V2X: how ‘storage on wheels’ can reshape our energy system

EV smart charging

Dagoberto Cedillos, Strategy & Innovation Lead at Open Energi

As Electric Vehicle (EV) uptake accelerates we’re starting to see a radical transformation in the way transportation influences the power system. Vehicle-to-X (V2X) technology, which can be used to discharge an EV battery back to the grid, or to power our homes and businesses, has a pivotal role to play.

By unlocking ‘storage on wheels’ V2X can bring down the cost of EV ownership; reducing the need for infrastructure upgrades and cost effectively integrating more renewable generation. Open Energi’s analysis suggests that by using vehicle batteries to optimise electricity demand against prices, EV owners could benefit from a new income stream in the region of £1,500 a year.

EV momentum

The UK currently has over 130,000 EVs on the road, and National Grid expects this to rise to over 10 million by 2030. Globally, BNEF forecasts 130 million EVs in the same timeframe.  As 2019 gets underway, all the indicators suggest EV growth is well on its way to hitting these targets, breaking records month-on-month. The graph below shows how EV forecasts have increased year on year. It’s possible we will see a very visible step change in the mid-2020s, as EVs hit up-front cost parity with Internal Combustion Engines (ICEs).

 

BNEF rising consensus on EV adoptionRising Consensus on EV adoption, source BNEF

Quantifying EV flexibility from smart charging

Last year Open Energi analysed the potential to manage EV electricity demand (one way) using smart charging.  Taking National Grid’s 10 million by 2030 forecast, we identified some 12GW of flexibility which could turn EVs from a threat to grid stability to an asset that can benefit the grid, drivers and the environment alike.

Smart charging flexibility comes from the energy that can be shifted (e.g. moving a period of charge, or part of it, from one time to another) and is determined by the amount of energy a vehicle will require at a given charge.

An average vehicle in the UK drives 21 miles per day, which translates to 6-7kWh. It is also limited by the speed of charging, typically 3, 7 or 11kW for an EV charging at home or in the workplace.  These scenarios offer the most smart charging potential because vehicles are parked and charging for longer periods, which makes their charging more interruptible.

There is no need for an expensive rapid charger outside your office or home if you are parked there for several hours. You will have ample time to charge your vehicle with a cheaper, slower charger.

Flexibility from EV charging with higher charging speeds is less interruptible, as it will tend to take place in situations where people want to charge quickly and continue with their journey, e.g. forecourt environments. These rapid charging scenarios will likely be complemented by stationary energy storage, which will help to reduce consumption during peak periods, manage local network constraints and provide grid services, as in the case of Open Energi’s project at South Mimms Motorway Services.

V2X capabilities

V2X tableOpen Energi’s 2017 analysis explored the potential to enable flexibility via smart charging. Turning our attention from smart charging to V2X provides food for thought. Instead of being limited by the amount of demand that can be shifted, V2X flexibility is defined by the amount of energy storage capacity in the vehicle battery (e.g. 40kWh for a Nissan Leaf) and its charge/discharge speed (3kW or 10kW based on current technology). This energy storage capacity could be used multiple times in a day, depending on its charging and discharging.

Conservatively assuming 5 million vehicles on the roads by 2030 – half of National Grid’s forecast – this translates to 200GWh of storage. Assuming they could charge/discharge at a low speed of 3kW, this equates to 15GW of capacity, enough to power 30 million homes! For comparison, National Grid’s most optimistic 2030 forecast of total (stationary) electricity storage capacity is 9GW.

Household demand

Given the battery accounts for some 50% of the car’s cost it is important to consider battery lifecycle and how using it could impact the vehicle’s warranty. However, keep in mind that a vehicle driving the average 21 miles a day will use less than a fifth of its capacity each day (7kWh/40kWh). The graph below illustrates a typical UK home’s daily consumption, which is in the region of 2kWh over the evening peak (4-7pm).

Daily Household Electricity ConsumptionResidential demand profile, source UKERC

Using V2X technology, an EV battery could discharge to the home during this time and already create substantial value by simply taking the household ‘off-grid’ when prices are at their highest. Adding this 2kWh to the 7kWh needed for driving gives a total daily throughput of 9kWh, or 22.5% of battery capacity.

