Domain Model and Security Principles of the re.alto API Platform
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This article is intended as a guide/intro for developers/architects using our API platform.
20.01.2025
Development

Introduction
The vision of re.alto is to support businesses in developing outstanding products by providing APIs and energy-driven data solutions to help build digital products faster. We do this by connecting to devices through their existing IoT connectivity. At the core of our solution is a powerful IoT management platform. It connects to any type of device, streams device data in real-time and securely stores it for future retrieval. The platform can stream thousands of data sets per second, it can aggregate readings, it can retrieve charge data records (where available), and it can be used to manage and steer devices. Integration is also straightforward.
The guide below explains our domain model, the terminology used and our IoT platform’s security principles.
Domain Model Components (Terminology and Set-Up)
The platform is structured in Tenants. Tenant refers to a customer environment. Every Tenant has an administrator. The Tenant admin controls everything within that Tenant. The Tenant admin can be either a person or a program/app, which are known as Principals of type User or Client respectively. A Client is usually used by a backend system/process like an app and has a Client ID and a Client secret. A User logs in using an email and password. It is this Client ID or User ID that defines what you have access to see on the platform. The Tenant admin is also a Principal (which is therefore either a Client ID or a User). Members are Clients or Users that are part of a Tenant but are not admins. Members also either have a Client ID or a User ID, however members cannot remove/add themselves or other members to a Tenant, only the Tenant admin has the right to do this.
In each Tenant, the Tenant admin can onboard devices which we refer to as Entities. An Entity is added in the system via an onboarding request raised by a Principal with access, which also becomes the owner unless a different owner is specified in the request. Any sort of device that we onboard becomes an Entity and receives an Entity ID. Each Entity has an owner. The Entity owner has the right to change its properties. Members have reduced rights and can read the data but cannot alter the properties of an Entity.
Entities can be grouped together in Collectives. A Tenant can have multiple Collectives, making it easy to separate different Entities into groups (depending on company they belong to, for example). Entities that are grouped together in Collectives can be displayed together. Each Collective has an owner that is assigned by the Tenant admin, and multiple members can be added to each Collective, all of whom then have rights to see the data of the Entities within that Collective. “Collective” refers to a group of Entities and of Users who are members of a Collective. A Collective of Entities has a Collective owner and Collective members. The data from all Entities in a Collective can be shared with a number of Principals (User or Client IDs). The owner of the Collective can set certain parameters on an Entity, such as its name. Members can only use the Entities (ie: read their data).
The Collective is a powerful tool to link various Entities together and then share the data with other people or programs. For example, a fleet manager could use a Collective to conveniently see the data from all of their company’s vehicles in one place. However, a Collective could also refer to a household with multiple cars, a heat pump etc, and any member of that Collective could then view the data from all Entities within that Collective.

Security
The security principles are based on the domain model explained in the first part of this article. You must be the Tenant owner/admin or member of the Tenant, or the Collective owner or member of the Collective, to be able to see the data of a device. To authenticate against our platform, a Client ID or User ID is required. Once you have that, you must be the owner or member of a Tenant or Collective in order to access data. Every individual record, Tenant, Entity and Collective is secured with these security rights. The only way to access our platform is to have a Principal ID, which is either the Client ID (for programs) or the User ID (for people). This ID is either a member of a Tenant or a Collective, or the owner of an Entity. This determines whether you can see that Entity and its data and do something with this data or not. If you do not have rights to any Entities, Tenants or Collectives, you won’t be able to view any data.
re.alto’s customer can have one Tenant on our platform but organise onboarded Entities into various Collectives within that Tenant. This means if Company A is working with various companies/fleet managers, for example, they can onboard the vehicles from various companies and organise each of these into their own Collective, meaning each company/fleet manager will only be able to see the data from the cars in their respective Collective and not the data from cars organised into a separate collective by Company A. Any vehicle added to the Collective later can also easily be viewed without any additional work – that is the power of the Collective. Company A is the owner of the Collective within their Tenant, but they can make Fleet Manager A a member of a Collective and assign them rights within that Collective, so that they can see data from vehicles within the Collective. But they will remain unable to view data from vehicles in the other Collectives within Company A’s Tenant. You have to be a member of a specific Collective to see the data from entities within that Collective – and that is where the domain model meets the security model.
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You have been subscribed for the newsletterNew Feature: Charge Sessions API
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We’re excited to announce that our EV connectivity platform now has a new added feature available: the Charge Sessions API.
27.06.2024
Electric Vehicles/IoT Connectivity

We’re excited to announce that our EV connectivity platform now has a new added feature available: the Charge Sessions API.
The Charge Sessions API offers an overview of an electric vehicle’s charging sessions. It enables the platform user to see when, where and how much a vehicle charged and is available as an add-on for any vehicle connected to our platform. re.alto is able to obtain this data from the car with no need for any additional hardware, and we provide this information in a very standardised way for various car brands on the market, making it a versatile and very useful product for those in need of EV charging data.
