FORESIGHT Climate & Energy Spring/Summer 2021

FORESIGHT — 12 Climate & Energy

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Digits, Data & Metrics HOW DIGITALISATION IS FURTHERING THE ENERGY TRANSITION

METRICS

BLOCKCHAIN

ARTIFICIAL INTELLIGENCE

Grid in search of a brain

New tools aid the business case

PAGE 10

PAGE 16

PAGE 28

PAGE 42

Using the correct data in the right way

A quieter revolution

MICROGRIDS

DIGITALISATION AND THE ENERGY TRANSITION

A great white whale FORESIGHT Climate & Energy SPRING / SUMMER 2021

PUBLISHER FORESIGHT Media Group

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EDITOR David Weston david@foresightdk.com

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The 21st Century has brought technological advancements that were once unimaginable. Digitisation of work flows, processes and our everyday lives are more than ever linked to one another. This interconnectedness provides huge opportunities for the energy sector to further strengthen and accelerate the transition from fossil fuels to renewables. In this special issue of FORESIGHT Climate & Energy, our twelfth, we join the dots between what digital technology can do for the energy sector and what the energy sector is doing with digital technology.

A 2020 report by McKinsey, a US-based management consulting firm, highlighted the problem facing the energy sector as it attempts to digitise: “For energy companies, achieving value from digital technologies has become the great white whale: anxiously hunted, dimly perceived, enormous, and elusive. They assumed that, as engineering-savvy organisations with a history of ingenuity, they could easily find the value from digital. Reality has proved more difficult.”

Finding and applying the right technologies and applying them effectively has been a challenge so far. But with the rapid pace of development in computing and technology, new applications are being developed constantly. While it has taken longer than some may have expected, in the coming pages, FORESIGHT highlights some of the cutting-edge projects that have worked out how to apply digital tools to speeding the energy transition.

Among the most advanced of those we uncover is the experimental Cornwall Local Energy Market in the UK. The project takes digital innovation to its limit in renewable energy system management by demonstrating how to maintain grid frequency and deal with imbalances using a trading platform for simultaneous action at both transmission and distribution level. It is an important real life example of how digital products are helping to navigate the ever more complicated energy ecosystem.

Distributed ledger technology, meantime, particularly blockchain is a digital technology whose benefits have remained “elusive” to energy companies, despite emerging on the scene to significant fanfare a couple of years ago. Development of the technology is ongoing with new iterations that may make it better suited to the energy sector than seen to date.

What the analysis and case studies in this issue indicate is that the energy transition is still a human problem and will be solved by humans. The digital tools that are being applied increasingly to the energy system should be used to support decision making by actual operators. Alone they cannot and should not be depended on to reliably manage the grid or guide us to a decarbonised economy. That will take the right decisions made at the right time by people with the right knowledge and experience: experts steeped in scientific fact.

www.climatecalc.eu Cert. no. CC-000001/DK

David Weston EDITOR

CONTENT

METRICS

ARTIFICIAL INTELLIGENCE

MICROGRIDS

BUSINESS

USE THE CORRECT DATA IN THE RIGHT WAY

THE GRID IN SEARCH OF A BRAIN

THE RISE OF MICROGRIDS

Advanced computing is helping to process mounds of data into usable information

Increasing reliability for urban and remote consumers

EMERGING MARKETS GAIN FROM THE DIGITAL EVOLUTION OF ENERGY

Measuring the correct data points will give a fuller picture to decarbonise the energy space PAGE 10

BLOCKCHAIN

PAGE 28

SOUTH AUSTRALIAN ROOFTOP PV FACE EXPORT TRIAL

An AI research project aims to ease grid congestion

A quieter revolution is underway to the one that was first promised PAGE 16

BLOCKCHAIN FINDS A PURPOSE IN TRACKING ENERGY UNIT ORIGINS

SOUND BUSINESS CASE NEEDED FOR VIABLE MICROGRIDS

Showing the value is essential to setting up a microgrid

The roll-out of mobile phone networks offer easy access to energy-as-a-service models PAGE 58

PAGE 48

PAGE 36

TRADITIONAL RULES DO NOT APPLY IN THIS EXPERIMENT

PAGE 42

WE HAVE TAKEN THE PROCESS AND TURBOCHARGED IT USING DIGITAL TOOLS

LOCAL ENERGY AUCTION TRIALS MADE POSSIBLE BY DIGITALISATION

The UK is using AI to help control grid frequency as traditional providers retire

Cornwall’s Local Energy Market provides clean flexible capacity for local and national grid operators

PAGE 38

PAGE 52

BIG PICTURE: REMOTE CONTROL

Unmanned vehicles at renewable energy projects improve accuracy, speed and cost of data collection

PAGE 8

INFOGRAPHIC: ZETTABYTES

The sheer mass of data is increasing at a phenomenal rate PAGE 26

Distributed ledgers can help guarantee the origin of electricity PAGE 24

FORESIGHT

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METRICS An influx of data is changing the roles of energy players across the value chain but it needs to be accurately gathered and correctly assessed before meaningful conclusions can be drawn.