EV storage on wheels

The batteries Open Energi operates in our portfolio of distributed energy assets usually perform a full charge/discharge cycle per day and comply with warranty conditions, so there is potential to extract further value by increasing the utilisation of the vehicle battery. However, in the example of a household we need to evaluate if the spread between the export price during the peak and the import price when energy is recovered is positive to justify exporting to the grid. This is not necessarily the case for larger demand sites such as an Industrial or Commercial user.

Opportunity for large energy users

Sites with greater demand could shift even more energy, and discharge more vehicles at once, without having to export. Essentially, a fleet of commercial vehicles becomes a behind-the-meter energy storage asset for a site when drivers have finished their shifts, displacing site consumption during the peak and recharging the vehicle battery when prices fall. Open Energi’s analysis suggests that this kind of demand optimisation could be worth up to £1,500 per vehicle per year.

The main obstacle today is the price and availability of V2G chargers but this should quickly change. While V2G chargers are relatively difficult to procure at present, V2G compatible vehicles are already being sold at a similar price to comparable EV models. For example, Nissan’s electric van, the e-NV200, does not seem to have a premium for the feature – it comes already equipped with V2G compatible charging technology. As charging technology catches up, V2G will be a standard bundled feature of these vehicles.

Storage on wheels

Projects such as Powerloop, the first large-scale domestic V2G trial in the UK, aim to demonstrate the benefits of V2X in action. Backed by Innovate UK and bringing together a consortium including Open Energi, Octopus Energy, Octopus Electric Vehicles, UK Power Networks and ChargePoint Services, the 3-year, £7 million project will see 135 V2G chargers rolled out on the UK’s electricity grid. EV drivers will be able to access a special V2G bundle when leasing a V2G compatible car.

A two-way charger will enable the driver to charge their vehicle intelligently, using their vehicle battery to power their home during peak times or sell spare power back to the grid. The project will also focus on the role of EVs in delivering flexibility services to the local network. Open Energi’s Dynamic Demand 2.0 technology will aggregate the cars’ battery power to integrate domestic V2G into UK Power Networks’ flexibility services.  Together, we aim to demonstrate the benefits of using EVs to support the grid and reduce costs for drivers.

It’s clear that V2X unlocks a huge opportunity for energy systems globally – with the potential to create a volume of ‘storage on wheels’ that will ultimately eclipse grid-scale and behind-the-meter batter storage many times over. Depending on how we shape regulation, develop technology and create new business models, this huge amount of flexible storage potential could be captured to lower the cost of car ownership, power our homes, and operate our electricity network more efficiently, whilst accelerating our transition to a net zero carbon future.

How the rise of ‘Energy as a Service’ can power decarbonisation

open energi wind farm

Energy as a Service is the latest business model innovation to arrive in the energy supply industry. In short it is all about moving away from buying energy on a per unit (p/kWh) basis and moving towards a fixed fee per month within certain volume thresholds; akin to how we pay for mobile phone contracts. Energy as a Service has emerged off the back of disruption to the way we supply, consume and now ultimately buy energy, which has fundamentally changed energy market economics.

This disruption is the result of four major technology-driven trends:

  • Decarbonisation – The growth of energy supply from zero marginal cost renewable resources
  • Decentralisation – The growth in energy generated from smaller scale low carbon resources either on customer sites (Behind-the-Meter) or at the Distribution Level (Distributed Energy)
  • Digitisation – The ability to measure and monitor machine behaviour in real-time and automate how we use and supply energy
  • Democratisation – The rise in consumer participation, control and choice which is increasingly determining how energy is bought and used

Traditional per unit models work where the dominant cost in delivery of the product or service scales according to the volume used. This was true when the majority of power supplied came from sources that required a fuel input e.g. coal and gas. The more energy consumed the greater the proportional cost of buying and burning that fuel to generate more kWhs of power.  Other components which make up the total ‘at-the-meter’ price have also been charged on a per unit basis to ensure those who use more of the electricity network pay more for it; government taxes, utility profit margins and network charges (with some time-of-use element).

However, when you start to use zero marginal cost power the economics get flipped on their head. Renewable ‘fuel’ is free, so the dominant cost in consuming energy becomes the infrastructure needed to deliver it. Wind turbines, PV panels, transmission and distribution cables have low operational costs once built, so the initial capital expenditure is where the dominant cost lies.

