X-Energy

X Energy

Open Energi is proud to once again be sponsoring X Energy. Organised by The Crowd, the event will bring together senior energy, sustainability, property, and facilities professionals to explore the intersection of energy and tech, inspiring and connecting the leading minds from a mix of energy intensive sectors.

It will explore how disruptive technologies, new energy management strategies and financing models are exponentially changing energy programmes in large organisations, and share knowledge and latest thinking amongst the community.

Date: 1 October 2018

Location: London

Further information and details on how to apply for a space are available from the The Crowd’s website.

 

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.

 

Business Development Manager

Oxford Brookes campus

About Us

Headquartered in London with global ambitions, Open Energi is an energy tech company applying artificial intelligence and data-driven insight to radically reduce the cost of delivering and consuming power.

Our advanced technology platform connects, aggregates and optimises distributed energy assets in real-time, maximising value for end users and providing invisible demand flexibility when and where it is most needed to create a more sustainable energy future.

We’re breaking new ground in demand-side management, working with leading businesses, suppliers, developers and world-renowned technology partners to deliver innovative solutions that put our customers in control of how, when and from where they consume electricity.

If you would enjoy the challenge of deploying a ground-breaking technology into an emerging market and want to work for an innovative company where you have complete belief in the product and service you represent, we might be just the place for you.

The Role

We are looking for an experienced Business Development Manager to join our growing team. You will be reporting to our Commercial Director. The role will involve leading and managing sales campaigns to support the acquisition of corporate customers. The successful candidate must focus on the creation of best practice across all aspects of sales management to include:

  • Develop and execute sales and marketing campaigns to meet company targets
  • Define the sales cycle from a strategic and tactical perspective detailing the customer acquisition and implementation process
  • Facilitate “right first time” customer qualification to improve workflow / handover and ultimately shorten the sales cycle through lean and efficient processes
  • Achieve / exceed business targets, expressed in terms of number of won accounts including revenue and margin
  • Influence and shape the customer’s energy strategy via board level interactions developing strategic partnerships
  • Create business opportunity for Open Energi across all customer asset bases by understanding the corporate usage profiles and how best to utilise group assets to deliver mutual value
  • Be accountable for all sales performance measures including pipeline development, appointment ratios, conversion measures and management of the sales CRM system
  • Ability to develop bespoke sales propositions to meet complex customer requirements
  • Adopt a strategic selling approach, which considers technical and economic buying influences to be active at influencer, recommender and decision maker levels
  • Utilise the Open Energi sales qualification model and CRM system to maximise effective account wins
  • Develop an in depth understanding of the business drivers and requirements including technical, economic and environmental influencers in key vertical segments

Requirements

We’re looking for someone with:

  • At least 5 years’ work experience in a similar role
  • Proven experience and success in direct sales, generating new business in a business-to-business or Public Sector corporate market
  • Proven ability to develop and maintain an effective network of contacts and build relationships at all levels of the customer / prospect organisation
  • High level of literacy, written communication and analytical skills
  • High level of numeracy & commercial judgement
  • Self-starter with effective problem-solving abilities, especially for unstructured tasks
  • Interest or expertise in the energy market
  • Enthusiasm for new technologies and their potential impact
  • Commercial and financial knowledge
  • Excellent communication skills, capable of clearly articulating data to a wide audience

Qualifications

  • Bachelor’s degree in a relevant subject, achieving at least a 2:1
  • Post-graduate education (such as a Masters’) is desirable, but not essential

Remuneration and Benefits

  • Competitive salary with discretionary bonus
  • Based in Open Energi’s London office
  • Career development opportunities

To apply

Please send a covering letter and CV to recruitment@openenergi.com. Due to the quantity of applications we receive, we regret that we are unable to give specific feedback on unsuccessful applications.

Commercial Analyst

Dynamic Demand 2.0

About Us

Headquartered in London with global ambitions, Open Energi is an energy tech company applying artificial intelligence and data-driven insight to radically reduce the cost of delivering and consuming power.

Our advanced technology platform connects, aggregates and optimises distributed energy assets in real-time, maximising value for end users and providing invisible demand flexibility when and where it is most needed to create a more sustainable energy future.