Ensuring the data is right to begin with is essential to the success of the energy transition

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n 2009, in the wake of the crippling global financial crisis, economists Joseph Stiglitz and Amartya Sen published a report investigating its causes. The authors suggested that governments had been overly fixated on increasing each country’s gross domestic product (GDP)—the total market value of all the final goods and services produced. They argued that focusing on this single key performance indicator ignored other issues affecting citizens and therefore the economy—contributing to the 2008 recession. Speaking to the New York Times newspaper at the launch of the report, Stiglitz said: “What you measure affects what you do. If you don’t measure the right thing, you don’t do the right thing.”

This thinking can also be applied to the world’s energy systems and its decarbonisation efforts, especially as the sector takes advantage of the higher levels of data processing, digitisation and the new business models this creates. No longer can the sector focus on just the one or two metrics such as demand levels or carbon intensity.

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Although more data helps decision making, a range of different metrics also need to be used to create a fuller picture of the energy system, so network operators, utility companies and decision makers can better navigate the market towards a decarbonised economy in a sustainable, just, and financially viable way that avoids catastrophic climate change.

“The issue is you have a multidimensional space.

If you look at it from any single viewpoint certain aspects of that space will be obscured by what’s in the foreground. People tend to go for very simplistic metrics which, if they also get coupled with policy, can drive the market into really silly places,” says Bill Bordass, an expert on energy performance in buildings.

DATA PROCESSING Digitalising the energy sector has resulted in huge amounts of data becoming available for utilities, grid operators, generators, governments and consumers.

To decarbonise effectively, these organisations must not focus on one sole metric or data point but use FORESIGHT

Orderly process Identifying the right metrics and processing them correctly can help make sense of a decarbonised world

TEXT David Weston ILLUSTRATION Clara Terne PHOTO ©Johannes Marburg, Geneva

Use the correct data in the right way

FORESIGHT

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METRICS

the tools provided by new technology to create a multi-dimensional picture of what is happening. It is about making use of a host of different measurements, which is where the rise of information technology can make an impact.

“Europe is obsessed with primary energy [use],” Bordass says. “Primary energy is [measured from] what emerges from the well-head or the wind turbine. That’s fine if you have a set of energy supplies that are fungible but actually, they’re not. A large fly in the ointment is primary electricity. A kilowatt-hour of primary electricity out of a wind turbine is certainly not fungible with some black glob out of tar sands,” he adds.

DATA AS INFORMATION Successfully decarbonising the economy by mid-century, as required by the Paris Agreement, depends on using the correct data. “What’s important about data is that you can turn it into information,” says Benjamin Beberness of German multinational software corporation SAP. “Having that data is great, but then how do we turn it into the information to make the right business decisions? That’s where analytics will become more and more relevant.”

Products backed by digital tools are being developed to help provide better insight on the market.

Thierry Mortier, from business services firm EY, says the digital technologies being applied today will help to support this transition. “The three emerging technologies that are crucial to making that architecture happen are: Internet of Things (IoT)—so every single device is somehow connected to the cloud set at different levels; distributed ledger technology such as blockchain—basically technology that will allow you to administer or capture and then process them; and then artificial intelligence (AI) and the algorithms and smart sensors, that make the right decisions at the right time with a level of certainty.”

THE RIGHT DATA However, the sheer amount of data collected—plus the multitude of data points and metrics being measured—make it difficult to determine the correct conclusions. As Stiglitz pointed out with the economy, it is important to ensure the correct data, to our best knowledge, is being measured and that it gives as full a picture as possible of the situation. Is the energy sector measuring the correct data and interpreting it in the right way in order to decarbonise effectively?

“Yes and no,” says Pierre Pinson from the Technical University of Denmark (DTU). “Yes, because this is what it’s about at the end of the day. There are these resources and you want to understand how much of these resources are being used, what are the losses 12

on the way when you convert it. All the metrics we are using today are useful.

“Do they fit what we want to do in terms of changing our way we look at the energy system and do better with decarbonisation or adding more flexibility to integrate renewables? In a way, no, because we need to also rethink metrics so that they are adapted to our new objectives for the way we want the energy system to be operated,” he says.

“What you measure affects what you do. If you don’t measure the right thing, you don’t do the right thing”

“The change of metrics is ongoing. I don’t think the new types of metrics have been set. It might be healthy that in a data-rich environment we might be more flexible or agile in updating our metrics before they were set in stone. Today, people have realised that we have the chance to update metrics much more easily because the world has become much more transparent,” Pinson adds.

The modern energy system will need to consider more data points and look at them in different ways in order to decarbonise to create a fuller picture. “If you look at the energy system in the past it was all about reliability, long-term forecasting, and measuring actual volumes. The new characteristics of a distributed energy resource (DER) system adds some new characteristics to this equation, such as flexibility, peak loads and so on. That’s probably the shift we need to make,” says Mortier.

DATA OWNERSHIP By recording a greater array of metrics and having a higher resolution of information accessed by more people, greater transparency is possible. “You’ll have this data so everything can be accountable. You will be able to write statistics, to re-simulate simulations to see if it’s the right thing to do. You’ll be able to benchmark, and do [bill] settlements,” Pinson says.