Across Europe average wholesale prices now reflect wind and sun patterns more than the cost of coal and gas, and at periods of low demand and high renewable output we consistently see negative prices. Clearly change is needed as consuming more energy at these times is beneficial to the whole system but a per unit charging mechanism disincentivises users from doing that.

Enter, Energy as a Service. Already we are seeing a shift in network charging towards capacity-based charges instead of use-of-system charges. Wholesale prices are not far behind; the task becomes providing the flexibility to firm up renewable output. Thanks to the digital revolution described above this flexibility can come from consumers’ demand, cost-effectively tapping into flexibility inherent in distributed energy resources behind-the-meter.

Take a given offshore wind site, with known capacity factors of about 50%. It is possible to quantify the amount of flexible energy needed to ensure 99% of customer demand is met at all times. Using existing business assets means it is possible to take advantage of zero marginal cost flexibility in everyday processes (such as heating, cooling, pumping, battery storage and CHPs), avoid unnecessary infrastructure upgrades and minimise efficiency losses in transporting power. Once it is understood how much flexible power is needed to firm up the output of renewable generation the next task is what technologies do you use to meet that flexibility requirement.

Artificial intelligence-powered flexibility platforms – like Open Energi’s Dynamic Demand 2.0 technology – which can manage distributed energy resources in real-time, are critical. They can evaluate the amount of flexibility in existing power-consuming assets and processes – in addition to any battery storage and/or flexible generation (such as CHPs) – and map demand to supply. This then becomes a constant, real-time scheduling problem for the platform to manage; invisibly ramping processes up when wind is abundant and storing as much power as possible, or turning processes down to a stable minimum and discharging batteries or using a CHP when wind output is low.  If real-time scheduling isn’t maintained, the cost structure breaks down, so the reliability of these platforms is critical.

What is important to recognise here is that below a certain demand threshold the marginal cost of putting in place this service is the cost of operating the wind and the software required to schedule behind-the-meter flexibility. This is why Europe’s utilities are making huge investments and acquisitions in virtual power plant technology.

By doing so the costs of delivering energy become fixed and predictable and scale with size of connection instead of actual usage. Exactly like the mobile phone industry where the marginal cost of sending a packet of data is immaterial in comparison to network costs of all infrastructure.

For Open Energi Energy as a Service has always been the natural end-game in maximising the value of Demand Response. It shelters consumers from the continuously changing and complex incentives of the existing Demand Response markets, and instead offers a simple proposition: “By installing demand response software across a range of assets you can pay a lower fixed monthly fee for your energy”.

The clarity and certainty offered by Energy as a Service makes it easy to structure simple, long-term financing solutions for different technologies – e.g. solar PV, energy storage, CHP – and allows businesses to concentrate on what they do best.  All the complexities of power procurement and demand response markets are removed in place of a known fixed fee per month that ensures reliable, clean and affordable energy. 

David Hill, Commercial Director, Open Energi

This blog was originally posted on Current News.

Discover the value of your demand flexibility – explore our VR world!

Open Energi VR landscape

Your electricity demand may be more flexible than you realise. Our analysis suggests that on average up to 50% of a business’ electricity demand can be shifted for up to one hour, with zero disruption to operational performance.

This flexibility is vital to support more renewable power and create a sustainable energy future.

In the UK, it’s created a £9 billion market opportunity. But how much could it be worth to your business?

Explore our Virtual Reality world to find out:

vr.openenergi.com 

Open Energi’s Flexible Energy Survey service provides an accurate, independent assessment of your site’s total demand flexibility and the commercial opportunity it represents for your business.

It includes:

  • Comprehensive site survey carried out by qualified engineers with unique experience assessing distributed energy resources for demand-side incentives.
  • Detailed feasibility report identifying the total flexibility of your site, asset-specific strategies, integration solutions and commercial benefits.

For more details or to arrange a survey, please get in touch.

Open Energi VR works well on desktop, better on mobile and best with a VR headset. Please note, the figures used in this VR are based on current market data and Open Energi’s experience with similar assets and processes across a wide range of sectors. They are intended only as a guide and are no guarantee of future value.