We’re breaking new ground in demand-side management, working with leading businesses, suppliers, developers and world-renowned technology partners to deliver innovative solutions that put our customers in control of how, when and from where they consume electricity.

If you would enjoy the challenge of deploying a ground-breaking technology into an emerging market and want to work for an innovative company where you have complete belief in the product and service you represent, we might be just the place for you.

The Role

We are looking for a Commercial Analyst to join our growing team. You’ll be reporting to our Commercial Manager and working closely alongside our Data Science and Technology teams to help inform business strategy and ensure our market leading solutions stay ahead of the curve. It’s a start-up environment, so you will be working on multiple tasks and must be comfortable working across teams and projects.

The role will include:

  • Commercial analysis and support
    • Working with data scientists on performance reporting
    • Internal reporting for investors and Finance team
    • Using models and other quantitative methods to support the Commercial team as required
    • Risk and scenario analysis
    • Market research and analysis of UK & international demand response markets
    • Researching new services and assessing their commercial value
    • Business case development and commercial agreements
  • Policy, sales & marketing support
    • Techno-economic modelling
    • Researching emerging technologies relevant to the business (e.g. energy storage)
    • Policy analysis and briefing of business on key industry and regulatory issues

Requirements

We’re looking for someone with:

  • At least 2 years’ work experience in a similar role
  • Strong quantitative background
  • High level of literacy, written communication and analytical skills
  • High level of numeracy & commercial judgement
  • Strong Excel modelling skills
  • Self-starter with effective problem-solving abilities, especially for unstructured tasks
  • A critical thinker with intellectual curiosity and thoughtful opinions
  • Interest or expertise in the energy market
  • Enthusiasm for new technologies and their potential impact
  • Commercial and financial knowledge
  • Excellent communication skills, capable of clearly articulating data to a wide audience

Qualifications

  • Bachelor’s degree in a relevant subject, achieving at least a 2:1
  • Post-graduate education (such as a Masters’) is desirable, but not essential

 Remuneration and Benefits

  • Competitive salary with discretionary bonus
  • Based in Open Energi’s London office
  • Career development opportunities

 To apply

Please send a covering letter and CV to recruitment@openenergi.com. Due to the quantity of applications we receive, we regret that we are unable to give specific feedback on unsuccessful applications.

How EVs can help drive a more sustainable energy future

Tesla South Mimms Supercharger and PowerPack

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

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

Rise of EVs

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

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

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

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

EVs and electricity demand

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

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

 

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

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

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

Flexibility scenarios

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

EV speed table

EV charging scenarios table

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

EV flex profile 2020 down

EV flex profile 2020 up EV flex profile table

Opportunities: smart charging for flexibility

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

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

Dago Cedillos is Strategy and Innovation Lead at Open Energi

Methodology

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

Charging speeds

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

EV speed tableScenarios

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

EV charging scenarios table

Main assumptions

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

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

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

Extracting flexibility

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

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

Flexibility profiles

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

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

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

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

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

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

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

Securing Digital Distributed Energy Infrastructure

Open Energi Engineer

The Internet of Things (IoT), a term used to denote the digital infrastructure where any digitalised asset, no matter how small, can connect to an invisible mesh of other assets through the internet, has recently become synonymous with security breaches and exploitation. This is true not just in a domestic setting, where flaws in Samsung’s ‘Smart Home’ let hackers unlock doors and set off fire alarms[1], but also in industrial IoT systems, where hackers were able to change the levels of chemicals being used to treat tap water[2]. While security breaches in websites are common, with credit card details frequently stolen, breaches to industrial systems connected to the internet are fewer and more recent, as such systems were previously isolated from public networks.

In the world of Demand Side Response (DSR), security is one of the priorities of most asset owners. DSR assets have a core purpose other than helping to balance the energy system, so a DSR provider must be able to demonstrate that they will never prevent the safe and correct operation of the asset, be that treating wastewater in a sewage treatment facility or refrigerating food in a supermarket. This condition must hold even in the presence of bugs in the DSR provider’s software, and even if their own systems are penetrated by hackers. The usual practices of data encryption, strong access controls and network segregation only provide part of the answer, as they still don’t guarantee safe operation under all possible failure modes.