But transparency requires an element of data sharing, something the energy market is not renowned for.

In Europe, this is muddled further by the introduction of the General Data Protection Regulation (GDPR) covering data protection since 2018. “In Europe, you cannot avoid the consequences of GDPR. FORESIGHT

METRICS

Different metrics for different users In monitoring building performance, different metrics address the needs of various users

PERFORMANCE METRICS ACTIVITIES

USERS OF PERFORMANCE METRICS

Monitoring procedures Analysis procedures

Policy makers INDICATORS

TIER 1 METRICS

Rating system sponsors Energy suppliers Owners

SOURCE US Department of Energy

Designers Operators Energy professionals Researchers

TIER 2 METRICS

DATA

Energy data falls inside GDPR because it says something about your behaviour when you look at electricity data,” says Bo Nørregaard Jørgensen of the University of Southern Denmark (SDU).

Ownership of the data and who is responsible for collecting consumer data also differs market by market, complicating decision-making and knowledge sharing. “In Denmark it’s the distribution system operator (DSO) that has the metering point and is responsible for collecting the consumption data. And then it forwards this data to a central hub where the retailers can access the metering data for their customers only in order to bill them,” Jørgensen explains.

“In Germany, it’s the retailer who actually knows the energy consumption which they use for billing and the DSO really doesn’t know what happens on FORESIGHT

its grid because it doesn’t have the hourly data. How the electricity market is organised has a huge influence on who owns the data and who has access to it for optimising grid operation and optimising pricing schemes.”

STANDARD BEARER This issue could be partly resolved by increased standardisation of metrics. One of the challenges facing the energy sector is agreeing on the same definition of metrics to ensure everyone is being measured against the same benchmarks. “We have to have a standard,” says SAP’s Beberness.

“If you look at how you, as a company, report your sustainability numbers versus how I report them and we’re not following the same standard, then we’re go13

BLOCKCHAIN Five years ago, technologists excitedly started suggestion how to use blockchain for energy applications and a raft of start-ups followed, sporting distributed ledgers for the power sector.

Today, the word "blockchain" is seldom heard in energy circles. While the hype may have been overblown, work continues instead on a quieter revolution to the one that was promised

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ctober 2017, on a hotel rooftop terrace in Barcelona, Spain. The Cryptofriends Netup industry event is in full swing.

Nobody has a clue where the next keynote speaker has gone and the already relaxed schedule appears to have gone out of the window. The audience, chatting and sampling free refreshments, seems unconcerned. After all, in the world of blockchain, traditional rules do not apply.

Just half a decade ago, blockchain—a digital ledger or records system that is distributed across multiple sites, or nodes, instead of having a single owner— was set to upend the world we live in. Some analysts claimed blockchain could revolutionise everything from finance to democracy. Threading through the crowd at the Cryptofriends Netup event was Lithuanian entrepreneur Nikolaj Martyniuk with a vision for what blockchain could do for energy.

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His company, WePower, wanted to create a digital platform that would cheapen energy by bypassing the complexities of electricity trading, tracking transactions with nimble blockchain technology instead of bulky centralised trading systems. “By employing technology, WePower solves the following energy market insufficiencies: global access to capital for green energy projects and green energy investments and trading as well as speed and transparency,” gushed a white paper from the start-up at the time.

BLOCKCHAIN BOOM Martyniuk was one of many who were thinking about how best to use blockchain in the energy sector. By March 2018, analyst firm GTM Research (now Wood Mackenzie) was tracking 122 energy-related blockchain start-ups, from companies—such as WePower—touting trading platforms to schemes to improve FORESIGHT

Distributed ledger Blockchain and other ledger-type technologies may still help increase the transparency of the energy sector

TEXT Jason Deign ILLUSTRATION Clara Terne

Traditional rules do not apply in this experiment

FORESIGHT

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A provider and a customer agree a transaction

The transaction is combined with other transactions made during the same period to create a data block

The data block is stored in the decentralised global network in a tamper-proof manner and thus verified

The blockchain process

solar energy production or make investment easier.

Energy-related blockchain companies managed to raise $322 million in funding just in the six months up to April 2018, according to GTM Research.

Yet just three years later, blockchain is seldom mentioned in energy circles. Among American utilities at least, beyond using blockchain for energy attribute certificates (page 24), Isaac Maze-Rothstein, a research analyst with Wood Mackenzie Power & Renewables says he has not “heard anyone talk about how [blockchain] has improved any of their core functions”.

There are at least three factors that can explain why enthusiasm for blockchain has chilled in the energy sector. The first is the technology was over-hyped to begin with. The energy blockchain start-ups of 2017 and 2018 were surfing on a wave of interest created by bitcoin and other cryptocurrencies, which made millionaires of a handful of technology-aware investors.

By mid-2018, potential backers were becoming wiser. They knew that not every blockchain scheme was going to become the next bitcoin. “The hype sur18

“I think everyone five years ago assumed that blockchain was the answer, but I don’t think they knew what the question was”

rounding blockchain technology will recede sharply in 2018 as the cost and complexity of implementing blockchain solutions becomes apparent,” GlobalData, a research firm, predicted at the time.