 

Why precision matters for Triad prediction

United Utilities Davyhulme

National Grid recently confirmed the Triad dates for Winter 2017-18. As most businesses know all too well, consuming electricity during a Triad is extremely costly, so accurately predicting and avoiding these three half-hour peak periods is vital. Open Energi’s machine learning approach correctly predicted the specific half-hour Settlement Period (SP) for all three Triad days in 2017-18. Wouter Kimman, Data Scientist at Open Energi, looks back at what happened this year, the growing need for precision forecasting, and what the future may hold.

Triad season 2017-18

The demand patterns and Triad results seen in 2017-18 demonstrate the strength of the Triad incentive. But, as more businesses shift their demand making the ‘peak’ flatter, identifying the right SP is becoming more of a challenge.

The 2017-18 Triads all occurred on a Monday, but with a different SP for each, spanning 35 (5-5.30pm), 36 (5.30-6pm) and 37 (6-6.30pm) by order of date; see Figure 1. The 26 February was the latest Triad to date and only the second time it has fallen in SP 37. Given that historically, 85% of Triads have fallen within SP 35, this represents quite a shift.

 

Triads 2017-18
Figure 1: Triads for the winter of 2017-2018 as published by National Grid

 

The trend for falling overall electricity demand continued, with all three Triad days below 50GW. Comparing the daily peak figures to previous winters (Figure 2) we see the spread between the extremes (lowest and highest daily peak) was also reduced, with peak demand more concentrated around the average 45 GW.

 

Triads 2017-18 demand
Figure 2: Peak demand figures comparing all winters since 2011. Each dot represents a day, and box plots represent the minimum, first quartile, median, third quartile, and maximum of their distribution in demand.

However, quite possibly due to Triad avoidance techniques, the timings of daily peaks were spread out across the evening period, including many more during SP 34. Comparing days with peak demand greater than 46 GW in the last 2 winters to previous years in Figure 3, this past winter had a profoundly different pattern; even compared to last winter, shown on the left.

 

Shift in Settlement Periods
Figure 3: The shift in the SP with the highest national demand from previous winters to this winter. A much broader spread is seen this year, evidence of wide spread Triad avoidance strategies?

Another clear example of the impact of Triad avoidance was provided by the Beast from the East, which gave rise to an exceptional late and severe cold spell. This year’s largest demand peak actually fell on 1 March, just outside the Triad season. The demand profile for that day (Figure 4) shows a very distinct peak, much more characteristic of days of low demand, outside the winter. In contrast, days with high demand within the Triad season had a flatter peak, as seen in Figure 4. As more behind-the-meter flexibility comes on-line the impact of Triad avoidance will continue to be seen on the national daily demand profile, making predictions ever more difficult.

 

Daily national demand profile
Figure 4: Daily national demand profile of various days throughout the 2017-2018 winter, and the 1st March. A very different profile is seen outside of Triad season.

 

Triad Predictions

These shifts in the national daily demand show how successful businesses have been at avoiding Triad periods, aided by increasingly sophisticated strategies. Triad management can now be automated and optimised according to a site’s specific energy profile (and the company’s risk appetite). Using Open Energi’s Dynamic Demand 2.0, our cutting edge machine learning approach enables companies to precisely target a specific SP, minimising calls, disruption, and manual intervention.

As many of our customer’s operations are not able to switch off for long periods of time without disruption (e.g. bitumen tanks that need occasional heating to stay within temperature setpoints, or sewage treatment plants that have a continuous usage pattern) there is considerable value in precisely identifying the 30-minute window in which they should reduce demand. Knowing exactly when a Triad might start allows us to manage equipment to avoid impacting operational performance; Triads can be successfully avoided without allowing processes to violate their permitted control parameter ranges.

For batteries of limited storage duration, this can be even more significant as they can export to the grid during peak-prices. Depending on their capacity, it can be vital to issue a dispatch at the right time, ensuring the system has sufficient state of charge to realise maximum revenue.

To minimise the number of unnecessary calls, Open Energi updates the prediction during the day, given the latest information. An initial prediction gives a good indication of the likelihood of a Triad occuring, and over the season gives rise to around 20 warnings. During the day we then update our prediction, exploiting available real-time data. This allows us to cut the total number of Triad calls in half, while accounting for the uncertainties involved. By using the latest machine learning techniques, and real-time automated dispatch, over the course of a year the total number of Triad calls can be thus be reduced; disruption is reduced while value is maintained.