Using our own Readings API, re.alto’s platform is now automatically able to derive a vehicle’s charge session data based on various information collected from the car, such as its real-time location at all times, the battery state of charge and whether it is currently plugged or not. Our solution spares development time and saves the platform user from having to figure out how to standardise and use all this different data together themselves. This feature is ideal for anyone either building apps relating to EV charging or managing fleets of EVs. Any app that you want to connect with an electric car can very easily determine from this product when a charge session was happening, how much the vehicle was charged and even the location where the charging took place. It enables our platform users to see when a charging session has started and ended, how much the vehicle’s battery was charged, how fast the vehicle was charging and how much energy was consumed in the session. The start and end value of the battery is displayed as a percentage (%), the charge speed is shown in kilowatts and the charge total is displayed in kw/h. This is very useful for apps focusing on dynamic tariffs and/or energy and cost optimisation, for example, to determine when the best time to charge the vehicle is.
For employers/mobility service providers, the Charge Sessions API also offers numerous advantages. The ability to communicate charge session data and determine where a charging session took place is useful for employers wanting to reimburse their employees for their electricity costs for charging at home. Also, when it comes to saving money on charge poles in a company carpark, the charging behaviour of your drivers will ultimately affect how many charge poles you need to offer at your parking facility. If a driver hogs a charge pole all day (or for far longer than necessary to charge their vehicle), you will end up purchasing a larger number of charge poles in order to comfortably accommodate all EV drivers. In collecting state of charge data, re.alto can determine when a car parked at work is fully charged and can inform that driver, so that they can move their vehicle and free up the charge pole for the next user (who we can then also alert to the fact that a pole has now become available!). Improving driver behaviour is a much cheaper and more efficient solution than installing an excessive number of expensive charge poles, especially as EV fleets are expected to continue to grow. Another issue that our charge session API can help alleviate for employers/mobility service providers/fleet managers is the range anxiety of their EV drivers, which often causes these employees to demand an EV with the largest battery pack option available – which is usually the most expensive and is often excessive for their average usage. Analysing charge session information can help employers/fleet managers monitor battery usage and determine whether such a large battery is really necessary for their next electric vehicle order.
With our standardised and versatile APIs, you can save development time and focus on delivering value to your customers. The Charge Sessions API is an optional add-on available through our EV connectivity platform and is ideal for those building an app related to EV charging or for those managing a fleet of EVs / mobility service providers.
This feature is currently still in the beta phase while we work on adding a guided onboarding option aimed at non-developers, but if you are interested in accessing it now, please reach out to our team for more information on how to do so, and we’ll be happy to assist you.
Example from Charge Sessions API:
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You have been subscribed for the newsletterIntegration with BMW

At the end of last year, we announced the launch of re.alto Connect. This product offers cloud-based, assetless connectivity to various kinds of high energy consuming applications at home and now also enables connectivity to electric vehicles. With EV uptake advancing and EVs set to have a fundamental impact on the decarbonisation of our society, re.alto is thrilled to announce that we have now integrated BMW vehicles onto our Connect platform, a significant milestone in maturing the Connect product.
BMW is a pioneer in electric vehicles in Europe and worldwide. The company is driving the energy transition by enabling use cases like smart charging, which creates a lot of value for their customers. Our integration with their platform will help enable the many interesting use cases that we unlock through re.alto Connect, use cases that any company with BMW cars in their portfolio can potentially benefit from. This integration means re.alto has access to the official BMW APIs, enabling us to provide our clients with reliable and high-quality data, while also generating value for BMW’s EV customers, who are partaking in the energy transition and can expect to see their assets increase in value as the ecosystem grows. With increasingly more use cases now arising around capacity tariff optimisation, vehicle and battery health monitoring, employee reimbursement, CAPEX reductions, Energy-as-a-Service and smart charging, there have never been more opportunities in e-mobility.
Alongside standard telematics data, such as charging data records and GPS locations, re.alto Connect gives clients access to the more elusive state of charge and odometer data. We are able to provide BMW EV insights for fleet and private vehicles. While our customers are mainly larger companies operating fleets, the end users of these devices reap many of the financial benefits of the optimisation offered by EV monitoring and eventually by smart charging. The BMW platform currently enables EV insights through re.alto, and we are also in the process of implementing further features, such as the ability to steer the charging of a car, which will ultimately allow us to provide smart charging functionalities to third parties without the need for a smart charge pole.
Our EV insights features offer value to those responsible for residual value calculations and are useful in employee reimbursement use cases. Residual value estimation can help leasing companies and fleet managers better manage their fleets. With some of the data sets we have available now, they can easily assess the health status of these fleets and determine the rate of depreciation of their vehicles. Utilities and charge pole operators, on the other hand, will be interested in state of charge data to optimise charging. This is data that we can provide our clients through re.alto Connect.
We’re currently working on access to start and stop charging commands, which will enable more advanced use cases, such as smart charging and optimisation for a capacity tariff. These are use cases that can be provided by any company with a large B2C client portfolio that wants to offer Energy-as-a-Service. With current end user apps, increasingly more companies are taking advantage of the opportunity in diversifying to other sectors where they can further monetise their extensive user base. re.alto is developing the energy services for third parties to take advantage of. This is an ongoing process, and we will communicate more on this once these additional features have been implemented.
