Power Responsive success stories: South Mimms battery storage and EV charging

At South Mimms Motorway Services, Open Energi own and operate a 250kW/500kWh Powerpack alongside one of Tesla’s largest and busiest UK charging locations. The project, which is one of the first of its kind globally, was selected as a demand side flexibility success story and showcased by National Grid at their 2018 Power Responsive summer reception.

The Supercharger site can charge up to 12 cars at one time, and since popular charging periods often coincide with peak periods of grid demand – between 4pm and 7pm, when electricity prices are at their highest – flexible solutions are needed to ease the strain on local grids and control electricity costs.

Integrating a Powerpack at the location has meant that during peak periods, vehicles can charge from Powerpack instead of drawing power from the grid. Throughout the remainder of the day, the Powerpack system charges from and discharges to the grid, providing a Firm Frequency Response (FFR) service to National Grid and earning revenue for balancing grid electricity supply and demand on a second-by-second basis.

Combining batteries and electric vehicles makes vehicle charging part of the solution to integrating more renewables without affecting drivers, unlocking vital flexibility to help build a smarter, more sustainable system.

Robyn Lucas, Head of Data Science at Open Energi explained “[the battery] provides a source of flexibility to what is otherwise a very inflexible demand. We do frequency response for most of the time, and over the peak period we use the battery to charge the car up, rather than them charging from the grid.

“Open Energi hope to repeat this blueprint with multiple other stationary storage assets next to EV charging stations. Having stationary storage assets used in this way allows both transport and electricity networks to be decarbonised and allows for greater renewable penetration.”

Power Responsive success stories: Aggregate Industries

National Grid’s Summer Reception 2018 profiled Aggregate Industries’ pioneering partnership with Open Energi as an example of real life achievements to unlock demand side flexibility and the innovation and collaboration within the industry.

Aggregate Industries is the first business to deploy Open Energi’s artificial intelligence-powered flexibility platform, Dynamic Demand 2.0, to deliver electricity cost savings of 10%.

40 bitumen tanks at ten Aggregate Industries’ sites UK-wide have already been connected to the platform, which uses artificial intelligence to automatically optimise their daily electricity use in response to a variety of signals, including wholesale electricity prices, peak price charges, fluctuations in grid frequency, and system imbalance prices.

Aggregate Industries is accessing the imbalance market via Renewable Balancing Reserve (RBR), a product offered by its renewable electricity supplier, Ørsted. RBR enables Aggregate Industries to tap into the financial benefits of participating in the imbalance market, by reducing its demand at certain times.

Over time Aggregate Industries plans to expand its use of Dynamic Demand 2.0 to 48 asphalt plants UK-wide – representing up to 4.5MW of demand flexibility. It is also exploring its wider portfolio of assets and processes to identify where further benefits may lie.

Talking to National Grid, Richard Eaton, Energy Manager at Aggregate Industries explained: “What we’re doing now is rolling out Open Energi’s Dynamic Demand 2.0 platform, where what we do is we flex our assets, not only to calls from National Grid, but also now to calls from Ørsted under their Renewable Balancing Reserve.

“The artificial intelligence within Dynamic Demand 2.0 is helping us to optimise our bitumen tanks leading to a predicted 10-15% reduction in the operating costs of those assets.”

How Artificial Intelligence is shaping the future of energy

Artificial Intelligence can unlock demand side flexibility for end users

Across the globe, energy systems are changing, creating unprecedented challenges for the organisations tasked with ensuring the lights stay on. In the UK, large fossil fuelled power stations are being replaced by increasing levels of widely distributed wind and solar generation. This renewable power is clean and free at the point of use but it cannot always be relied upon. To date National Grid has managed this intermittency by keeping polluting power stations online to make up the difference but Artificial Intelligence offers an alternative approach.

What’s needed is a smart grid which can integrate renewable energy efficiently at scale 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. Most people associate energy storage with batteries, but the cheapest and cleanest type of energy storage comes from flexibility in our demand for energy.

