Manual vs Automated Trading

In essence, optimising flexible assets in traded energy markets means trying to maximise (or minimise) the captured price for whatever energy can be sold (or bought) by the device in question: a gas power station, battery storage or just a single electric vehicle. In practice, it is often a highly complex exercise requiring processing and a combination of information from two distinct sources: the asset characteristics and market intel.

This cross-optimisation involves continuous calculation over different time horizons, as market opportunities (like Day Ahead auctions) and asset limits (such as ramp rates restrictions) must be planned against. A classic example would be a trader managing a gas power plant; assessing changing market conditions and working closely with plant operators to understand variable physical parameters, such as efficiency at different power outputs or the energy required to start up the generator.

This information must then be considered when selling energy into the power markets, and that involves a careful trade-off between physical and price considerations. For example, when low demand causes low prices overnight, plants must choose between shutting down in the evening then starting again in the morning or running through the night, selling power at a loss – whichever is the more economical.

 

Adapting to new technologies

However as storage, demand response and hydrogen production become the dominant tools for balancing the grid, this is also driving change in the methods for optimising assets. Novel technologies are being deployed at the megawatt or kilowatt level, not gigawatt, meaning many more assets will be involved in making up the required level of balancing capacity.

Each device has its own features and characteristics, such as power capacity or response time, as well as dynamically changing parameters impacting optimisation, eg state of charge (SoC) or energy recovery period. So it is clear when dealing with thousands of individual assets the complexity of the problem scales greatly.

Even for larger Front-of-the-Meter batteries, warranties are becoming increasingly complex to manage in real time; specifying rest periods or dynamically limiting depth of discharge, as opposed to simply warrantying a certain number of cycles per year. Also, many projects will be co-located with variable renewable power to exploit the benefits of a shared connection, effectively giving a dynamically varying export connection to factor into optimisation.

 

Pros and cons of automation

In this world, automation is fast becoming essential. Allowing the principles of continuous asset optimisation can be applied at a scale far below what would be economical for a human trader.

Open Energi has been trading fully algorithmically in the Day Ahead markets for over a year and has some key learnings.

On the face of it picking the highest and lowest hour in the day is simple (and fairly predictable). However, to maximise revenue you must also respond to more real time signals which occur within day (eg Triad), which alters your SoC from the planned schedule. This creates a problem when submitting bids in advance for the trading day before the current day has ended, as you do not yet know what SoC the battery will be at at the start of the trading day.

Automated fixes are able to easily correct for misalignments to get round this; however, doing so in the most economical fashion is harder. And the problem is exacerbated when dealing with more dynamically changing markets like the intraday continuous, which require thinking between different trading horizons.

 

Manual plus automated trading – a winning team

Overall, traders still have the upper hand on algorithms in areas like price formation, especially during extreme events like 4th March, and the best solutions will be ones that exploit the strengths of both. This is the principle of our solution Dynamic Demand 2.0 Trader, where full automation capabilities will perform the heavy lifting but oversight from Erova Energy’s 24hr trading desk provides the manual oversight and possibly intervention if greater opportunity is identified.

Ultimately, combining the strengths of power traders and algorithms provides the best optimisation. And ensuring each is capable of running independently provides the built-in resilience that proves its worth as COVID-19 pushes systems to their limits.

 

For a free consultation about automated trading, call +44 (0)20 3051 0600

Batteries in the Balancing Mechanism

The Balancing Mechanism (BM) is the primary flexibility market in the UK. In 2019 over 2TWh of flexibility was procured through the BM with a value worth over £800m. Batteries are only a recent (and small) participant – the vast majority of flexibility is provided by CCGTs and some through pumped storage such as Dinorwig.

Batteries have had over a year in this market and have steadily seen increases in activity, helped by the introduction of the Distributed Resources Desk, while upcoming Project TERRE could also help non-traditional providers receive dispatches. Hence, while batteries remain a niche player in the BM, compared to the dominant technologies of CCGT and pumped storage, there has been a steady increase in activity.