 

Figure 5: Open Energi’s Triad Settlement Period prediction on the three Triad days
Figure 5: Open Energi’s Triad Settlement Period prediction on the three Triad days


O
utlook for Triads

The electricity system must be able to meet peak demand; enough investment in the network must be provided in order that it can deliver the peak amount of electricity to homes and businesses. Triads are the current way that the transmission network is paid for. At present, there is a significant advantage to businesses in reducing their demand at peak, and as a result, the system peak has reduced. In theory at least (while the price signal exists), less copper is required.

While businesses are focused on avoiding Triad costs, Ofgem is increasingly concerned that their success is creating an unfair charging system, where those least able to afford the cost of the network (i.e. less well-off domestic users) end up paying more than their fair share. Consequently, Ofgem is in the middle of a network charging review expected to result in changes to the Triad system from April 2020. Its intention is to create a fairer charging structure where large, non-domestic users cannot avoid paying their fair share of network costs.

In the meantime, Winter 2018-19 will see two charging reforms coming into effect; updates to Distribution use of System (DUoS) charging and the start of embedded benefit reform. DUoS charges are being ‘flattened out’ across the day, while Triad payments for exporting from distributed generation will reduce gradually from £47/kW to £3.22/kW over the next three years.

As the policy landscape continues to shift – and new markets emerge – we expect the task of managing behind-the-meter flexibility to deliver value becoming an increasingly intricate exercise. The ability to manage demand and generation assets in real-time, according to different site characteristics and constraints, will be crucial to choosing the right course of action to maximise client value.

By Wouter Kimman, Data Scientist, Open Energi

How demand flexibility can boost the benefit of a Corporate PPA

solar panels

More and more companies are turning to corporate PPAs as a way to power their business sustainably and manage their long-term energy costs. Using demand flexibility to help align patterns of supply and demand can boost the benefits all round, as Open Energi’s Commercial Analyst, Dago Cedillos, explains.

The rise of corporate PPAs

The increasing cost competitiveness of renewables and the desire from many businesses to strengthen their sustainability credentials has led to the rise in popularity of the corporate PPA. Through a corporate Power Purchase Agreement (PPA), a company agrees to purchase the energy produced by a renewable project(s). This helps businesses to meet their sustainability goals whilst enabling them to hedge against future energy prices and even bring down the cost of their current energy bill.

Renewable developers have turned to corporate PPAs as a means to enable the delivery of their pipelines. With the removal of subsidies such as the Feed-in Tariffs (FiTs) here in the UK, PPAs can help developers  finance and develop projects by securing long-term energy sale contracts which guarantee revenue for a substantial part of the project lifetime.

How does a corporate PPA work?

A corporate PPA is a contract between a renewable power producer and a corporate, agreeing to supply a specified volume of electricity at an agreed price. It is usually structured to last for 10 years or more, considerably longer than an energy supply tariff which tend to be for one to three years.

There’s no need for the corporate and the renewable project to be located near one another – they could be next door to each other or located on opposite sides of the country.

Of course a company’s demand will not always match a project’s generation. To manage this disparity companies have to go through a licensed supplier who will trade and settle in the market the surplus energy they do not use and/or the additional energy they may require, guaranteeing power delivery and assuming responsibility for issuing the corporate’s electricity. Suppliers take a fee or a premium for administration and taking the risk of balancing the residual of the renewable generation and the company’s electricity demand.

Aligning supply and demand

For example: let’s say a factory with demand profile X (blue line) agrees a PPA with a small solar farm with generation profile Y (grey line). The factory effectively consumes energy generated by the solar farm represented by shaded area A. The area B represents the additional energy that must be bought by the supplier to meet the factory’s demand, whilst the area C represents the surplus renewable energy that is sold to another party as the site’s demand has already been met.

Matching factory demand and renewable generation

The cost of this residual balancing will be affected by market dynamics and the premium charged by the supplier for managing this process.