This demand-side flexibility takes advantage of thermal or pumped energy stored in everyday equipment and processes, from an office air-con unit, supermarket fridge or industrial furnace through to water pumped and stored in 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.

This means that 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 instead of paying wind farms to turn off we can ask equipment to use more now instead of later.

Making our demand for electricity “intelligent” in this way means we can provide vital capacity when and where it is most needed and pave the way for a cleaner, more affordable, and more secure energy system. The key lies in unlocking and using demand-side flexibility so that consumers are a) not impacted and b) appropriately rewarded.

At Open Energi, we’ve been exploring how artificial intelligence and machine learning techniques can be leveraged to orchestrate massive amounts of demand-side flexibility – from industrial equipment, co-generation and battery storage systems – towards the one goal of creating a smarter grid.

We have spent the last 6 years working with some of the UK’s leading companies to manage their flexible demand in real-time and help balance electricity supply and demand UK-wide.  In this time, we have connected to over 3,500 assets at over 350 sites, operating invisibly deep with business processes, to enable equipment to switch on and off in response to fluctuations in supply and demand.

Already, we are well on the way to realising a smarter grid, but to unlock the full potential of demand-side flexibility, we need to adopt a portfolio level approach. Artifical intelligence and machine learning techniques are making this possible, enabling us to look across multiple assets on a customer site, and given all the operational parameters in place, make intelligent, real-time decisions to maximise their total flexibility and deliver the greatest value at any given moment in time.

For example, a supermarket may have solar panels on its roof and a battery installed on site, as well as flexibility inherent in its air-con and refrigeration systems. Using artificial intelligence and machine learning means we can find creative ways to reschedule the power consumption of many assets in synchrony, helping National Grid to balance the system while minimising the cost of consuming that power for energy users.

Lack of data is often an obstacle to progress but we collect between 10,000 and 25,000 messages per second relating to 30 different data points and perform tens of millions of switches per year. This data is forming the basis of a model which 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.

Artificial Intelligence model learning to control the electricity consumption of a portfolio of assets

Graph of AI model

More rapid progress could be made across the industry if energy companies made more anonymised half-hourly power data available. It would enable companies working on smart grid technologies to validate these ideas quickly and cheaply. In the same vein, it would be a major breakthrough for balancing electricity supply and demand if energy companies made available APIs for reporting and accessing flexibility; it would allow companies like Open Energi to unlock enormous amounts of demand-side flexibility and put it to good use balancing not just the grid but also helping to optimise the market positions of those same energy companies.

In the UK alone, we estimate there is 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.  Artificial Intelligence can help us to unlock this demand-side flexibility and build an electricity system fit for the future; one which cuts consumer bills, integrates renewable energy efficiently, and secures our energy supplies for generations to come.

Michael Bironneau is Technical Director at Open Energi. He graduated from Loughborough University in 2014 with a PhD in Mathematics and has been writing software since the age of 10.

Can a sharing economy approach to energy deliver a more sustainable future?

Sunshine through tree tops - green energy

As global demand for electricity grows, are there alternatives to building more power stations which make smarter use of existing infrastructure? And in an industry renowned for high levels of consumer mistrust, could an Airbnb of energy finally deliver a consumer-centric energy market?

Technology is shaping our lives like never before, making our world smarter, more efficient and more connected. In the last decade, it has fuelled an explosion of sharing economy business models — adopted by the likes of Uber, Airbnb and Zipcar — who in just a few short years have revolutionised established industries. But can a sharing economy approach help to tackle one of man-kind’s greatest challenges and deliver clean, affordable and secure energy to all?

Sharing economies are a consumer-led phenomenon which work by exploiting excess capacity or inefficiencies in existing systems for mutual benefit. Take Airbnb for example. The wasted asset is your property and the excess capacity is the space you are not using. By creating a user-friendly platform and giving homeowners the security they need Airbnb have built the biggest hotel chain in the world, surpassing the Intercontinental Group in less than four years. They have achieved this because they haven’t needed to construct a single thing.

So how could this apply to the energy industry? As global demand for electricity grows, are there alternatives to building more power stations which make smarter use of existing infrastructure? And in an industry renowned for high levels of consumer mistrust, could an Airbnb of energy finally deliver a consumer-centric energy market?