Figure 1 – Activity by batteries in the Balancing Mechanism has been increasing over the last year

Batteries in the BM – The Basics

The Balancing Mechanism is manually dispatched by the ESO Control Room – providers submit prices and volumes but only deliver (and are paid) when selected. Dispatch decisions are made based on a number of operational criteria, of which volume and price are just two. For example, only certain technologies are able to meet certain needs: thermal plant provide inertia but batteries don’t.

However, battery storage does have its own unique benefits as batteries can respond extremely quickly and accurately in either direction. This quality is being exploited by the Control Room with batteries delivering short bursts of power of mostly under 10 minutes duration (see fig 2). Traditional thermal providers cannot do this, given their ramp rate restrictions.

The most obvious difficulty batteries bring is that they are duration limited, whereas a gas power station could increase its power indefinitely. This means, once a battery has discharged completely, it cannot sell any more energy and so must recharge, either through trading or by waiting to be dispatched in the other direction. Batteries can be dispatched in either direction throughout the day – even if the system is long, batteries may be offered up, and vice versa, so leaving the battery empty (or full) would result in missed dispatches and lost revenue.

Figure 2 – A day of BM actions for a battery, light area showing availability and dark bands are dispatches. Most dispatches are under 10 minutes in duration.

 

State of charge – The limiting factor?

State of charge (SoC) is, therefore, a massively important consideration for both operators and National Grid alike. However, unlike the physical restrictions of thermal plant (such as minimum output), SoC is not captured in the BM, given it is a novel issue. We can infer when SoC has drifted significantly, though, as batteries adjust their available power (MEL and MIL) to represent 15 minutes of storage. This means that when less than 15 minutes output is available in one direction, the system can only be dispatched at this reduced level.

For a two-hour system this only has a small impact – state of charge can drift significantly in either direction before this limit is hit. However, for a one-hour system the impact is much more significant, as the battery could potentially be offering up reduced availability 50% of the time.

Overall, taking a much more active role in managing SoC is necessary to maximise benefit, especially for more limited duration batteries.

 

Being Active

Market optimisation of batteries within the BM takes two forms: integration with other trading strategies, and through much more dynamic provision of bid and offer price. Both of these offer solutions to more actively managing SoC to reduce time spent offering reduced availability.

Trading

The most obvious route to managing SoC during the course of the day is through the intraday markets. If one or more offers in a row start to deplete SoC, energy can be bought on the intraday market to recharge the system. However, doing so may not always be the optimal solution – eg if the price is too high, or perhaps it is likely a bid will arrive soon anyway.

An advanced optimisation and forecasting solution combining manual and automated inputs is needed to effectively manage SoC through trading; system warranty is a constant consideration and confidence will be needed that any actions will increase profitability later in time.

For the example below, purchasing just 30 minutes of energy at the time shown would increase total daily returns by 13%.

Figure 3  – A day of BM actions for a battery, with energy purchased through intraday markets around 9am (green), and corresponding increase in availability and dispatches shown in grey

 

Bid/offers

Although operators have no control over whether their assets are dispatched in the BM, they can influence the likelihood of being dispatched in either direction by adjusting their posted prices, or by providing stepped bids and offers.

Increasing bid price in response to low SoC could be provided to increase the chance of dispatch, in order to then capture higher revenues across the whole day. Meanwhile, stepped bids and offers provide the Control Room with two or more prices, which can be paid to access different levels of power output.

However, this route still has a limitation in being dependent upon being dispatched, even if the probability of being so can be influenced.

 

Conclusion

The BM has long been talked about as the holy grail for battery operation but there is still a lot of uncertainty over when (and indeed whether) that point will be reached as system balancing transitions from CCGTs (with infinite duration headroom and footroom) to fixed duration energy storage.

However, recent activity has provided good signs for batteries to be the principle candidate to take over from CCGTs as the UK moves towards net zero, and we expect to see further design aspects of the BM to be updated in favour of storage assets, to enable NG ESO to meet its target of zero carbon operation by 2025.

Meanwhile, value from the BM continues to increase and challenge frequency response revenues – Open Energi and Erova Energy will be launching our Balancing Mechanism offering in the coming months, so watch this space!