MISSING MARKETS Within the energy sector, many companies were targeting a market that did not really exist. A GTM Research analysis released in March 2018 showed 57% of the money raised by energy blockchain companies at that point was for schemes related to peer-to-peer trading.

FORESIGHT

SOURCE PwC global power & utilities

BLOCKCHAIN

BLOCKCHAIN

The verified block is combined with all other blocks previously verified, thereby creating a continuously growing blockchain

The transaction is confirmed to both parties

This was no doubt an exciting prospect in view of rising levels of distributed energy generation and an experiment in Brooklyn, New York, showed how a blockchain energy trading platform could work in practice. But in most markets worldwide, there was no regulation regarding how you might trade energy with your neighbours. In Europe, regulations allowing peer-to-peer trading are only being ushered in this year.

Plus, even in 2021, the number of consumers who would probably feel moved to trade electricity with each other is vanishingly small. “In the United States, if you live in an apartment or a small house, you’re spending maybe $100 at most a month on your electricity bill,” says Maze-Rothstein. “Who wants to take up part of their brain space about trading that to save five bucks?”

This enthusiasm for small markets suggests some energy blockchain entrepreneurs may have prioritised the capabilities of their technology over the needs of their customers. “I think everyone five years ago assumed that blockchain was the answer, but I FORESIGHT

don’t think they knew what the question was,” says Anthony Boden from Charles River Associates, a global consulting firm.

TECHNOLOGY MISMATCH A second factor working against blockchain in the energy sector is, despite the hype from devotees, early forms of the technology may not have been suited for the applications they were being applied. In the case of energy trading, distributed ledgers were supposed to be ideal because they were said to scale up to handle millions of transactions rapidly and cost effectively.

In practice, though, the blockchain technologies available in 2018 were neither fast nor cost effective.

For a transaction to be validated on a blockchain, it has to be registered on multiple blocks across the distributed ledger. On bitcoin in 2018, this meant registering a transaction on at least six blocks, at an average rate of around ten minutes per block.

At the time, the bitcoin network could only process up to seven transactions per second, which 19

Case study

Blockchain finds a purpose in tracking energy unit origins The breathless furore around blockchain has died down but in some ways the technology is still supporting the energy transition. Carbon-conscious buyers and sellers can use a distributed ledger to track where the electricity they use comes from

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FlexiDAO created a distributed application, called REspring. Energy retailers can use it to enhance the renewably sourced supplies they offer to carbon-conscious customers. It tracks the kilowatts bought and sold in physical or virtual power-purchase agreements, green energy tariffs, community solar trading schemes and electric vehicle charging initiatives.

“Having more accurate, granular requisites over the source of energy can drive up prices, hence fostering investment in new plants,” says FlexiDAO’s Joan Collell. “Blockchain finally allows for that level of granularity.”

REspring has been adopted internationally by large power users looking to enhance their environmental reporting, such as Vodafone or El Corte Ingles, Spain’s leading department store. Energy firms including Iberian majors Acciona Energía, EDP Renewables and Iberdrola are including REspring reporting in their green tariffs and power purchase agreements (PPAs). Each year the platform tracks about five terrawatt-hours of renewables, out of a total of 3269 TWh in 2020.

FlexiDAO is not the only company that has found success in applying blockchain technology to EACs. In France, Engie-owned company The Energy Origin offers a similar service. Meanwhile, Power Ledger, an Australian firm, also provides guarantees of origin as part of a wider suite of blockchain-enabled services focused mostly on energy, grid flexibility and environmental commodities trading. • FORESIGHT

Tracking energy Blockchain is helping consumers understand the carbon intensity of their energy consumption

TEXT Jason Deign

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n 2017, the founders of Spanish startup FlexiDAO spotted a potential niche where blockchain could make a difference. A distributed ledger could solve a growing problem for businesses buying clean energy supplies over the grid—to make sure a specific renewable plant is producing at the exact time you need electricity.

Traditionally, clean power producers and consumers have relied on energy attribute certificates (EACs), also referred to as guarantees of origin or Renewable Energy Certificates, as a way of certifying the source of energy. They are meant to encourage clean energy investment by giving customers a way to pay a premium to renewable energy producers, with the hope that this money will get reinvested in new plants.

When it comes to measuring carbon emissions, however, traditional EACs are imperfect instruments.

They do not take into account the moment in time in which the green energy was consumed or produced and the price of an EAC, at around 1% of an energy bill, is too cheap to drive real investment in new plants.

With businesses facing increasing scrutiny over their commitment to carbon reduction, FlexiDAO realised that a blockchain platform could add an extra layer of transparency to EACs. It allows each unit of energy to be given a smart contract, recorded on the distributed ledger and allocated to a specific customer. It results in accurate measurement of the real carbon footprint of a company’s energy consumption.