Since the world’s first power station was built in 1882 the global energy system has worked on the basis that supply must follow demand. Consumers — businesses and households — have been passive users of power, paying to use what they want when they want, whilst electricity supply has adapted to ensure the lights stay on. This has created inefficient systems built for periods of peak demand — in the UK this is typically between 4–7pm on a cold winter evening — which most of the time are massively underused.

But this is no longer the case. Today, our ability to connect and control anything from anywhere means we can manage our demand for electricity in previously unimaginable ways, and consumers are emerging as a driving force for change.

By connecting everyday equipment to a smart platform (just as you might upload your property to Airbnb), it’s now possible for consumers to take advantage of small amounts of “flexible demand” in their existing assets and processes — be it a fridge, a water pump, or an office air con unit — and sell it to organisations tasked with keeping the lights on — like National Grid.

Applying artificial intelligence and machine learning to govern when and for how long assets may respond gives consumers confidence their equipment’s performance will not be affected, and in return for sharing their “flexible demand”, they benefit from cost savings or direct payments.

This sharing economy approach relies on the power of tech and our ability to orchestrate many thousands of consumer devices at scale. Any one piece of equipment can only make small changes to the timing of its electricity consumption — e.g. delaying when a fridge motor comes on for a few minutes during a spike in electricity demand at the end of a football match — but collectively, the impact is transformational.

It means that when electricity demand is greater than supply, we don’t need to fire up fossil-fuelled power stations. Instead, we can reduce demand by asking non-time critical assets to power down for a short while.

If the wind is blowing and too much electricity is being supplied, we don’t need to let this clean, abundant power go to waste, but can ask equipment to shift its demand and make use of this power as it is available.

And we don’t need to keep building more power stations to meet occasional peaks in demand. Instead, we can distribute demand more intelligently throughout the day, reducing the size of these peaks and making better use of existing capacity.

In the UK, Open Energi’s analysis suggests there is 6 gigawatts of peak demand which can be shifted for up to an hour without impacting 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.

This doesn’t make it easy. Unlike other sharing economy success stories, energy is a public good. The need for incredibly robust solutions means the barriers to entry are high. But, if we can get it right, the prize is enormous; a cleaner, cheaper, more secure energy system which gives consumers control of how, when, and from where they consume their energy.

Businesses have already recognised the power they hold and the benefits it can bring, with the likes of Sainsbury’s, Tarmac, United Utilities and Aggregate Industries adopting the tech and demonstrating what’s possible. Households look set to follow, but wherever the flexibility comes from, it’s clear that consumers and the environment will benefit from a sharing economy approach to energy.

David Hill is strategy director of Open Energi. He is an expert on electricity markets and demand-side flexibility, including demand-side response and energy storage. He joined Open Energi in 2010 after completing an MSc Energy, Trade & Finance at Cass Business School.

Why the UK needs an energy security rethink

London at night
Sebastian Blake
Sebastian Blake, Commercial Analyst, Open Energi

Blackout Britain is a headline which has become increasingly common over recent years. Many argue that decades of under investment in generation infrastructure has left the margin between demand and supply in the UK desperately short, raising the possibility of network outages at times of high power demand. Given the blame that would be landed at the Government’s feet were the lights to go out, energy security has been given top priority over the other facets of the energy trilemma; decarbonisation and affordability.

The Government’s solution to this was to devise the Capacity Market as a mechanism to encourage investment in new power plants, with yearly auctions for participants who can provide capacity over the winter peak. Crucially, auctions are held four years in advance of the capacity ‘go live’ date, to guarantee revenue and give investors the confidence they need to build new power stations.

There are, however, major flaws in the thinking behind such an approach. There is much evidence to suggest that the UK is in fact well supplied with power station capacity, that building more stations is unnecessary and that running the system more efficiently on tighter margins is a good thing. And by ensuring there is sufficient power plant capacity to meet the instance of highest demand in the year other potentially greater threats to security of supply are being ignored.