 

For a free consultation about trading in the Balancing Mechanism, call +44 (0)20 3051 0600

Solar plus storage – The benefits of co-location

The UK will need 30GW of storage to meet our climate goals, according to Imperial College. That’s 10 times the current capacity. There are many questions this raises, such as ‘what is the appropriate technology mix?’, but if we consider the form predominantly being developed now (lithium-ion batteries of under or around two hours duration), one of the main questions is where best to situate this?

So far the vast majority of volume has been deployed as front-of-the-meter installations – a standalone site with a dedicated connection for the battery alone. However, given that connections can be costly or administratively difficult to obtain, a more cost-effective solution would be co-location.

In this blog we will dig into some of the advantages of co-location of batteries with solar farms (PV installations with a dedicated connection). We will leave the current policy/regulatory framework to the side and focus on the fundamental benefits.

 

The case for co-location

When new generation connects to the grid, it has to pay for the new copper in the ground. This isn’t cheap. For a battery (short duration, lithium-ion) the connection typically represents 10-20% of the total capital expenditure – and can be much higher, depending on the conditions of the local network (eg if you are unlucky enough to be the marginal connection requiring a sub-station to be upgraded).

If the battery was able to share an existing connection with a solar farm of the same size, it could save the 10-20% of upfront cost; it would still need to buy an import connection, which the solar farm doesn’t need, to ensure the battery can draw from the grid to charge, but the economy would be significant.

In the UK, solar PV (without tracking) has an average capacity factor of 10-15%. This means that for the vast majority of the time the connection is an expensive sunk cost, lying there unused. By sharing it with storage, the return on investment from the connection increases several times over.

 

Why solar and storage are perfect bedfellows

Sharing one connection becomes a problem when both energy sources are producing at the same time. Export from one resource will constrain the ability of the other to export. With solar and battery storage, we find that this is rarely the case; ie both assets are very seldom trying to use the connection to export at the same time [see fig 1].

This is due to the price cannibalisation of renewables – where prices are lowered at times of high renewable generation because they produce at zero marginal cost, and so will sell power at any price above zero. There is sufficient solar power in the UK (>12GW) that during the middle of the day market prices will drop lower.

If we are performing price arbitrage with the battery, it is obvious that we would not be looking to discharge at these times when prices are low. We want the highest prices – usually over the evening peak. In fact, we have found that when optimising the battery against Day Ahead prices, a conflict occurs with the solar generation less than 1% of the time.

Figure 1: Generally, the battery looks to discharge at times of high prices which does not align with solar output

What this means is that we can effectively trade the two assets separately from each other, rather than as one. This has great benefits because solar predictions are best made at portfolio level, taking advantage of geographical dispersion to neutralise stochastic cloud impacts on production. Therefore, the solar can be traded as a portfolio, while battery activity can be scheduled separately.

This also highlights one major advantage of pairing batteries with solar rather than wind. Solar has very high diurnal periodicity, so we can guarantee there would be no production over the most lucrative peak time (4-7pm, especially in winter). The same cannot be said for wind; so if it a wind farm was generating during this peak period there could be large entailed opportunity cost for the battery.

Given that the battery is the more controllable resource, and solar produces at zero cost, the battery should accommodate the solar generation and plan activity around it.

 

The need for advanced optimisation

Pairing solar with batteries, then, looks like an obvious and straightforward win. However, there is more nuance.

While Day Ahead prices will rarely incentivise discharging the battery in the middle of the day, there are often later market opportunities that do; for example, if a large generator trips off the network to create a shortage. The most advanced battery trading strategies will cycle far more than once per day by looking to optimise at each time horizon, to stack value across the day.

Given that cloud cover could have a strong impact on PV output, there will still be many instances where a solar farm has the connection unutilised in the middle of the day [fig 2].

Figure 2 – Clouds drive large short term volatility in production

To take advantage of this we need reliable, real time monitoring of the solar farm (we can only dispatch the battery and make use of the connection if we can be certain the solar PV isn’t) and dynamic responsive controls to ensure solar output is tracked closely (to prevent overloading the connection point).

Dynamic Demand 2.0 Trader is powered by our fully automated platform, needed to support this level of sophistication. Control logic is held both locally on the battery, to ensure responsiveness to changing site conditions, and centrally in the cloud, enabling responsiveness to live price opportunities provided by Erova Energy’s advanced market insight.