BLOCKCHAIN

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DIGITS, DATA & METRICS

Count it in zettabytes* Volume of data/information

2010 2012 2 ZB

26

6.5 ZB

2014

12.5 ZB

2016

2018

18 ZB

33 ZB

FORESIGHT

2020 59 ZB

DIGITS, DATA & METRICS

2022

2024

94 ZB

149 ZB

The digitalisation of our world is seeing the total volume of data grow at a tremendous rate. *1 zettabyte = 1 trillion gigabytes. SOURCE Statista/IDC

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ARTIFICIAL INTELLIGENCE Around 50% of the shift from fossil fuels to renewable form of energy has been a digitised transition to 2020, says Energinet, Denmark's power system operator. As the world digitises further, the already vast volumes of data will only increase in mass. Advances in Artificial Intelligence technology and machine learning tools provide ways of processing this tsunami of data into a new world order

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iven the accelerating electrification of the world and aggresive carbon emission reduction goals, Artificial Intelligence (AI) and machines that learn by doing will help develop next generation power systems running mainly on variable renewable energy, expand the use of electric vehicles (EVs), increase plant-scale storage capacity, and do more with as few new transmission lines as possible.

AI and machine learning are terms that are—inaccurately—used interchangeably. Simply, AI can track vast quantities of data and is taught to detect patterns not easily discernible to humans. Using AI increases the speed and precision of data-hungry programming. Computers make fewer mistakes and do not get tired. Today, AI can often analyse an X-ray better than a real-life technician. Machine learning, meanwhile, is a subset of AI allowing devices to learn from data without being programmed explicitly. Put another way, machine learning is the optimisation of data. For the grid, AI can help with electricity sector

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asset management, control and acquisition, according to Shuli Goodman, executive director of California-based Linux Foundation (LF) Energy, an energy software non-profit organisation.

Kristian Ruby, secretary general of Eurelectric, a lobbying group for European utilities, says society will eventually move “beyond digital” to form an ecosystem of interconnected technologies. For next-generation power systems, decentralised machines and machine learning must be adopted, adds Ruby, supported by vast banks of memory processing using cloud storage and new 5G technology.

But it is still early days for AI’s involvement in managing the grid and generation assets. No utility has enough data, yet, to track how a particular vendor’s transformer is performing, when it needs maintenance or is heading for trouble. Tens of thousands of transformers would need to be tracked with AI to get an accurate assessment. Luke Witmer, of Finland-based Wärtsilä, a power plant and storage provider, says AI is good for forecasting and deciFORESIGHT

Building blocks Management of next-generation power systems will be built on a foundation of ever expanding stores of data

TEXT Ros Davidson ILLUSTRATION Clara Terne PHOTO National Grid

The grid in search of a brain

FORESIGHT

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ARTIFICIAL INTELLIGENCE

smarter, data-driven investments and maintenance decisions, it says. Using this approach, the company will be able to provide better value for customers by increasing system reliability, allowing it to focus instead on investments and maintenance projects.

“With this [pilot] substation and future ones, we expect to gain efficiencies and deliver cost savings for our customers and ensure even greater system reliability and resilience, all while more easily integrating additional renewable energy sources onto the power grid,” says Rudy Wynter, president of National Grid in the US. GE, a US engineering conglomerate, uses a Digital Twin product, an analytic engine for optimising operations at power plants that is boosted with AI. The models can show design limits of a power generation unit when commissioned or they infer the design limit for an existing single plant or array of units by matching the equipment to thousands of other similar pieces of equipment in the database. The model, which improves as it learns, can accurately represent the plant or fleet under many operational variations— fuel mix, ambient temperature, air quality, moisture, load, weather forecast models and market pricing.

The information is especially useful when managing the variable energy output of wind and solar units.

LineVision of Boston, which secured financing from National Grid in April 2021, has developed a non-contact overhead power line sensor that uses AI and cloud-based analytics and lasers to monitor, optimise, and protect energy delivery infrastructure. It gives dynamic line ratings for transmission lines, a real time forecast of their power carrying capacity. This helps utilities to optimise their grid. Grid congestion is an issue that must be tackled if President Joe Biden’s goal of a net-zero grid—with massive deployment of renewables—is to be achieved, notes Hudson Gilmer, CEO at LineVision, pointing to the grid congestion caused by the rapid roll-out of renewables plants.

Gilmer refers to the results of a study by the Brattle Group released in February 2021 for the US-based Watt Coalition, a collective of companies in the energy transmission sector working to add new grid technologies of which LiveVision is a member. It found that three AI-backed technologies—dynamic line rating, advanced power flow control and topology optimisation—could enable Kansas and Oklahoma to integrate 5.5 gigawatts (GW) of wind and solar generation currently in interconnection queues by 2025,

Data boost Dynamic management of loads on electricity lines using AI can often increase their capacity without the need to string up more wires

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ARTIFICIAL INTELLIGENCE

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Case study

South Australian rooftop PV exports face export trial

A

project underway in South Australia and Victoria will trial a flexible connection for solar PV customers using artificial intelligence (AI). The A$4.84 million project will examine a flexible connection option for residential rooftop solar PV customers so that they are not restricted by static export options in congested areas.

The 12-month trial will involve up to 600 participants with rooftop solar installed on their houses across the two states that already have high penetration. The technology being trialled will receive signals from the distribution network and adjust flow export limits from the participants’ panels every five minutes, enabling the distributor to remove a five kilowatt (kW) cap on the power households can sell back to the grid. Two different configurations will be tested: one entailing a retrofit with energy management system device from SwitchDin, an Australian technology company, paired with a compatible inverter. The other configuration will use built-in integration within inverters purchased by participants.

