it is the right thing to do and it is supporting their organisation’s sustainability credentials. Accessing all a business’ flexibility means it should be possible to return around 5-10% of its energy bill in DSR revenue. National Grid has clearly stated its desire and need to grow demand side participation significantly, and its value is expected to increase over time.

Myth 4: It’s a winter peak problem

There is a winter peak problem and margins remain slim at around 6.6%, but National Grid increasingly faces challenges in the summer and with the year round second-by-second balancing of supply and demand. As more of our power comes from wind, solar and other sources of distributed generation over which National Grid has no control, it is having to cope with periods in the summer months where supply exceeds demand, often overnight or in the middle of a sunny day. Rather than pay wind farms to turn off, it has been using a new service called Demand Turn-up to encourage businesses to shift their demand to these periods to help absorb the excess energy.

A very different challenge is that of managing the real-time balancing of electricity supply and demand, which National Grid must do 24/7, 365 days a year. Whether a gust of wind means a surge in power or a gas plant tripping means a shortage, demand flexibility is cleaner, cheaper and faster than ramping power stations up and down in response. Fast acting real time flexibility is essential to keeping the lights on in the future.

Myth 5: Participating in Demand Side Response means handing over control of my processes

Absolutely not! It is not the place of DSR providers to tell you how to run your business and you should always retain ultimate control. This should be a fundamental part of how you approach DSR. We spend a lot of time working with our customers to understand their assets and processes and agree the parameters within which they want their assets to participate. Once a control strategy is in place, each individual asset is then able to decide if it can respond, and the technology will enable it to kick us out automatically if it reaches a point where it can’t.

The beauty of DSR is that because the response is aggregated from many thousands of assets, where one fridge can’t respond we know that a pump or a bitumen tank will. Added to this there is always an override switch which means the system can be disabled on site at any time.

Myth 6:  Demand Side Response is easy

It is getting easier, but it is certainly not easy just yet. As described above, much of the effort and resource is required pre-implementation, in understanding the assets and processes and developing a strategy to ensure there is no impact on operational performance. There is a lot of great learning happening in the UK and globally, connectivity is increasing, technology is improving, and we are starting to see equipment being manufactured “DSR” ready. These changes are making it easier for businesses to participate by the day.

Myth 7:  Energy storage = batteries

Batteries are very interesting and the cost curve has been plummeting – especially for Lithium-ion batteries. But energy storage comes in many forms; there is thermal storage in a fridge, in a building’s air conditioning or in a bitumen tank for example.

Working with Aggregate Industries, we have found that a modern, well-maintained and insulated bitumen tank – which stores the liquid bitumen used to make asphalt for roads at between 150-180 degrees centigrade – can be switched off for over an hour with only a one-degree change in temperature.

Similarly, the water pumped to a reservoir represents a form stored energy. If we can find these small amounts of stored energy in everyday processes and unlock this flexibility for National Grid, then we can start to deliver a transformation in how our energy system operates without the need to build new batteries.

Myth 8: There isn’t enough demand flexibility to make a difference

A number of recent studies have looked at this, including the Association of Decentralised Energy and the National Infrastructure Commission. Our analysis suggests there is around 6GW of demand that can be shifted during peak periods, and that’s real demand only, not including back-up generators. 6GW is more than the UK’s two biggest coal fired power stations combined, and almost double the proposed Hinkley Point C nuclear plant. Unlocking this flexibility means we can build fewer peaking plants, integrate more renewable generation and mitigate the effects of intermittency. It offers major advantages in terms of cost, network reliability and sustainability which is good news for the environment and bill payers!

Myth 9: It’s unreliable

In setting the Capacity Market Auction Guidelines, National Grid prescribed the reliability for each balancing technology class available. Demand Side Response was ranked as more reliable than Combined Cycle Gas Turbines (CCGT), coal, hydro, oil or nuclear power. For example, for a 100MW nuclear generator, National Grid estimate it can rely on 81.4MW being available, while for DSR they would expect 89.7MW to be available. Large centralised power stations do not necessarily confer reliability. By their very nature they represent large single points of failure with the potential to cause massive disruption should a problem arise. The aggregated nature of DSR which relies on many thousands of smaller assets working together has proved its reliability over many years.