Are you a fleet manager or leasing company interested in capacity tariff optimisation, residual value calculations or involved in employee reimbursement? Or are you an electric utility needing to know state of charge for smart charging purposes? If either applies to you, re.alto Connect is the solution you have been waiting for. Get in touch with us today to find out how Connect can benefit and transform your business.
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You have been subscribed for the newsletterNear Real-Time Data: What & Why
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Near real-time data: what is it & why is it useful?
23.01.2022
Smart Meters/Energy APIs

A look at near real-time data and some of the use cases relating to it.
With the aftermath of the energy crisis still having an effect on us all, any relief that companies can offer their customers when it comes to their energy bills will be welcome. The right energy solution can alleviate some of the pain caused by the energy crisis and cost-of-living crisis. re.alto can save your customers money by determining their energy usage and enabling them to consume more intelligently. Access to near real-time data enables consumers and energy companies to both act and react and is therefore essential for successful energy management. Analysing this data greatly increases the capacity to create value for the consumer and to build more extensive energy services. Knowing what devices are consuming in real-time ultimately enables consumers to make data-driven decisions and provides utilities with the ability to personalise their services for a more customer-centric model, a potential that is yet to be fully realised in the energy sector. So, what exactly is real-time data and which use cases can be applied here?
Real-time data refers to the elapsed time between when the data was generated and when it was transmitted for analysis. Real-time means the time interval is instantaneous, meaning the data needs to be streamed continuously from its point of origin. The energy industry relies heavily on data to maintain its standard operations, but energy data is rarely analysed in real-time or near real-time. Instead, it is normal to see up to hourly intervals for wholesale electricity pricing, and smart meters generally match this settlement infrastructure. There are then further delays before this data is transmitted back to the utility. This means that utilities are often reliant on data that is days old, making it challenging to efficiently balance supply and demand. A monthly, weekly or daily frequency is well-suited to most of the systems within the energy sector, but such frequencies are insufficient for active energy management. Monitoring data in real-time, on the other hand, enables consumers to better recognise and manage spikes in their consumption at certain times of the day. This means they can identify peak hours and make smarter decisions in order to optimise their consumption and reach their energy saving targets. Utilities can use this data to incentivise off-peak consumption. In peak shaving use cases, analysing consumption data in near real-time provides consumers with the opportunity to reduce their consumption during peak periods and positively influence their energy bills.
Head meter data is the digital representation of a household’s total consumption and is therefore essential to any sort of household optimisation when it comes to energy. The main issue, however, as mentioned above, is that the energy sector itself only requires smart meter data to settle electricity bills faster, meaning the industry does not require this data in real-time. When it comes to energy management, however, this data is only useful when it is very granular and provided in real-time or near real-time. re.alto recognises that there are many benefits to having access to smart meter readings in near real-time, especially when it comes to optimisation. The data can be applied to various use cases such as dynamic rates consumption, self-consumption, capacity tariff optimisation and peak-shaving. It enables the optimisation of a household in that the energy consumption in a home can be aligned with the energy production from the PV panels on the roof of the house, for example, to reduce the amount of excess energy injected back into the grid. To ensure that a household’s own installations consume most of the energy produced at home, it is necessary to know what is happening in near real-time. Or if you have a capacity tariff, this data can help you avoid peak consumption and reduce your bill by making you aware of exactly what you are consuming in real-time and in ensuring you do not increase consumption all at once, for example by cooking dinner and charging your EV at the same time. Spreading electricity consumption throughout the day can potentially reduce energy costs at a time when every saving helps.
Great financial benefits lie in knowing in real-time exactly what your devices are doing and in possessing the ability to actively steer those devices. That is why we are developing the solutions to do just that. We obtain data via APIs for almost every energy-relevant asset, however, when it comes to head meters, the infrastructure does not currently exist, meaning the data has to be extracted in a different way. There are various methods of doing this in different countries in the European market, but the end game is ultimately the same: Obtaining data from smart meters in order to optimise energy management. That is why we are launching a new product focussed around capturing near real-time data from smart meters. Watch this space!
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You have been subscribed for the newsletterAlternative APIs for Dark Sky

In this article you’ll be introduced to weather data use cases and the importance of weather data within the renewable energy and digital landscape. We also do a deeper dive into alternative APIs for ‘Dark Sky’, provider of hyper-local weather forecasting, whose API will be shut down entirely by 2022.
Weather plays a central role in the energy industry, most notably within the renewables sector where intermittent generation is so dependent on suitable meteorological conditions. From selection of infrastructure location and ongoing site maintenance to maintaining the delicate balance between supply and demand and influencing market prices, weather can have a far-reaching impact.
As we look to expand renewables production this decade, simple access to high-quality integrated weather data to mitigate the increasing vulnerability to the elements becomes even more important. Weather is impossible to control but data-led intelligence enables the energy industry to accurately predict meteorological conditions and make decisions accordingly – both in short-term day-to day operations and in longer-term strategic planning.