Project manager Bryn Williams, from SA Power Networks, says without the new process new households adding solar panels might be stopped from exporting to the grid. “The level of solar on the grid in

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South Australia is increasing daily. The trial will target some areas that are particularly congested, where we might soon have to consider imposing zero-export limits on new installations, as is happening already in other states like Victoria,” says Williams.

This inability to export surplus electricity back to the grid risks creating an inequitable system, where early adopters essentially max out the available grid capacity. This would lead to limitations on later adopters and a reduction of the economic benefits from installing rooftop PV. It also risks passing on the cost to upgrade the network to all customers irrespective of whether the household has solar PV installed. The trial will target new customers wishing to connect in areas where the grid is already at capacity and otherwise be facing a zero or near-zero static export limit.

It will seek to quantify the value a flexible export capacity can bring these customers.

The field trial phase is set to begin in mid-2021. If successful, Williams says SA Power Networks plans to offer all new residential solar PV customers a flexible connection option “as standard” from late 2022. It also has the ability to be rolled out nationally if successful and distributors are working to establish technical standards to this end. In turn, this could potentially FORESIGHT

TEXT Katie Kouchakji PHOTO Ross Jones

As renewable energy, particularly rooftop solar, continues to be rapidly adopted across Australia, power system operators are having to find new ways of managing electricity generation and supply as the level of complexity increases. Digital solutions are coming into their own

ARTIFICIAL INTELLIGENCE

“The inability to export surplus electricity back to the grid risks creating an inequitable system”

FORESIGHT

double the amount of renewable energy the network can accommodate over the next five years.

“This capability to provide flexible export limits or ‘dynamic operating envelopes’ is fundamental to integrating high levels of [distributed energy resources] with the network,” Williams adds. “We’ve proved the concept through our ongoing trial with Tesla’s South Australian virtual power plant (VPP), and the upcoming trial is about extending that to passive solar PV.” The A$64.17 million Tesla trial built a network of up to 50,000 solar installations and the US storage company’s Powerwall home battery systems to create the world’s largest virtual power plant. The project uses AI to optimise power supply and predict demand peaks to provide stability to the grid. • 37

Case study

Turbocharge the process using digital tools

T

he UK’s National Grid Electricity Systems Operator (ESO) launched its Dynamic Containment frequency response service on September 30, 2020. The service is the first of a suite of digital services being introduced by the ESO to speed up the grid’s resilience to disturbances caused by faults such as the loss of a generator.

The rise of renewables is displacing thermal generation and the inherent inertia its heavy spinning turbines, synced with the grid's frequency, contribute to power system stability. As a result, additional means of containing rapid changes in frequency during system imbalances are needed. Dynamic containment in real time is the answer, made possible by artificial intelligence technology.

Deviations in system frequency can take just seconds to travel the full length of the network. Imbalances need to be managed extremely rapidly—dynamic containment can achieve this in under one second. Digitalisation supports how the ESO procures dynamic containment, explains Colm Murphy, electricity market change delivery manager at the ESO. “In the past, we secured frequency response at quite long procurement horizons—one or six months ahead. It was a fairly manual process, with bidders filling in prices and availability on a spreadsheet, sending it by email to someone who would assess the 38

tenders and work out who won,” he says. In contrast, dynamic containment is procured through day-ahead auctions seven days a week every 24 hour period from 23:00, giving operators of demand-side response assets such as batteries much more certainty in how their assets will be used and what prices they should propose, based on conditions closer to real time.

An algorithm rapidly optimises the markets based on what the ESO needs and the price it is willing to pay, while providers submit the price they are willing to sell dynamic containment for, which speeds up the process of procuring dynamic containment, Murphy says. “We’ve taken the process and turbocharged it using digital tools to create auction platforms and algorithms that result in a really user-friendly, easy way to submit bids,” he adds.

The service's agreements with generators require them to be available and respond when needed. Any technology can take part, but the speed and flexibility with which batteries can store and release power makes them well-suited to the task and the ESO expects them to make up the majority of providers in the early stages. The first round of tenders in September 2020 saw two battery energy storage units accepted to provide 90 megawatts (MW) of fast response services over 24 hours—with six units and 165 MW available to compete in the next day ahead tender.

FORESIGHT

TEXT Catherine Early PHOTO Shane Rounce & National grid

A new market service rolled out by the UK's electricity grid operator in autumn 2020 invites fast-response injections of power or withdrawals of load from generators, electricity storage owners and consumers to help it contain frequency deviations that would otherwise destabilise the power system

ARTIFICIAL INTELLIGENCE

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MICROGRIDS As technology costs come down and microgrids become increasingly “smart” using more advanced digital tools, their role in integrating distributed energy resources is set to expand.

By providing flexibility to the local distribution system and deferring the need for expensive transmission upgrades, microgrids are facilitating the electrification and decarbonisation of the energy networks

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orrego Springs lies at the extreme west of the Sonoran Desert about 140 kilometres from San Diego in southern California. It is subject to scorching heat and monsoon weather conditions. For decades, the town of about 2800 people relied on a single 95 kilometre transmission line and distribution circuit and frequently suffered from power outages. In 2013, San Diego Gas & Electric (SDG&E), a major state utility, launched a microgrid system, backed by digital tools.

