By Joel Hagan
Water utilities around the world face huge challenges. Population growth, urbanization and more frequent extreme weather events make delivering even adequate customer service through aging infrastructure extremely difficult.
Analysis from the University of Washington suggests that the number of people on the planet will reach 11 billion in 2100. By 2030, 53 U.S. cities are expected to have populations of more than a million people, up from just 41 in 2010.
The frequency of extreme weather events is also on the rise. The United States has experienced 30 occurrences of billion-dollar weather disasters in the last two years alone, according to the National Centers for Environmental Information. Such events now happen at a rate that is more than double the long-term average. Such frequency places ever greater strain on finite water resources.
The vast contrasts between U.S. states only exacerbates the situation: from persistent droughts in Texas and California, to the recent devastation caused by the spate of hurricanes in Florida. Given the extent of these challenges, as well as mounting regulatory requirements and often a shortage of capital to invest, U.S. water utilities need be innovative and adaptable in what they do.
The adoption of smart water networks is already helping water utilities located outside the United States improve customer service and – critically – extend the lifespan of their existing assets, allowing them to delay some of the significant investment required in new supply infrastructure and pipe replacement.
Evolutionary Road Toward Smarter Water Networks
Smart networks are a natural progression for the water industry, and a logical step forward for an industry that has already, on the whole, made the shift from analog to digital.
Historically, water networks were measured and managed using analog technologies such as listening sticks and pressure gauges. These provided useful insight, but these findings needed to be laboriously recorded and reported by hand.
Calculations, to design a network or diagnose an issue, were then performed on paper and any resulting installation or operation performed manually. Maintenance was typically performed on the basis of failure.
This manual approach has largely been replaced by digital technologies that have improved the accuracy and efficiency of gathering data. Water utilities adopted digital sensors that could be moved around the distribution network to collect and store data. This would then be downloaded to a local device plugged in by hand and delivered, in person or – more recently – over the internet, to a central point for analysis.
Calculations based on this data could be performed by computers, bringing a higher level of reliability, accuracy and processing power to the process. Even with the addition of these digital technologies, however, this analysis still tends to be performed on an occasional basis only, and any resulting actions performed manually. More often than not, maintenance is still scheduled based on time or once a failure has occurred.
The shift from analogue networks to digital was a step forward for the water industry, although the advantages seem small when compared to what is being achieved by the transition from digital to smart networks.
Benefits & Challenges of Truly Smart Water Networks
From i2O’s point of view, smart water networks have three essential components: sensors, analytics and automation. This approach is familiar to most water utilities, since it is similar to their use of Programmable Logic Controllers (PLCs) and SCADA systems to manage water treatment plants.
This approach can now be replicated across distribution networks because of advances in technology. Mobile communications are pretty much ubiquitous; data processing and storage is more cost-effective, secure and reliable and scalable than ever before; and network assets can be controlled much more precisely through automation.
Each of these components has its own particular characteristics, benefits and challenges. Together, they are revolutionizing water networks.
Sensors enable accurate status readings to be gathered reliably and relayed to a central point on a regular basis without anyone needing to collect them in person. This can be done today with pressure and flow, and it is likely this will extend to water quality parameters such as turbidity and chlorine levels in the not too distant future.
These sensors are located in harsh, remote environments, required to operate in extreme temperatures and can be submerged in water of all qualities. They need to communicate through concrete chambers and from under heavy manhole covers. As few network locations have accessible mains power, they need to function on low power and have batteries that last a long time.
Once gathered, analytics crunch the data, combining it with diverse datasets and applying a range of algorithms to provide actionable insight that can be used to improve network management. When provided with accurate, reliably and timely data, analytics can crunch through it continuously without bias or error – something that people simply cannot do.
A further advantage of analytics, is the ability to move away from traditional time-based maintenance to scheduling network interventions based on asset condition. It is now possible to infer the condition of network assets such as pressure reducing valves by analyzing pressure data, reducing maintenance costs and eliminating the potential risks that can arise from opening up the network unnecessarily.
The final element of a truly smart network, automation, enables the network to be controlled remotely, without human intervention. Automation allows network pressure to be continuously and autonomously optimized, ensuring supply matches demand, and reducing the strain created by excess pressure that ages the network prematurely and accelerates leakage and bursts. On average, water utilities that adopt automation cut leakage and energy use by 20 percent and reduce burst frequency and operational costs by 40 percent.
The challenge of automation is two-fold. Hardware designed for manual control needs to be adapted in order to be remotely actuated, however, the most significant challenge tends to be more human. It can be difficult for some people to accept that machines can now do a lot of what they’ve spent their careers doing, and in most cases, much more reliably.
We’ve found that the younger generation of engineers is more open to embracing new ways of working and learning how to work with these new technologies to maximize the impact of smart networks.
Processing Power
Some water utilities have expressed concerns around the volumes of data that investing in smart networks will require them to process and store, particularly with the addition of smart meter data from every customer endpoint.
While this represents a big increase in data for water utilities, it is relatively manageable when compared to the levels produced by other large consumer facing organizations.
Smart networks aren’t entirely new, as the energy industry has been using them for more than a decade, and they are a well-trodden path in the telecommunications and financial services sectors, too. Around the world, they are now being adopted as an answer to the major challenges facing the water industry.
The significant challenges facing U.S. water utilities generated by population growth, urbanization, aging infrastructure and more extreme weather events aren’t going away. The water sector isn’t the first to undertake the journey from analog to smart, but it could benefit the most.
Joel Hagan is CEO of i2O. He has more than 20 years of business leadership and technology expertise. As founder and former chief executive of ONZO, a venture-backed start-up providing energy data analytics, he has a deep understanding of the utilities sector and significant experience of building early stage companies and developing data analytics and control technologies.