Weather Data Uses Within Energy
Weather forecasting data goes far beyond standard temperature, windspeed and rainfall measurements. Alongside complex analytics, historic data can reveal meteorological trends which are used in determining the most suitable locations for the development of renewable infrastructure with maximum production potential. Wind farms, for example, require a mean wind speed at turbine hub height of 8m/s to be considered ‘excellent’ and historic wind speed data can offer an insight into locations where this looks likely to be possible. When planning new solar installations, assets owners and indeed potential investors need to examine historic weather data which includes not only the level of sunshine hours but also parameters such as hail forecasts and wind speeds to ensure that the site can deliver on an expected yield and withstand adverse conditions – both important for maximum profitability and financial return on investment.
Long-term climate data, incorporating risk modelling for extreme weather events based on climate change analysis, is also used to simulate the impact of such events on facilities and flag potential service interruptions by predicting large-scale weather patterns. Working hand-in-hand with more short-term real-time meteorological information, this data can also play a key role for asset owners looking to mitigate potential damage caused by incoming bad weather. This is relevant beyond renewables – consider the complex data analytics required for off-shore oil and gas platforms which are more exposed to some of the most extreme weather conditions.
Real-time weather data is operationally vital to ease the challenge of volatility that comes with renewable energy generation in particular. Uniquely, both demand and supply can be affected by weather – cold, still, low cloud weather spikes, for example, drive up demand for heating while simultaneously driving down wind and solar production. For grid operators, this unpredictable inconsistency can make balancing difficult. Weather data provides intelligence on the expected volume of renewable energy being fed into the grid, feeding into operational decision-making, and enabling operators to make real-time changes such as reconfiguring transmission network paths based on incoming weather trajectories. This demonstrates well how vital it is for smart grids to be able to integrate and analyse vast quantities of big data in order to perform at maximum efficiency.
The fluctuations in generation and transmission that come from unpredictable weather conditions also have an effect on electricity prices. Put simply, as the weather changes, so too do the prices. For energy traders, the integration of weather forecasting intelligence – both short and long-range forecasts – with complex pricing models is hugely important to anticipate likely changes in both demand and supply. In such a complex sector, the opportunity to match accurate forecast sources to constantly changing portfolio needs offers an unrivalled competitive advantage for traders.
Digital Integration Challenges and Opportunities
As we’ve seen, the energy industry is a widespread user of weather and climate data. Forecasting tools and products are no doubt becoming more technologically sophisticated but there are still significant challenges in integrating them with existing energy IT architecture. It is a barrier that we have seen with energy data across the value chain – procurement and account management processes are traditionally long and carried out offline, making data sourcing and integration a resource-heavy operation. As the renewable sector (and indeed the energy industry as a whole) rapidly evolves, we need to streamline the exchange of precision weather data, making the communication between provider and user far more efficient.
The use of weather data APIs is the most operationally efficient method to do so and can offer a simple data access solution for weather packages tailormade for the energy sector. Last year, one of the most high-profile weather data sources, Dark Sky, announced its acquisition by Apple. Dark Sky offered hyper-local weather forecasting, and, alongside its own standalone app, its API was used as a major source of relatively inexpensive weather data for many third parties, including those within energy. The news that Dark Sky would be shuttering its API entirely by 2022 opened the door to the many alternative weather API options, each offering a wide range of weather intelligence capabilities and many demonstrating functionality particularly suited to the energy industry needs.
Here are some Dark Sky alternative suggestions on the re.alto marketplace:
- The Visual Crossing Timeline Weather API combines historical observations, current 15-day forecasts and statistical weather forecasts in one single consolidated dataset via API call in JSON format.
- UBIMET offers a highly accurate weather API to optimise price models and spot market forecasts for energy suppliers and direct sellers. The API includes weather forecasts for countries, network regions and metropolitan areas as well as population-weighted energy trade forecasts and accurate real-time weather analysis.
- The Meteomatics REST-style API retrieves historic, current and forecast data globally, including model data and observational data in time series and are
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You have been subscribed for the newsletterEnergy Quantified and re.alto - Marketplace Case Study

A Marketplace Case Study
As decentralisation of the energy market drives the rise of a host of smaller industry players, easy access to digital products at volume is now an essential factor for the rapid scalability desired by those at the cutting edge of innovation. A bespoke product offering with a personal one-to-one offline approach is no longer sufficient in today’s digital times. In fact, it only hinders growth and makes the creation of a digital partner eco-system – vital for collaboration and scale – almost impossible.
We have seen in other industries how the API offers the most streamlined approach to offering a digital product or services at scale. The energy industry however remains behind the digital curve, and API integration remains frustratingly low. It is a challenge which Energy Quantified encounters on a regular basis and one which the company is keen to spotlight and lead the way with a solution through a partnership with re.alto-energy.
Set up in 2017 by three veterans of the power industry (and now part of the Montel Group), Energy Quantified (EQ) is a leading provider of high-quality pan-European data and market intelligence. The company sets the standard for modelling and forecasting of the short-term power market, and delivers a vast range of advanced analysis tools, such as weather-powered price forecasts.