The overall business benefit of a PPA will be determined by a number of factors, including the demand profile of the site, generation profile of the asset, market prices and the structure of the agreement with the supplier. But the more responsive a corporate’s demand can be to these factors, the better positioned they will be to maximise the benefits of a PPA.

Cutting costs with demand flexibility

This is where demand side response (DSR) and energy storage come in; shifting demand to more closely match the project’s renewable generation profile could maximise the effective consumption of this energy real-time and result in lower residual balancing. This would mean having to buy less energy during the shortage periods, which might be more expensive than that offered by the PPA, and selling back less energy during the surplus periods. Additionally, it could help decrease the imbalance risk of the supplier and make the case for a lower fee or premium.

Demand flexibility and corporate PPAsIt could also present arbitrage opportunities for the business. By shifting consumption away from peak times to cheaper periods, surplus energy from the PPA can be sold on at a high rate, while avoiding punishing network and capacity market charges which occur at the same time. Flexibility could even be used to respond to instantaneous market opportunities, such as high system prices occurring with mismatch in supply and demand, much in the way the trading team of a supplier would do today with large generators.

Optimising a PPA with demand flexibilityThe value of this balancing achieved through flexibility with storage and DSR will vary across hours, days and seasons according to changing market conditions and patterns of supply and demand. What’s needed is technology that can evaluate these parameters in real-time, and optimise a business’ demand accordingly. This is where Open Energi comes in. We’re using our advanced technology, data-driven insight and experience of invisibly managing demand flexibility to help corporates make the most of their PPA.

Our solutions not only help to balance the grid, but can also balance demand real-time against PPA generation. This means businesses can make better use of cheap, renewable energy when it’s there, lower costs for suppliers, and ultimately bring their own energy bills down.

Dago Cedillos is a Commercial Analyst at Open Energi, where he focuses on innovative methods and business models to enable a more flexible energy system. Prior to Open Energi, Dago was part of a clean-tech startup working on a novel carbon-negative electricity generation technology. Dago has an MSc in Sustainable Energy Futures from Imperial College London, and has published a paper on investment strategies for decarbonisation and decentralized energy systems.

Using demand flexibility to reduce supplier imbalance risk

Bitumen tanks

At Open Energi, we are teaming up with energy suppliers and their customers to help make the most of the flexibility in their energy consumption. Using smart demand flexibility to sustainably balance the system, we can mitigate the risk of volatile prices and help reduce rising system charges.

The balancing act

Electricity can’t be stored efficiently or cheaply at scale, so electricity suppliers must balance the energy that they produce themselves or procure from third parties with the energy that their customers use. This means, ahead of time, forecasting how much electricity is going to be generated, forecasting customer demand, and taking any actions to balance them out: buying or selling additional electricity as required.

Any imbalance between generation and demand can result in suppliers facing costly charges from National Grid, who are forced to act in real time to balance the system. Some of the balancing actions that National Grid takes to ensure the lights stay on are expensive and polluting, and lead to gross inefficiencies in the system. During periods when the system is short (insufficient generation / high demand) it might call on a thermal power station to increase its output. Similarly, when the system is long (too much generation / low demand), a thermal power station could be asked to decrease output.

For the flexible energy generators of the UK – namely CCGTs – to be able to respond to these calls, they are run at < 100% of their maximum capacity. The inefficiencies here are twofold. The plants are not run optimally – they use more fuel and produce more carbon per MWh of electricity produced – and, more power stations are required to meet the nation’s electricity requirements. Balancing actions, by their nature, are also taken very close to real time, often outside of the market, which pushes prices up.

An alternative to balancing on the generation-side is to do it on the demand-side: instead of increasing or decreasing the output of a power station, decrease or increase the demand of electricity users. By enabling flexibility behind the meter, for example using battery storage alongside inherent process flexibility, demand-side response can provide an efficient and economical (roughly an order of magnitude cheaper than more traditional methods1) way to balance the system.

Rising system prices

National Grid recovers the cost of balancing from suppliers and generators through Balancing Services use of System (BSUoS) charges, which are passed onto the consumer. A large part of these charges are driven by the imbalance, or system price, which quantifies the cost of balancing energy of the system per half hour period by asking power stations to turn up or down. High prices usually occur when system margins are small; when there is a lack of surplus generation that can be called on. Similarly, low, or even negative prices can occur when there is a surplus of generation. This typically happens during periods of low demand, when solar power is at a maximum – for example on a sunny weekend day.