The microgrid in Borrego Springs is connected to a 26 megawatt (MW) solar photovoltaic (PV) facility and includes two battery storage systems, a microgrid controller, two diesel generators as backup and an ultracapacitor—capable of quickly storing and discharging electricity to keep power flowing during emergencies and planned outages on the larger grid.

It was the first utility-owned community microgrid project in North America.

The United States’ Department of Energy (DoE) defines a microgrid as, “A group of interconnected

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loads and distributed energy resources (DER) within clearly defined electrical boundaries that act as a single controllable entity with respect to the grid and that can connect or disconnect from the [main] grid... to enable it to operate in both grid connected or island mode.” A remote microgrid is a variation of a microgrid that operates in islanded conditions.

The rise of intelligent digital network products, and cheaper renewable energy, microgrids offer a way of bolstering the resilience of power systems in areas with fragile grids or critical infrastructure where a reliable power supply must be a priority.

RESILIENT SYSTEMS Last year SDG&E received a $4.5 million grant from the DoE to buy smart power inverters, microgrid controls and state-of-the-art energy management systems it says will enable it to improve energy reliability, stabilise the microgrid and become 100% renewable.

In April 2021, the utility announced Borrego Springs would be the site of one of two green hydroFORESIGHT

Remote living A microgrid can function as a local supply network for a defined urban area or for a remote community with weak or nonexistent links to a transmission grid

TEXT Heather O'Brian PHOTO Scott Curtis-Ells

The rise of microgrids

MICROGRIDS

Case study

Sound business case needed for viable microgrids

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n the summer of 2020, Siemens, a German engineering conglomerate, installed a microgrid power system at its corporate headquarters campus in Vienna, Austria. It features solar generation, electric vehicle (EV) charging stations, battery storage and a smart microgrid controller that coordinates connected assets and optimises the power supply to account for peak loads and grid capacity utilisation.

The microgrid plan was conceived when, like many other corporations, Siemens began pushing the use of EVs by its employees and needed a vehicle charging infrastructure. “SRE (Siemens Real Estate), our internal real estate provider, came to us and asked if it was good enough to put some PV on rooftops,” says Robert Tesch, head of digital grid and distribution systems at Siemens Austria and Central and Eastern Europe. “But it wasn't good enough.”

The additional power needs from EV charging meant the company risked exceeding grid access limits exposing them to higher tariffs, he notes. “Every micro-

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grid needs a business case and our business case was peak shaving.”

The microgrid consists of rooftop solar panels stretching over 1600 square meters and with a capacity of 320 kilowatts-peak (kWp), 500 kilowatt-hours (kWh) in battery storage and some 50 charging stations. The microgrid also incorporates a building management system, which provides another source of flexibility via the water boiler in the company’s kitchen. The boiler can be heated either through the district heating system or with electricity, depending on solar production, power consumption and storage needs.

Aside from saving Siemens money on its energy bills, the project illustrates how smart energy management systems can lower emissions by reducing energy waste and avoid the need for additional grid capacity for the uptake of more renewable energy generation. Siemens estimates power from the solar PV panels at the Vienna microgrid will avoid some 100 tonnes of CO2 emissions every year.

FORESIGHT

TEXT Heather O'Brian PHOTO Siemens AG

Technologically, microgrids are relatively simple to establish. It is the business case that is complex and can make or break a project

MICROGRIDS

The benefits of a microgrid Microgrids can provide a secure and reliable supply of clean electricity

Sustainably effective

Microgrids can help ensure an around-the-clock provision of electricity and are able to balance shifting load demands

Microgrids can maximise the efficient utilisation of renewable via local storage and flexible management. This can reduce the CO2 output

Cost-effective

Independently local

Operators can optimise energy consumption on the basis of demand, energy prices and other factors with intelligent software. This especially applies to commercial and industrial users, and business parks

Microgrids can help take pressure off electrical networks and reduce grid expansion costs by consuming locally generated energy

SOURCE Siemens AG

Reliably flexible

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MICROGRIDS

“Every microgrid needs a business case and our business case was peak shaving”

The centrepiece of this microgrid—and of all microgrid systems—is the controller. It collects a lengthy list of information from the microgrid ranging from power consumption to the temperature of the water boiler and the charging state of the stationary battery and and EV batteries. It also has forecasting capabilities, both for expected solar production and for charging requirements, and puts all available infor50

mation together to optimise electricity use. There are plans to integrate a Siemens Internet-of-Things (IoT) application into the microgrid, adding extra intelligence to microgrid applications, says Tesch.