The devastating Covid-19 pandemic and its impact on global energy demand has placed even greater importance on the ability to accurately assess and forecast the markets. EQ’s data in particular has provided key insights throughout the Covid crisis into the state of the power industry across Europe, including analysing the impact on spot pricing and forecasting demand recovery scenarios.
As a forward-thinking company pushing the boundaries of digital innovation, EQ recognises the value of digitalisation to its customer base – from analyst and trader to developer – and provides access to its data sets through a range of easy to use APIs. Despite the API availability however, many EQ customers continue to interact with the company through the EQ portal, leaving levels of direct API integration low.
By making their APIs available on the re.alto marketplace, EQ is looking to encourage greater client adoption of the digital end-to-end sales process which is vital for operational and cost efficiency.
Hugo Birkelund, EQ’s CEO and co-founder said: “We believe an acceleration of this digitalization is an inevitable result of a competitive energy sector. EQ’s contribution is to support power-data within a cutting-edge infrastructure. Teaming up with re.alto was just a natural step for us. Together with re.alto we can further simplify data sourcing and facilitate companies to scale their business with a minimum of associated friction and cost.”
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You have been subscribed for the newsletterWhite Paper: Realising the Energy Transition in Times of Change
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The role of the API Marketplace in driving down data acquisition costs and establishing new service-led business models.
Energy APIs

Chapter 1: Executive Summary
The energy industry is in flux, with existing change accelerated by the dual influences of global Covid-19 disruption and a heightened sense of urgency in the fight against climate change.
The upheaval to the status quo presents a unique opportunity for innovation and transformation; for digitalisation to expedite the development of new service led business models and solutions which enable long-term low carbon transition and industry growth in these challenging times.
As this whitepaper will show, the energy industry however remains relatively digitally immature, lacking the understanding and technical capability to fully realise the digital opportunity. In this paper, we explore the existing operational barriers to digital change that are deeply embedded within the industry. In particular, we examine the obstacles preventing the smooth exchange of energy data, a critical element of digitalisation, including the high cost of data acquisition and the challenges presented by legacy IT infrastructure.
At re.alto, our ambition is to accelerate digital transformation and decarbonisation through the standardised exchange of energy data and digital services. We believe that a collaborative approach through API connectivity is the key to business transformation, sidestepping the legacy infrastructure of yesterday. In this paper, we delve into use cases around e-mobility, energy communities and data-driven profiling for utilities to demonstrate how a data-led approach enables operational streamlining and unleashes entirely new revenue streams. The purpose of this whitepaper is to demonstrate the added value of an API marketplace in facilitating this data exchange and driving the creation of a digital ecosystem which ultimately enables the energy transition
Chapter 2: Introduction
Within energy, digitalisation has been a disruptive force for years, but progress has remained painfully slow.
Amongst the talk now of a ‘new normal’, the pandemic will almost certainly accelerate the momentum towards digital transformation as those with more traditional business models struggle to bounce back and find themselves unable to compete at an expedited pace of change. As recovery now becomes the priority, the pan-European infrastructure upgrade initiatives promised to stimulate the sector offer a unique opportunity to accelerate decarbonisation, enabled by digitalisation and an API-led connectivity approach. Post-Covid, building a digital eco-system and forging new collaborative industry partnerships to support next-generation business models will be more important than ever to move towards a dynamic and sustainable energy future.
I. The role of COVID-19 in accelerating change
The energy industry has felt the impact of the pandemic in key areas such as demand reduction and the supply chain thanks to lockdown. Rather than raise new issues however, the disruption from Covid-19 has instead exacerbated existing challenges and is accelerating change that had already been well underway. It has, in fact, given us a fascinating glimpse into the future of a power market where renewable sources (RES) outstrip non-renewables in system share and demonstrated the opportunities for innovation.
At the height of the first wave in April, electricity demand dropped by nearly 20% across Europe as business and transport networks slashed their usage during global lockdown. Despite short-term recovery as restrictions on movement were eased, the longer-term impact of Covid-19 on demand continues to ripple through the energy market. In the last week of July, electricity demand was still 5% below 2019 in all EU countries bar Italy, while global energy demand Is expected to contract by 6% in 2020, the largest drop in more than 70 years.
A combination of lower lockdown demand and surging RES generation has caused electricity prices across Europe to consistently dip into the red. At the same time, demand for non-renewable sources has significantly dampened. During this period, wind delivered 17% of Europe’s electricity, producing 241 terawatt-hours of electricity , while at one particular point in early April, renewables accounted for a record 70% of UK electricity demand. Coal consumption in the UK, on the other hand, fell from 50 Mtpa to 5Mtpa.
Covid-19 and the disruption it has caused should not be seen as the prime cause of this shift in the power mix, but rather an important contributory factor in the acceleration of an ongoing industry transition. Social and political factors have too played their part, in particular, a decline in oil production in light of the Russia-OPEC price war and political volatility in the Middle East. There is no doubt that the energy industry is currently in flux and Covid-19 is helping to further shake up the status quo. While the major European RES generators are experiencing their highest profit margins in years, low wholesale electricity prices mean that energy suppliers continue to struggle to maintain profit margins with their single KW/h revenue stream. Grid operators are encountering greater technical challenges in balancing erratic RES generation, demanding more advanced demand-side management and the increased flexibility that comes from a decentralised system.