With this level of automated control and trading insight, pairing solar with storage represents a cost-effective solution for storage location and a potentially lucrative way forward for energy investment.

 

For a free consultation about co-location and your energy investment, call +44 (0) 20 3051 0600

Here’s to the end of coal. But the revolution in energy is just beginning.

This article was originally published on 18 June at Open Access Government

David Hill, Commercial Director, Open Energi talks about the necessary infrastructure required to achieve the government’s ambitious net-zero emissions target and whether the hype matches reality


At precisely 3.12pm on Friday 31st May, the UK went two weeks without burning a single lump of coal for the first time since the Industrial Revolution. Social media channels buzzed with the #coalfreefortnight as commentators across the energy policy spectrum chose to mark the occasion with a tweet.

We’ve come a long way since the ‘dark satanic mills’ of William Blake’s iconic poem. It is right that we celebrate milestones like coal-free fortnight. But consider this. It has taken the UK 130 years finally to turn its back on coal. With the spectre of climate change looming larger and more tangible by the day, we must ask ourselves whether we are moving fast enough and smartly enough to deliver the revolution in energy delivery required to satisfy future demand while protecting the planet?

Renewable energy, comprising wind, solar, and biomass generation hit 42GW in the UK last year, accounting for 33% of total capacity. Meanwhile, analysis by Carbon Brief suggests up to 50% of the UK’s electricity could come from renewable energy by 2025. Progress at this level is encouraging. But integrating this level of renewables cost-effectively is challenging. Unlike traditional thermal sources of power, turning wind and solar on and off according to demand is simply not possible. Sceptics are also quick to raise the question of what to do when the sun doesn’t shine, and the wind doesn’t blow.

A smart solution to a complex challenge

When dealing with intermittent supply, such as wind and solar power, flexible capacity management becomes a fundamental need and challenge. The goal is to reach a point where we no longer require polluting power stations to ‘fill in the gaps’ when wind turbines and solar powers aren’t generating.

Achieving this requires energy storage to act as a buffer, easing pressure on demand when supply is too low, or saving valuable energy from renewables on a very windy, or sunny day where too much energy is being produced.

Most people associate energy storage with batteries. Battery storage systems allow energy consumers to store low cost, renewable energy and deliver it back at times of peak demand. For example, if you have a battery storage system integrated with a solar farm, it is possible to use photovoltaic (PV) power to charge up the battery for free during the day, drawing on that power at peak times, or selling that power back to the grid.

Applications for energy storage projects in the UK have grown from 2MW in 2012, to over 6.8GW in 2018, according to trade body RenewableUK. Little wonder, as batteries are already proving their value in helping organisations save money on power while doing their bit for the planet. But in our pursuit of low-cost clean power, arguably the cheapest and cleanest type of energy storage comes from the pockets of flexibility in our demand for energy.

Finding the hidden pockets of flexibility

Demand-side flexibility involves getting energy consumer to change their energy consumption patterns based on certain market signals. A lot of us practice a version of this already at home. For example, we switch lights off when we’re not in a room, or we use the washing machine at times when energy is cheaper.

The same applies at an industrial scale. Think about a supermarket fridge, an industrial furnace, or a water pump that feeds a local reservoir. The electricity consumption patterns of these types of devices are not necessarily time-critical. Provided they operate within certain parameters – such as room temperature or water levels – they can be flexible about when they use energy.

When electricity demand outstrips supply, instead of ramping up a fossil-fuelled power station, certain types of equipment can defer their electricity use temporarily. And if the wind blows and too much electricity is being supplied, then instead of paying wind farms to turn off we can ask equipment to use more now instead of later.

That sounds simple enough, but imagine trying to do this at scale, often with multiple assets on a single site, all with varying requirements. It would be virtually impossible to manage, and completely impossible to scale. Until now.

An automated approach to grid flexibility

Artificial intelligence and machine learning techniques are enabling us to keep an eye on multiple assets on a site, consider all the variables, from weather forecasting, through to pricing, and then make a series of intelligent, real-time decisions on how and when these assets should be using energy.