The graph below shows the frequency of the UK grid, which is the primary indicator of the system stability. The network is in balance when the frequency is hovering around the 50Hz mark, however any significant variation either side is a sign of a serious imbalance between generation and demand and could result in a potential shutdown of the network. This isn’t a distant threat: whole towns had to be shut off as an emergency measure in 2008 when grid frequency dropped to 48.8Hz.

Grid frequency graph

In this case, we can see what happed to the frequency when a large supply source – an interconnector between the UK and France – failed, leading to more power being drawn by consumers than was being supplied to the grid. To counteract the resulting frequency drop and avoid a system shut down, a series of automatic measures kicked into action, including turning up thermal power plants (coal and gas) and sending water reserves cascading through turbines of hydroelectric plants.

More recently on the 9th May 2016 there were 37 significant failures across 27 different coal and gas plants as well as the France interconnector; with each one disrupting frequency and testing the grid’s resilience. At one point in the day National Grid issued a warning that insufficient spare capacity would be available in an hour’s time. This is too short notice for a thermal plant to start up (which takes around four hours) so not something the Capacity Market would have helped with.

National’s Grid’s Head of Commercial Operation Cathy McClay has said managing the grid frequency is becoming an increasing headache for our island system. However, the technologies traditionally used to respond in these situations look increasingly unfit for the role. The best new candidate is demand side flexibility – in the form of batteries and demand side response – which offers numerous benefits.

 Energy storage and demand side response offer five core advantages over traditional solutions

  1. Speed of response: Demand side response and batteries can deliver their full power in under 1 second from receiving a request from the network. By comparison thermal plants and hydroelectric generators need around 10 seconds. As the interconnector example shows, this difference is crucial for avoiding a potential network shutdown and will be needed more and more due to continued reductions in system inertia.

 

  1. Decentralisation: Demand side response and batteries are distributed technologies meaning a required level of response can be made up from aggregating together many smaller sites. We have seen how relying on large centralised technologies (like the undersea link to France) poses increased risk to system stability as they represent significant single points of failure. Thermal power stations fail on a daily basis so individual plants cannot be relied upon for response; whereas with distributed technologies this risk is shared across many assets; if one fails the whole service is not compromised.

 

  1. No need for spinning reserve: Traditional providers are only able to achieve the 10 seconds or so when starting from an already running position, hence the generators must be operating at some partial output to provide the quick response. This impacts fuel efficiency by around 10-20%, greatly increasing costs and CO2

 

  1. Flexibility: The network can only absorb as much power as there is demand, so at times of low demand, National Grid must turn down clean and zero marginal cost power from renewable sources like wind to accommodate the thermal generators which must be kept running for frequency response. Demand side response and batteries overcome this problem.

 

  1. Low carbon: By maximising the use of demand side response and energy storage technologies, the UK will be able to achieve further growth in renewable generation; while reducing its reliance on interconnectors and its exposure to volatile gas prices.

 

The high capacity fossil fuel plants which have historically been used to respond to the demands of the grid are increasingly unfit for purpose in a modern electricity network, yet the Capacity Market fails to encourage the development or implementation of smarter, cleaner and decentralised solutions which would provide a more efficient means of addressing both our energy security and other elements of the trilemma.

Neglecting these alternative solutions via the Capacity Market will undermine exactly the thing Government is trying to advance: security of supply. National Grid should be applauded for its efforts to implement change through its Power Responsive campaign – designed to encourage demand side participation in the balancing markets – but many policy makers remain locked into the old paradigm of an archaic industry; no doubt weighed down by the stranglehold of well-established energy incumbency (better known as the Big Six).

For these parties, using distributed assets to balance the system still represents a significant departure from the orthodoxy of constructing and operating a few large centralised assets like Hinkley Point C, which will deliver 7% of all UK electricity when completed.

To achieve a real paradigm shift towards a secure, affordable and low carbon economy, we don’t even need to find new solutions. Distributed and demand side technologies are ready to deliver; we now need to change the supply-focused mind set of our policy makers and operators.

By Sebastian Blake, Commercial Analyst, Open Energi