One particular benefit of the unique combination of decreased non-renewables production, the rise in RES generation and the worldwide restrictions on mass movement is a reduction in global carbon emissions, which have temporarily plunged by 8% to the lowest recorded levels since 2010. As promising as as that sounds, a rebound in emissions levels is inevitable in the long-term without sweeping intrinsic strategic change across the energy industry and beyond. Growing social and political pressure to reduce CO2 emissions has made decarbonisation a core objective for all energy companies, with an ever increasing sense of urgency as we fight to head off irreversible climate damage, caused in no small part by decades of fossil fuel burning and car exhausts.
The Covid-19 crisis has helped to create fertile ground for rapid innovation. The upheaval presents an opportunity to accelerate the development of new digital solutions which drive both long-term low carbon transition and industry growth in the face of economic stress.
II. The data-led opportunity
Digitalisation is the enabler of both growth and decarbonisation. Fuelled by data, it is the key to overcoming the dual economic and environmental crises of Covid-19 and climate change that we are now facing. Energy data is the very foundation stone of digitalisation in the industry. As we have explored in our previous ebook ‘Understanding how APIs drive the digital transformation of energy’ data is already recognised and valued as a crucial building block in the creation of a smart energy system. It goes beyond simple consumption metrics, spanning the value chain from SCADA data to market pricing and weather forecasting.
Harnessing the power of this data should be a key objective in any digital strategy of an energy company looking to scale. Data connectivity enables innovation on a scale previous unachievable in energy as well as the creation of new customer-centric business models. It is a powerful driver of growth in the sustainable energy sector.
The Obstacles to Capturing the Growth Market
There is a recognition across multiple sectors that electrification is a clean route to a sustainable future, and there has already been a noticeable shift towards a decentralised renewables system with significant technological developments. But while a proliferation in open data combined with increasingly advanced algorithms and availability of real-time processing capability is revolutionising sectors such as telecoms and insurance, the energy industry is failing to keep up. As such we are not yet seeing the widespread evolution of commercial models which adopt the required data-led digital collaborative approach to unleash innovation and take decentralisation and decarbonisation further still. The smooth exchange of data which we see in other industries, a critical element of digitalisation, is hindered in energy by two key barriers to change: firstly, the relative immaturity of the industry in realising the potential of available data. Secondly, the costs associated with data acquisition and, for traditional incumbents in particular, the issues involved in integrating data streams with existing legacy IT infrastructure.
Barrier 1: Realising the potential of data
The energy industry remains fairly rudimentary in its understanding of the value of data and in particular its role in developing new digital products and services quickly and at lower cost. Given this, it is hardly surprising that many organisations within energy still fail to therefore recognise the importance of web based APIs, a standard means of making an organisation’s data and services digitally available to external developers and partners.
The perception remains that APIs belong only within the IT domain, used for internal processes at best. As such, much data exchange nowadays still uses the approach of sending large CSV files to an FTP server, a remarkably outdated method of enabling the communication between two systems. Moreover, CSV files only allow for data in its simplest form while using an FTP server prevents any real-time response or error handling, which significantly restricts the possibility of any sophisticated data interaction between two parties.
Over the last decade, APIs have evolved and scaled in volume, and their worth as a technological interface to facilitate agile internal processes and improve operational efficiency is well recognised. But without a basic understanding of the value of the vast streams of data at its disposal, the energy industry simply will not be able to fully recognise the commercial value of an API as a revenue source in its own right.
Barrier 2: Data acquisition and integration (access and cost)
If understanding the value of data is the first step to digital connectivity, access to data is the crucial second step, or in the case of the energy industry, a hurdle. There is currently no central search engine for energy API discovery as most energy data remains siloed, and navigating the jungle of companies, services and products in search of data in web-based API format is challenging. As the industry further diversifies into new sectors such as smart mobility, data is likely to become even more fragmented. Moreover, a significant lack of transparency around pricing and availability within the market makes it difficult to even benchmark the monetary value of data.
With smart meter data in particular, there is added complexity around the handling and user consent to consider. Unlike data generated by smart phone or social media usage, data generated by smart meters legally belongs to the end user and requires explicit consent before it can be accessed. Data protection obligations may restrict what customer and systems data can be shared, and it requires an awareness of the implications of data security as well as potentially the development of specific IT architecture to support privacy requirements.
Beyond access, the costs associated with integration and ongoing maintenance can be an obstacle. For larger incumbent energy organisations, onboarding each individual API from a new supplier can bring higher than necessary costs around compliance, procurement and security – far outweighing the far smaller basic cost of the API licence – as well as administrative costs stemming from disparate contractual documentation, largely non-standardised and all from separate sources. Each API subsequently also requires significant resource in ongoing management. API providers will regularly update the APIs with new features, security fixes and product improvements, but unless monitored closely, these have the potential to cause backward compatibility issues – and a break in critical business processes – when third-party endpoints are removed or relocated. The more APIs that are integrated, the more prohibitive the level of resource and cost required for initial technical set up and ongoing maintenance. It is unsurprising therefore that data acquisition costs can easily soar, transforming what should be a cost effective and quick solution for rapid product development into a significant investment and budget drain.
