revenue protection
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David Green, senior research manager for Smart Buildings & Energy Infrastructure at Omdia, explores three broad categories for revenue protection measures.

If increased energy efficiency is key in ensuring future energy demand won’t outstrip supply, then revenue protection is the only way utilities can survive the change.

This article was originally published in Smart Energy International Issue 3-2020. Read the full digimag  or subscribe to receive a print copy here.

By 2040, global energy demand could have risen by a third, according to BP’s 2019 ‘Evolving Transition’ scenario. In a word, there is no single solution to ‘solve’ the issue. Rising adoption of renewable generation reduces utilities’ generation deficit and their revenue, but sustained action is also needed to reduce average residential and industrial consumption.

But in which other industry does a company need to help reduce its own top-level revenue? With the potential exception of big tobacco, utilities face a unique challenge in their business model.

Lower demand can be beneficial if the utility can’t meet the current demand and can, therefore, reduce/delay the necessary investments in grid upgrades. Additionally, utilities can use big data generated by this growing ‘Internet of Energy’ to analyse and find operational efficiencies. This is often without the need for further hardware investment.

However, logic also says reduced energy consumption means less revenue for utilities, which disincentivises many of the initiatives.

So, if utilities want to avoid the ‘death spiral’ they need technology’s help – and revenue protection becomes the aim of the game. If top-level revenue falls, you want to charge for every percentage of electricity supplied you possibly can.

Vendor applications are numerous and typically far more advanced than the average utility is ready to adopt. Of those, Omdia notes three broad categories for revenue protection measures: hardware-driven solutions, data-driven savings, and data-driven opportunities.

The basic step of hardware-driven solutions

Utilities may be a slow-moving bunch, but technology adoption happens at scale. In 2019, over 173 million new communicating meters shipped worldwide (electricity, gas and water) according to Omdia data. With the global installed base rapidly approaching one billion meters, there’s a clear ROI to utilities beyond simply satisfying legislation.

While AMI solutions undoubtedly bring cost/ operational efficiencies through improved meter-to-cash processes, a key driver for many is reducing non-technical losses too.

Globally, non-technical losses cost utilities between $90-100 billion per year. There are several causes, including: billing inaccuracies, misallocation, conveyance errors, and energy theft. Utilities can create robust and efficient billing automation systems through AMI, reducing the need for consumers, or manual labour, to relay energy usage back. Many European countries have already shifted to AMI and have meter readings every 15-30 minutes, thus creating a reliable data stream for improved billing.

However, reducing billing inaccuracies isn’t enough: energy theft is one of the single leading causes of non-technical losses. In India, an estimated $16 billion in revenue is lost to theft every year. Smart meters therefore need not only connection but smart design and the addition of data analytics. This means evaluating numerous tampering methods to highlight weakness, including more sensors, and using higher quality durable materials.

Improved analytics through regular readings allow for better understanding of consumer behaviour. For example, sudden unexplained changes in energy usage patterns can be identified and resolved faster than ever before.

Therefore no wonder theft reduction is a key driver for the 10 million smart electricity meters Omdia forecasts to ship in India by 2025.

But what of hardware-driven solutions in the ‘developed’ AMI markets such as the United States? Remote shutoff/disconnect is the growing application of choice for some utilities.

GLOBAL ANNUAL NONTECHNICAL LOSSES FOR UTILITIES VARY BETWEEN $90100 BILLION.

Once AMI foundations are in place, remote disconnect is often the final step to completing the meter-to-cash business case.

It’s not difficult to implement with the right hardware and offers benefits in terms of revenue and safety.

Anywhere from 5 to 15% (greater for college towns) of endpoints are typically classed as areas of high turnover – meaning water, electricity, or gas needs to be shut off because there are gaps in residency, or households aren’t paying their utility bills.

In fact, some meter vendors now plan to exclusively offer remote shutoff functionality in static meters, to help boost the adoption of these new devices (such is the popularity of the feature).

There’s still potential in hardware-driven solutions even as the installed base nears one billion smart meters, but for some utilities the game has already moved on.