This condition may seem unreasonable, but in critical systems development it is crucial. A nuclear facility operating normally is run through a software system, but all safety-critical checks are duplicated in hardware interlocks that take over should the software fail in any way[3]. These interlocks are immutable and thus immune to hacking or software bugs. In space missions, NASA has since the Challenger and Columbia incidents started to use consensus of multiple software systems developed by several independent teams to control rocket operation to eliminate the possibility that a single bug could affect the mission[4].

As the DSR industry progresses towards standardisation and common best practice guidelines, a key safety requirement must be safe operation of the asset under any failure mode. Open Energi on-site controllers are always supplemented by independent hardware or software interlocks that cannot be modified by us, creating an orthogonal layer of control required to operate critical assets. For example, on asphalt sites, we supplement our own controls with hardware interlocks to disable our control should the temperature of the tank increase beyond a safe limit. On water sites, we augment our controls with independently developed PLC code that checks that the asset is still within its control parameters and disables our control immediately if not. This dual layer of security means that even if our systems are compromised by an attacker, the DSR assets will continue to operate safely.

Michael Bironneau is Technical Director at Open Energi.

[1]     Wired Magazine. May 2016. ‘Flaws in Samsung Smart home let hackers unlock doors and set off fire alarms’. https://www.wired.com/2016/05/flaws-samsungs-smart-home-let-hackers-unlock-doors-set-off-fire-alarms/

[2]     The Register. March 2016. ‘Water treatment plant hacked, chemical mix changed for tap supplies’. http://www.theregister.co.uk/2016/03/24/water_utility_hacked/

[3]     L.J. Jardine and M.M. Moshkov. Nuclear Materials Safety Management, Vol 2. 1998. See eg. p.151.

[4]     Organizational Learning at NASA: The Challenger and Columbia Incidents. 1989. J. Mahler. See eg. p.63.

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.

Daring to imagine an energy future that’s unlike our past

Future Energy System

Two years ago, when we walked into a pub in Old Street to chat with Forum for the Future about creating a virtual power station, we had no idea we’d end up convening a project to challenge the fundamentals of how our energy system works – called the Living Grid.

Our early conversations were all about reducing our reliance on fossil fuelled generators, and proving the potential of demand-side management to revolutionise our energy grid.  But it turns out, when you mix inspiring conversations with businesses, universities, government bodies, local authorities, community groups, start-up technology providers, industry associations and everyone in between with a standing-room-only presentation from Michael Pawlyn, you end up with an initiative that questions every aspect of how our energy system is designed.

Why limit the conversation to the role of sophisticated, demand-side technologies. If our goal is an energy system powered by renewable energy rather than fossil fuels, we must look at the capabilities, interactions and design of every aspect of the system and question whether it has to be this way, or whether there is a better, alternative approach – and we must unleash our imaginations to do it.  The Living Grid has become a community of people and organisations who are deliberately challenging the beliefs we hold about our energy future, to open up solutions to us that are simply not possible using the same thinking that created our fossil-fuel powered grid.

“The system of nature, of which man is a part, tends to be self-balancing, self-adjusting, self-cleansing.  Not so with technology.”  E.F. Schumacher

The Living Grid is provoking us to look beyond carbon reductions at the mismatch between our human energy system and the wider, living energy system that’s evolved here over the last 3.8 billion years of life.   Rather than cycle solar energy through a closed-loop, cooperative system – as other life forms do around here – our linear, centralised grid releases energy into the atmosphere by burning fossil fuels, wasting it rather than recapturing it. ‘What it would take to make our alien energy system part and parcel of nature again? 

As founding technology partner, Open Energi is proud to have helped bring the Living Grid into existence with our customers Aggregate Industries, Sainsbury’s, Tarmac and United Utilities.  As the Living Grid grows, we’re pleased that other organisations who share its vision, such as Smartest Energy, are getting involved to usher-in the next stage of development. This next next phase is starting with a global, online conversation to reimagine our legacy grid.  Are you curious about how nature would design our energy system?  Join the debate here.

The Living Grid is a project convened by Forum for the Future.  To find out more about the Living Grid and how you could get involved please contact: g.adams@forumforthefuture.org or h.hauf@forumforthefuture.org

 

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.