In the UK alone, we estimate there are 6 gigawatts of demand-side flexibility which can be shifted during the evening peak without affecting end users. Put into context, this is equivalent to roughly 10% of peak winter demand and larger than the expected output of the planned Hinkley Point C – the UK’s first new nuclear power station in generations.

Get low-cost, clean energy – with your car

Things become even more exciting when we add electric vehicles into the mix. Imagine if the charging points we used to charge our vehicles at home run on a system connected to technology which pinpoints the optimum time to charge the battery. Cars could help to absorb energy during periods of oversupply and to ease down demand during periods of undersupply. Your car would effectively become an energy storage unit that could help power your house with clean, low-cost energy.

Thanks to rapid advances in technology it is possible to envision a fully autonomous, self-balancing grid which delivers all the clean energy we need, incredibly cheaply. This is not decades away. Everything I have mentioned exists, is proven, and is scalable.

We’re forecasting up to 30GW of capacity in the UK by 2030, stemming from a mix of energy storage, combined heat and power units (CHPs), electrolysers and Electric Vehicles, through to more traditional demand-side response assets such as industrial pumps, boilers and chillers. Our technology already enables us to address all of these assets, unlocking potential cost-savings of up to £8 billion per year by 2030. When you begin to think about the opportunities this unlocks, it starts to put the long, slow demise of coal into perspective.

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.

 

Innovative research project aims to support greater local integration of Solar PV

solar panels

Increasing levels of solar PV are having a growing impact on the operation of the low voltage (LV) network. The need for new grid connections has impacted project viability and in some areas of the country Distribution Network Operators (DNOs) have been forced to limit new solar integration. However, new technologies are introducing ways to make smarter use of the abundant free energy provided by the sun and deliver new revenue streams, without the need for costly infrastructure upgrades.

Funded by Innovate UK, this innovative research project aims to support greater solar PV integration, by forecasting solar output in near-time with better accuracy, and enabling generation to interact dynamically with demand.

In the South West of England, where these challenges are particularly acute due to a constrained network, Meniscus Systems, BRE National Solar Centre, Cornwall Council and Open Energi are collaborating to create short-interval (every 5 minutes), location-specific solar intensity and power predictions that will improve local grid operation, optimise the performance of solar farms and enable operators to participate in Demand Side Response (DSR) schemes to maximise revenue, with or without energy storage.

Cornwall has the fewest grid interconnections with the largest solar PV installed capacity – over 475MW of large-scale (1MW+) solar farms – leading to network operating problems. Resulting constraints imposed by the DNO make it harder to connect large scale renewable generation. The ability to better predict and manage the performance of solar PV on the LV network is an important step towards the creation of local energy markets, and will help to ensure that Cornwall’s residents, communities and local economy benefit from the low carbon energy transition.

The project will make use of:

  • Real-time and historic satellite based imagery to predict solar intensity for any location at intervals of 5 minutes on an hour ahead basis.
  • Historic and near real-time PV data from the Cornwall Council solar farm at Cornwall Airport Newquay (CAN) to test and demonstrate the system and explore the role of on-site battery storage.
  • Open Energi’s expertise to deliver accurate, real-time PV-based DSR solutions to DNOs and owner/operators of solar farms to more efficiently manage local networks.

Accurately modelling the commercial benefits of solar PV and battery storage will be an important aspect of the project. If predicted solar generation is higher than the export limit of the site, a battery can be charged instead of curtailing generation, discharged to grid during a later period of high demand, and in the meantime the battery can be employed for DSR. For a site with no installed storage, generation can be curtailed at times when the network is constrained in response to DSR signals, such as Demand Turn-Up. Accurate predictions allow the DNO or Transmission System Operator (National Grid) to efficiently manage their network

With the UK’s solar capacity forecast to rise to 15.7GW by 2020 – from just over 9.3GW at present – using advanced technology to more efficiently integrate and optimise solar PV sites is vital to create a more sustainable energy future. Due for completion in early 2019, this project aims to pave the way for the smarter use of solar PV via peer-to-peer energy markets that benefit local communities, delivering a smarter, more flexible energy system across the UK.