Incumbents in particular face a second barrier to digital transformation beyond the cost of data acquisition. A lack of experience in cloud computing and real time processing technology often leaves them incapable of creating or accessing the technology platforms required to deliver big data processing capability. Complex and inflexible legacy IT architecture and a scarcity of technical skillsets ensure that the integration of multiple disparate data sources is prohibitively difficult. For new smaller industry players, the disruptors for whom digitalisation already lies at the very heart of their business model, the challenge lies less in legacy technology and more in the availability of resource and their own limited budgets. They may be forging the innovation path by maximising the value of their own data to offer digital products because they recognise their power to add value to customers. But their internal business processes and offline B2B sales activity remain remarkably analogue in nature and operationally inefficient. These digitally minded companies encounter the same challenges as the incumbents in being unable to devote the required resource to discover, integrate and maintain multiple API integrations as part of a long-term API-led strategy. They simply struggle to fully exploit the value of third-party data internally as well as externally, and as a result cannot efficiently streamline their operations into a cost-effective end-to-end digital pathway.
Chapter 4: Exploiting the Growth Opportunity
Within energy, digitalisation has been a disruptive force for years, but progress has remained painfully slow.
We have now explored the principal challenges faced by both traditional organisations and new industry players around the acquisition of energy data, a pre-requisite for digital transformation. If the future lies in enhanced data connectivity, bringing businesses across the industry together through the technically simplified and cost-efficient provision of such data is the answer, and it comes in the shape of an API marketplace.
Seen in a less comprehensive form in other industries as API management platforms but not translated to the energy sector until now, an API marketplace connects the providers and consumers of data in API format.
It facilitates the connection between parties, simplifying the exchange of data and digital services by amassing them in one place in a standardised form. As a broad high-level outcome, this API economy allows organisations to create and interact with a much broader ecosystem of service providers and consumers, increasing market visibility and opening up new revenue streams with agile product development.
In much the same way as the traditional energy business model of a single centralised supply and a passive consumer is becoming obsolete, so too is the market model of single party transactions – that between one buyer and one seller – which make scaling slow and cumbersome. In today’s connected world, this is being displaced by the more collaborative model of flexible multi partner ecosystems, leveraged through the channel of a digital marketplace and the exposure it brings.
The benefits of an API-led approach
Taking a deeper dive, the API marketplace offers operational and cost efficiencies on a technical level which make a key difference in streamlining day-to-day data-led business activity. In light of the stresses placed on the global economy by Covid-19 and downward trends in spending and investment, these benefits which deliver growth and revenue in times of crisis become increasingly attractive. Put simply, a digital marketplace for energy APIs is the nexus that the energy industry needs to unlock the unrestricted flow of information across the entire value chain in the most technologically sophisticated, cost-effective and operationally efficient manner possible.
The standardisation of data transfer technology in the form of web-based RESTful APIs facilitates integration and allows for faster cross-sector collaboration and digitalisation at scale. It is the modern replacement for the CSV/FTP approach. The importance of having structured data in a standardised format that consumers can easily identify and subscribe to has already been realised across other industries. We already know that there are enormous quantities of fragmented and diverse energy data across the industry; making it available to third parties in standardised API format with standardised contractual documentation improves the quality of the information exchange and reduces friction.
Centralised digital transaction management
As we’ve seen, a data-led approach raises the need for the structured management of a myriad of disparate APIs, which can be time and cost-heavy. Standard API management platforms, much like developer portals, tend to focus on the basic transactional nature of an API subscription – a means to solely find and subscribe to the API. Some enable evaluation of the utilisation of the product, any service disruptions, and the technical adequacy of a setup. This delivers data, yes, but does little to mitigate the hefty resource requirements for setup and ongoing maintenance. A digital marketplace however delivers a full API management package in one integrated system. It not only provides a discovery mechanism for a full range of API products (and not simply a vendor-specific set), but also offers an array of online tools which span discovery, centralised governance and standards, security, user consent management, contract management, centralised billing and settlement and usage analytics, all designed to maximise the value of the APIs.
Let’s take the example of a utility requiring the subscription of five separate APIs in the development of their own digital app aimed at improving customer experience through usage tracking and digital billing. At least one of the APIs will comprise smart meter data. Acquired separately, the utility would need to spend a significant amount of time sourcing the APIs, negotiating the contracts and obtaining all required documentation, managing the initial set-up and performing all ongoing monitoring and maintenance. Consider firstly that the entire initial B2B sales process of finding and subscribing to the APIs will likely take place offline as there are unlikely to be any digital processes in place with each of the five API providers. Secondly, consider the added complexity brought by the integration of smart meter data from residential end users – aggregated and anonymised, but still requiring user consent management and throwing up privacy and security considerations which cannot be ignored.
And finally, consider the time that will be required to monitor and maintain each of the five APIs in the long-term to ensure that any updates or fixes from the provider do not interrupt the functionality of the utility’s own new digital app.