Data-driven savings: the rise of software and analytics

Every industry faces the transition from hardware, to connectivity, through to solutions – utilities being no different.

Recent trade shows highlight the shift in conversation; where DISTRIBUTECH or European Utility Week [now Enlit, see page 7] are definitively becoming solutions/software shows with added hardware – not the other way round.

Shifts in connectivity are still happening; for example ‘Advanced Cellular” technologies will rise from 1% of new smart meter shipments in 2018 to 14%. However, that doesn’t dramatically increase total revenue spend on new AMI solutions; that comes from software and services being added to create new value. In fact, around 40% of head-end software for communicating electricity meters in North America is already hosted off premise, with the utility paying for ‘software as a service’.

Increasingly, the utility returns to the vendor after the initial deployment is complete, to layer on further analytics packages and maximise the value of the data.

This is clear for both vendors and utilities.

Omdia recently claimed vendors need to make 15%+ of their annual revenue from software and services, including managed services, within the next five years – those who don’t will lose share even in hardware markets.

In revenue protection, the clearest use case for utilities lies in outage management. In general, outage minutes cost utilities twice: there are penalties (fines) for interruptions in service, and they also lose the revenue they would have generated during that time.

Many applications exist geared towards outage management, but the most common tend to be reactive – such as workforce deployment and optimization (avoiding truck rolls). However, utilities are looking to add more predictive functionality; for instance integrating weather data to understand grid impacts around weather ‘events’.

Whilst a ‘true’ OMS might still be within the domain of DMS/ADMS, the role of dedicated analytics packages or add-on modules is rising.

One example is outage management analytics using meter data to strip temporary outages from the data before feeding into the real OMS – meaning workforces are directed straight to priority cases. It’s bringing tangible operational efficiency and revenue protection, and it’s gaining market traction.

Data-driven opportunities: the intangible need for the future

The ‘final’ step in revenue protection measures looks further into the future and focuses on engaging the consumer – a preferred choice to the ultimate alternative of ‘losing’ them off-grid.

Customer-facing applications are the next step, such as load disaggregation. These applications break down home energy usage into categories, effectively creating an ‘itemized’ energy bill for the consumer (e.g.

15% washer/dryer, etc.). This works by analysing historical MDM data, running algorithms to create ‘signatures’, processing real time meter data through those signatures, then displaying the outputs on a utility consumer engagement portal. Most real-world projects are connected to cities/utilities with demand response initiatives, and utilities typically find funding from efficiency mandates/initiatives (federally or locally). Grid-side management then becomes the next logical step, to help reduce the operational costs to utilities too.

It’s hard or even impossible for utilities to quantify the exact ROI for these applications in the short or medium term. However, the fact remains that they must consider consumer engagement, educating their consumers and changing behaviour. The real question is: ‘What will it cost if I don’t invest in revenue protection?’

Where next for revenue protection?

Every utility is somewhere along thetechnology adoption curve – moving from hardware to solutions, and from basic revenue protection measures to more advanced.

Where action used to be limited to the most ‘threatened’ (i.e. those with limited supply, or with the quickest adoption of PV/energy storage solutions), a 33%+ rise in global energy demand by 2040 would clearly require action from every utility.

The supply side of the technology market is largely ready – with solutions from hardware, connectivity, software, and analytics already available. The bigger challenge is now fixing the demand from utilities, before their business model becomes broken beyond repair.

About David Green

David is a senior research manager for Smart Buildings & Energy Infrastructure at Omdia..

Omdia is a leading technology research provider that combines the acquired IHS Markit technology research portfolio with Ovum, Heavy Reading and Tractica.

David is currently responsible for leading a team of analysts focused on our building technologies areas such as access control, intruder alarm, fire suppression, smart building and smart lighting.

He also leads our smart utilities intelligence services, research on key technology trends and consumer analysis for smart metering and AMI related software/services, as well as speaking at events such as European Utility Week [now Enlit, see cover story] and DISTRIBUTECH.

David holds a Bachelor’s degree in Mechanical Engineering from Cardiff University and is based in the company’s Wellingborough, UK office.