The lead Project Team comprise:

  • Meniscus Systems – Project Lead and delivery of solar intensity predictions in a form that will allow integration with the DSR market.
  • Cornwall Council – owner/operator of solar farm which will be used to test and demonstrate the system.
  • BRE National Solar Centre – responsible for ensuring the system meets the requirements of the PV industry and validating the system’s performance.
  • Open Energi – DSR aggregator responsible for identifying DSR revenue opportunities and systems needed to deliver this capability.

For more details, please get in touch.

Robyn Lucas is Head of Data Science, Open Energi

New consortium to develop domestic V2G charging technology in UK

EV smart charging

Last month saw the announcement of almost £30million in Government funding for V2G projects. Open Energi is part of a consortium which secured funding to develop the first large-scale domestic trial of vehicle-to-grid (V2G) charging in the UK, as part of a three-year, £7million project.

The consortium, named PowerLoop, comprises Open Energi, Octopus Energy, Octopus Electric Vehicles, UK Power Networks, ChargePoint Services, Energy Saving Trust and Navigant. Together, our objective is to roll out V2G charging technology to UK electric vehicle (EV) drivers in the next 12 months. Over the course of the three-year project we aim to demonstrate the benefits of using domestic V2G to support the grid, reduce costs and deliver a more sustainable future.

A total of 135 V2G chargers will be installed in a ‘cluster’ delivery model that will facilitate research into the impact of widespread EV rollout on the UK’s electricity grid. EV drivers will be able to access a special V2G bundle, Octopus PowerLoop, 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.

This smart charging approach means EVs can be managed to the benefit of the system, accelerating the transition to a sustainable energy future, supporting low carbon growth and creating value for the driver.

Recent analysis by Open Energi found that EVs could provide over 11GW of flexible capacity to the UK’s energy system by 2030, demonstrating their huge potential as a significant grid resource, able to provide flexibility to support renewable generation, balance electricity supply and demand and alleviate strain on the network at a local and national level.

The technological challenge is to drive down the cost of single phase, bi-directional chargers and to develop software that controls the charging of many thousands of batteries distributed around Britain, without impacting drivers.

Open Energi will lead on developing a bespoke V2G aggregation platform and will work alongside UK Power Networks towards integrating domestic V2G into their flexibility services. We will draw on our extensive experience of working with businesses to connect, aggregate and optimise industrial equipment, battery storage and generation assets on a second-by-second basis, for participation in Demand Side Response schemes.  This includes a project at South Mimms Welcome Break Motorway services, on the outskirts of London, where we operate a Tesla Powerpack alongside one of Tesla’s largest and busiest UK charging locations.

By working with EV owners and the distribution network operator – UK Power Networks – the consortium will demonstrate the benefits of using domestic EV batteries to provide grid flexibility, cheaper transport and energy to homeowners, and help to accelerate the decarbonisation of the UK’s power and transport sectors.

By Dagoberto Cedillos, Strategy & Innovation Lead, Open Energi

Faster Frequency Response: A Cost-effective Solution to Future System Balancing

open energi wind farm

Creating a sustainable energy future will take decades and the pace of technological development will lead to ideas and solutions that no one has even thought of yet. This innovation will come from the next generation of energy leaders, who are already conducting vital research at universities across the globe.

 Over the last year, we’re delighted to have been supporting Yifu Ding, who is studying for an MSc in Sustainable Energy Futures at Imperial College. Yifu has been assessing the value of faster frequency response times in power systems, and Open Energi’s Dagoberto Cedillos has been one of her supervisors. Yifu’s project was recognized as the Best MSc Research Project in the cohort, and we’re pleased to share a post from Yifu about her work.
Y_Ding_Headshot

What is System Inertia?

In a stable power system operating with a fixed nominal frequency (50 Hz in the UK) electricity supplies must closely match loads on a continuous, second-by-second basis. This is especially difficult during some special cases such as the power pick-ups after big football games or a royal wedding.