Siemens also aims to provide flexibility services to the balancing market of Austria’s electricity transmission system operator via an aggregator, helping to provide stability to the grid and further strengthening the feasibility for the microgrid. While the business case for microgrids depends on many factors, among them grid tariffs and regulatory regimes, Tesch expects the technology used to optimise energy use at the Siemens Vienna headquarters to also have applications beyond the campus and company settings, including in some of the energy community projects that are developing in towns and cities in Austria and throughout Europe in the wake of the European Union’s December 2018 revised renewable energy directive. • FORESIGHT

Roof space Siemens utilises rooftop solar PV as part of its microgrid system in Vienna

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MICROGRIDS

Case study

Local energy auction trials made possible by digitalisation

TEXT Catherine Early PHOTO Hannah Woolley

The Cornwall Local Energy Market in the UK trialled algorithms to optimise auctions of power increase or load reduction offers while allowing and allow simultaneous purchases of flexibility by different levels of grid operation

MICROGRIDS

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he secret of systems that are user-friendly and simple is they are often the result of complex mathematical calculations. This is particularly true of the trials for a Local Energy Market (LEM) in southwest England, which sought to prove that decentralised renewables generation assets within the region could provide the grid with sufficient flexibility to self-balance the bigger swings in demand and supply that accompany a shift to localised clean power.

Cornwall is one of the sunniest and windiest regions in the UK with surging levels of renewable energy generation. But it also faces severe grid congestion. The three-year £16.7 million pilot scheme tested the role of flexible demand, generation and storage through a digital trading platform. It allowed network operators to pay energy producers and consumers to either ramp up generation or reduce load in a competitive but coordinated process.

Participants included households and businesses, who volunteered to take part in the trials, receiving free equipment in return. While businesses participated in the auctions themselves, residential players were managed by an aggregator, Kiwi Power, a UKbased energy technology company, which formed a virtual power plant from more than 600 kilowatt-hours (kWh) of battery storage capacity.

The aggregated capacity could then trade autonomously with the National Grid Electricity System Operator (ESO) and Western Power Grid, the distribution network operator (DNO). The platform ran closed-gate auctions, where both the buyers and sellers submitted the quantity and availability of their flexibility capacity. Once the market closed, an algorithm matched the orders in terms of price compatibility, while also considering the capabilities of the technologies involved and the grid.

“You need to ensure that the actions taken on the market will not blow up the transformer. We can ensure that through market clearing because we input these types of constraints into the system,” explains Adrien Rosen, from N-SIDE, a Belgian software company with expertise in advanced analytics, which provided the basis of the Cornwall LEM digital platform.

The algorithm takes into account the limits of the renewable or storage technologies, for instance a battery cannot be asked to discharge twice without sufficient time in between to recharge, Rosen says.

Techniques such as these enabled the LEM platform 53

CHEAPER, CLEANER AND MORE RELIABLE

TEXT Jason Deign PHOTO Jason Andrew

Emerging markets gain from the digital evolution of energy

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BUSINESS

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ub-Saharan Africa exemplifies the challenges facing the energy business in many emerging markets. The vast sub-continent has little in the way of infrastructure—less than half the population has access to electricity—but a pressing need to provide basic services to a growing population. It has also been hard hit by the Covid-19 pandemic with economic activity expected to have dropped 3.3% in 2020. The need for services has sparked rapid invention and innovation.

Digital projects and technology start-ups are tackling the energy transition and battling the devastating effects of climate change.

Aptech Africa specialises in providing solar systems to power water pumps in rural areas, which otherwise use dirty and expensive diesel generators. The company not only provides a clean power source but also uses an innovative business model. It began operations in South Sudan in 2011 and now has a presence in more than half a dozen sub-Saharan markets.

When it first launched, Aptech asked for a 30% down payment before installing its solar-powered pumps— but this was a significant amount of money for some communities. As a result, Aptech developed a payas-you-go business model using mobile payments.

“Instead of paying for the system, people just pay for the water on a per-litre basis,” says Aptech’s Laura Corcoran.

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Pay-as-you-go, or energy-as-a-service, business models are gaining in popularity in emerging markets because companies and individuals rarely have access to the kind of capital required for the upfront purchase of generation technologies such as solar photovoltaic (PV) systems. Now, a growing number of mini-grids and renewable energy systems are being installed across Africa by developers that remain the owners of the system and sell electricity to customers on a utility basis.

However, these customers are not adopting renewable energy merely for environmental reasons.

“For many of those people, who are just trying to secure their livelihoods and their energy supplies, climate is not at the front of their mind. But the really interesting thing is that most purely business-driven decisions these days are actually very climate friendly,” says Svet Bajlekov, co-founder and chief executive of AMMP Technologies, a company that provides remote monitoring services for developers that sell clean energy to African businesses.

“We participate in the hybridisation of diesel with PV, moving away from diesel, [but] people are not do-

Fertile land Emerging markets in sub-Saharan Africa and southeast Asia can be hubs for innovation thanks to digital tools with prices low enough to make them accessible

FORESIGHT

TEXT Jason Deign PHOTO Jason Andrew

Technology start-ups in Sub-Saharan Africa are making use of the rapid roll-out of mobile phone networks across the continent to bring digital innovation to remote areas through pay-as-you-go models for services that can directly increase prosperity. Smallholders can for the first time afford solar panels for electricity while others can sign on to thriving energy-as-a-service business models that do not require an initial capital outlay

BUSINESS

from the Centre for Climate Finance and Investment

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