In the last 6 months or so we have seen the highest and most volatile system prices ever. They peaked at over £1500/MWh in November 2016, compared to an average cost of about £40/MWh over the last year. This peak was caused by a combination of factors. Much of the UK’s aged coal fleet was placed in Supplemental Balancing Reserve (SBR) to be called upon only as a last resort. Then, maintenance to the French nuclear fleet (causing the UK to export rather than import power through the French interconnector) coincided with maintenance to some UK gas peaking plants and low wind speeds, creating a situation where the system got very, very short. When one generator pushes prices up, and these high prices get accepted by National Grid, other generators are likely to follow suit to maximize their profits. For suppliers, this means that an imbalance of a few MW over a few half hours at the wrong time can suddenly become very, very expensive.

Figure 1 shows how system prices have risen since January 2016. With BSUoS similarly rising, suppliers can no longer afford to be complacent with their self-balancing.

 

Suppliers must manage their imbalance to mitigate the risk of volatile system prices
Figure 1: System price over the last 15 months, for periods when the system has been short (insufficient generation) and long (insufficient demand). Prices have increased compared to the mean over the period for both cases

Thus, suppliers are increasingly looking to protect themselves against the risk of coming up short. This is particularly true of renewable generators: you can’t make the wind blow harder at the same time as customer demand peaks (whereas you can burn more gas). Rather than buying in more conventional ‘brown’ (rather than ’green’) generation to make up any gaps at the last minute, or paying the imbalance price on any shortfall, an alternative is to use the inherent flexibility in connected customer loads to alter your demand, and better align with the power being generated by the wind. Instead of flexing the generation, flex the demand.

Flexing electricity consumption

Here at Open Energi, we are using our experience with Dynamic Frequency Response to flex the energy usage of large industrial & commercial consumers to balance the books of their renewable supplier. By intelligently talking to equipment which has energy stored in its processes we can shift electricity consumption without affecting the operation of a customer’s site. For example, the stored energy in a bitumen tank means we can delay heating it for an hour with very little impact on its temperature. Given notice by a supplier that they are short in the next hour and so require a reduction in demand, or, they think system prices will be high, we can delay turning on the tank’s heater until after the price spike.

Figure 2 shows a typical bitumen tank. The blue line shows the tank under ‘normal’ operation and the orange line shows the tank under Open Energi control. Following a request from the supplier (given approximately 30 minutes before hand) to reduce demand at 11am, we can delay switching the tank on, without affecting its operational parameters (the temperature always remains within set limits). We then allow the tank to switch on and heat up after the price spike, shifting its power consumption.

Demand flexibility can help suppliers to manage their imbalance risk
Figure 2: Flexing the power consumption of a single bitumen tank, such that it’s temperature always remains within predefined limits

Do this across a portfolio of tanks, and you make a sizeable reduction in the supplier’s demand during periods when they would otherwise be short: see Figure 3. The energy is recovered later, and, given the energy storage in any one asset, this definition of ‘later’ can be flexible.

Open Energi is working with businesses and their suppliers to manage imbalance risk using demand flexibility
Figure 3: Resulting shift in electricity consumption when flex energy across a portfolio of bitumen tanks

Suppliers save money by avoiding costly imbalance prices and mitigate the risk of price volatility, while managing renewable intermittency and reducing the need for brown generation. By partnering with innovative suppliers who create a market for such flexibility in an open and accessible manner, businesses can use technology to deliver smart demand side flexibility, in real time, with no impact on their operations, while saving money on their electricity bills. This kind of smart, digitized demand side flexibility is crucial to building the decentralized, decarbonized energy system of the future.

1Open Energi analysis

Robyn Lucas is a Data Scientist at Open Energi. She works on demand side flexibility in the UK electricity network; modelling, forecasting and optimizing the usage and performance of a variety electrical loads and enabling customers to intelligently control their electricity consumption. Prior to Open Energi she worked for a technology consultancy, helping clients make the best use of their data. Robyn graduated from Imperial College London in 2015 with a PhD in Physics, during which she worked on one of the experiments at the CERN LHC.

 

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.

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.