Myth 10: I have no flexibility!

You probably have more than you realise. If you’re thinking about demand flexibility but not sure how or if it could work for your business, we recommend you:
1) engage the right people internally who know what equipment you have and understand how it is managed
2) find someone who understands the market
3) find someone who understands your industry and what you do

By overlaying the above in a meaningful you can identify how much flexibility you have and where you can use it in a way that doesn’t disrupt your business and delivers the value you need.

 

 

Ashden Awards 2016: Open Energi Case Study

To keep the lights on, National Grid has to keep electricity demand and supply exactly in balance, and when faults occur a rapid response is needed – within two seconds! Traditionally this was provided by gas and coal power plants running below full power, so they can adjust output quickly, but this is inefficient, expensive and increases CO2 emissions. Open Energi has developed an alternative – cutting-edge software which can automatically switch energy-hungry equipment on or off when required, without disrupting business operations.

Large energy users like water companies identify which items of equipment are not time-sensitive in their operation and this equipment can then increase or decrease its consumption within agreed parameters to provide a rapid response service to National Grid.

Open Energi Harnessing the power of IoT for cleaner, more efficient and affordable energy

David Hill, Business Development Director at Open Energi speaks to theCUBE about how Open Energi is harnessing the benefits of connectivity to bring customers more efficient, more affordable and, ultimately, cleaner energy.

“We were an IoT company before we even knew what IoT was,” said David, discussing how Open Energi was founded pre-Hadoop. Becoming Hadoop customers was a “huge leap,” and Hortonworks Dataflow services are enabling much more cost-effective integration that has Open Energi extremely excited about the future.

David spoke to theCUBE whilst attending Hadoop Summit 2016, Dublin – http://bit.ly/1qIrgEN

Powering a Virtual Power Station With Big Data

Michael Bironneau, Data Scientist at Open Energi, discusses powering a virtual power station with big data.

At Open Energi in order to prove that we’ve delivered our Dynamic Demand service to National Grid and kept it running at optimum, we need to analyse large amounts of data relatively quickly. We’re also making our service smarter so that more assets will be able to participate in Dynamic Demand than before. This is where Big Data and Hortonworks Data Platform come in.

Big Data is a phrase that has been floating around companies like Google for the last two decades. It has never really had a precise definition, but when used casually it usually means that someone somewhere is running out of space for your data and/or computing power to analyse it, this can also mean that your data is so unorganised it is difficult if not impossible to analyse. Data is the most important asset when considering Dynamic Demand, it tells us when to flex certain assets, it proves we are providing a service and it allows us to better understand our portfolio.

Michael was speaking at the 2016 Hadoop Summit, Dublin – http://hadoopsummit.org/dublin/

Green Gown Awards recognise University of East Anglia’s innovative approach to energy management

University of East Anglia Logo

University of East Anglia and Open Energi were Highly Commended for their entry in the Technical Innovation for Sustainability category at the 2014 Green Gown Awards.

 

UEA was the first university to install Dynamic Demand across its campus, helping to keep the lights on and boosting its credentials as one of the most sustainable universities in the country.

Air handling units (AHUs) across its estate have been equipped with this unique form of Demand Response and the AHUs are now adjusting their energy consumption instantaneously to help National Grid balance electricity supply and demand in real-time.

What it means to win… “UEA has a top-rated School of Environmental Sciences and we are committed to replicating this success in the sustainability of our campus. Adopting more intelligent ways of managing our electricity demand supports this goal and we are thrilled to win a Green Gown award for our work with Open Energi.“

Professor Edward Acton, Vice-Chancellor

 

What the judges said: An interesting application of technology into the HE sector, where the complexity of power demands across a campus can be used to balance the power system. Clear applicability to other areas, and replicable elsewhere. The “invisibility” of the technological fix is also attractive.

Click here to view the winners’ brochure.