Now, let’s take that example and translate it into the resource and cost savings of performing the same transactions and long-term management of the five APIs on one integrated API marketplace. All discovery, subscriptions, standardised documentation and user consents (where needed) can be taken care of in one place in a fully digitalised online sales journey, while all ongoing maintenance can be bundled together to leave the API consumer one update to perform rather than five. The increased efficiency of an outsourced fully end-to-end digital process on a digital marketplace is staggering.
Chapter 5: Digital Transformation in Action Today
USER-CENTRIC SERVICES PUTTING THE CUSTOMER MORE IN CONTROL
USE CASE 1: E-MOBILITY AND SMART CHARGING
Following an initial fall of 25% in the first quarter of 2020 , global sales of electric vehicles (EVs) are still expected to rise this year as the transport industry turns to electrification to achieve decarbonisation targets. Europe continues to show the strongest market growth despite the impact of Covid-19, expanding its market share overall to 26%. Regulatory changes around emissions standards, iterative improvements in battery storage and postCovid government stimulus packages are likely to further drive the shift towards this more sustainable form of transport. In France, for example, the government has now increased the incentive from €6,000 to €7,000 for purchasers of EVs, while in Germany the incentive has been upped to €9,000.
As the market scales and EV technology matures, e-mobility now plays a key role in the connected energy IoT ecosystem and demonstrates the vast potential for digital synergy between the energy and transportation sectors in the pursuit of a greener future. Through smart charging and Vehicle to Grid (V2G) technology, there is an opportunity for EVs to provide a digital solution to the challenges of grid balancing as RES generation increases. Although still in its infancy, V2G technology enables the discharge of electricity stored in EV batteries back into the national grid to help balance supply during consumption peaks, enabling dynamic multi-directional electricity flow. Integrating EV data with real-time tariff, market pricing and smart meter data from a home energy management system (HEMS) creates a smart charging opportunity from which the EV company, the grid operator and the vehicle owner all benefit. By controlling the time and rate at which the EV is charged based on local demand and electricity market prices (while still adhering to the minimum charge levels set by the owner), the EV company can open up new revenue streams such as the provision of balancing services to the grid operator as well as wholesale arbitrage opportunities based on the bulk buy of electricity. The vehicle owner is incentivised by the possibility of low-cost or even free charging, while the network operator is able to balance the local grid with greater flexibility. Cross sector communication and the smooth exchange of real-time data is the key here, and the sustainability gains are vast.
USE CASE 2: ENERGY COMMUNITIES AND DISTRIBUTED GENERATION
Local energy communities (LECs), where generation is dispersed across smaller local plants, have previously attracted much support, largely thanks to how they empower consumers to play a far more active role in the green energy transition. Over recent years, LECs have become increasingly prevalent, particularly across Europe, as consumers now demand a more active role in their own supply. Pioneering digital technology is accelerating the move towards this decentralised system where renewables play the starring role. Virtual power plants (VPP), for example have been described as the ‘internet of energy’ and are showing promise in taking power aggregation to a new level and driving virtual generating capacity to take pressure off centralised assets.
Aligning grid balance at a local level through technology-enabled demand response solutions offers up far greater flexibility to flatten the load curve and integrate volatile sustainable sources. It has been forecast that digitally enabled demand response combined with increased storage could reduce the curtailment of PV and wind power from 7% to 1.6% by 2040 in the EU alone, cutting a possible 30 million tonnes of CO2 emissions[1]. Continued advances in storage solutions are likely to take this decentralisation trend even further. It is an evolution of a new collaborative business model, turning a previously centralised system on its head with clear cost benefits to the consumer – no longer a system designed on the economies of scale as with behemoth fossil fuel plants, distributed generation drives down costs instead through the economics of small-scale and volume. But in order to thrive, digitalisation is vital to coordinate the more granular nature of distributed generation and ensure that the power supply remains consistent, reliable and secure.
USE CASE 3: UTILITIES AND DATA-DRIVEN PROFILING
Energy data, such as that from smart meters and HEMS, provides utilities with two valuable insight streams: consumption metrics and behavioural patterns. Following in the enormously successful footsteps of Amazon and Netflix, utilities are now beginning to realise the value of the millions of human behavioural big data points – such as how and when customers interact with services – and understand how it underpins the ability to understand and engage on a more meaningful level with the customer. In particular, it offers the opportunity to add value by delivering personalised services and apps based entirely on data-driven preferences. Digital flexible billing and visibility over real-time variable tariff information are just two examples of such user-centric services which put the customer more in control and help to avoid annual bill shocks. For the utility, these services not only enhance customer loyalty but also could in theory shorten the settlement cycle – delivering an accurate invoice directly to a customer over a digital channel is shown to speed up payment, cutting the risk of bad debt.
Chapter 6: Conclusion
Integrating a seamless end-to-end user journey on a single digital platform is a paradigm shift in customer engagement for the utility sector, moving from product to service delivery with a new Energy-as-a-Service business model. The agile development required to deliver this digital service is made technically possible by the integration of data from multiple sources in an API-led approach.