Undoubtedly, achieving such a real-time balance is not a simple thing, but there are many approaches. Large power systems have an inherent property which provides the quickest response for contingencies. In a conventional power plant like coal, gas and even nuclear, electricity is generated by a turbine, basically a large spinning mass of metal. The inertia stored in these rotating turbines provides an energy store which automatically stabilises the system and insulates it from sudden shocks. In an event of a generation outage or surge in demand, inertial energy is released which prevents the frequency from falling. Equally the inverse happens in the case of a sharp increase in electricity supply or decrease in demand.

After that, the system operator begins to manipulate power assets through an array of automated measures already in place (like different frequency response products) and by sending out manual notifications. In response to these, large-scale power stations adjust their outputs. Hydroelectric reservoirs release or pump water. Aggregators control loads or battery assets they manage to provide a response.

Challenges for System Balancing

In light of the decarbonisation trend, great changes have been undertaken in the UK power system. Old methods relying on fossil-fueled power plants to balance the system are challenged and we need to explore new options.

As a rule of thumb, we are losing the system inertia. According to the National Grid System Operator Framework (SOF) 2016, approximately 70% of the UK system inertia is provided by thermal power plants. Unfortunately, the rapidly increasing volume of renewable generation units with power electronics interfaces, including solar PV and wind turbines, are not synchronized with the Grid. Therefore they don’t contribute to the system inertia.

Fig1a synchronous coupling

Figure 1: Generators contributing (or not) to the system inertia (From National Grid SOF 2016)
Figure 1: Generators contributing (or not) to the system inertia (From National Grid SOF 2016)

In our research, we considered ‘Gone Green’ and ‘Steady State’ scenarios from National Grid Future Energy Scenarios (FES) 2017, to compare and contrast what could happen in the near-term future. We found out that the inertia of the UK system will fall from 198 GVAs in 2015 to 132 -155 GVAs by 2025, as large numbers of thermal power plants are closed to meet carbon reduction targets.

Figure 2: The future scenarios considered in this research according to National Grid FES 2017
Figure 2: The future scenarios considered in this research according to National Grid FES 2017

Why Faster Frequency Response?

From this point of view, our power system will become more ‘erratic’ than before due to lack of this self-stabilization property. To counter this we could use more Frequency Response (FR) services, or perhaps something else?

We can envisage a power system with a stable frequency as a large tank with a stable level of water. The current inlet and outlet represent the generation and demand respectively. If a sudden imbalance occurs between inlet and outlet, we need to respond quickly in case the water level becomes too low or overflows.

In this fashion, one of the effective solutions is delivering faster-acting response. In July 2016, National Grid launched and tendered a sub-second FR service called Enhanced Frequency Response (EFR). Currently it is provided by batteries which can respond fast enough to provide a similar level of security to the inertial response from conventional power generators.

Value of Enhanced Frequency Responses

A few statistics from our research and other documents give you an idea of the exact economic benefit from delivering this new FR service.

By developing an optimization mathematical model to simulate power generation, dispatch and balancing in a row, we estimated the economic benefits of EFR will reach £564 to £992 per kW by 2020. National Grid has already contracted 201 MW of EFR, therefore the total economic benefit is estimated to be up to £200 million. This result conforms to the estimation published by National Grid on 26 Aug 2016.

Figure 3: A screenshot of the daily power generation and dispatch outcomes from the optimization model.
Figure 3: A screenshot of the daily power generation and dispatch outcomes from the optimization model.

But this isn’t the whole story. Although the fast-acting FR service demonstrates many advantages, there are still obstacles when it comes to the implementation.  For the system operator, an issue which might arise is how to determine the optimal mix of those FR products. Otherwise some of them could be undersubscribed or oversubscribed as mentioned in System Needs and Product Strategy (SNAP) report from National Grid.

Stakeholders in the balancing markets, such as electricity storage operators, can make themselves invaluable by providing such a service. However, we should note that it is designed to be fulfilled continuously, meaning it’s unlikely to be delivered in combination with other network services. In this case, the operator can only obtain the single revenue from the asset, risky from an investor perspective. Providing such a service is technically challenging since it requires a sophisticated state of charge (SoC) control to meet the service specifications and manage battery throughput.

As we look into the future balancing markets, fast-acting FR services indeed provide a cost-effective solution towards the low-carbon power system. Planned streamlining of  procurement mechanisms and ongoing technology development will help to fully unlock its potential.