From raw wastewater to sludge and “cake,” across clarifiers and aeration tanks to digesters and dewatering machines, there’s a lot to manage at a wastewater treatment plant. The processes used to treat influent depend on wastewater characteristics, treatment targets, and each plant’s purposes. Balancing priorities and costs at municipal treatment facilities is challenging, and complexity increases further when working with industrial wastewater.
At traditional plants where primary, secondary, and sometimes tertiary treatment are required, facilities tend to have large physical footprints. Modern plants have adopted advanced membrane separation and high-rate reactor technologies, significantly reducing the footprint and making improvements upon the treatment principles employed at traditional facilities. However, they require more advanced control strategies and sensor data, which then need to have an integrated system to be managed effectively.
Due to the diversity and complexity of wastewater treatment processes, existing process control systems that are based on traditional control algorithms have created a bottleneck when it comes to increasing treatment efficiencies and reducing operational consumptions and costs at both traditional and more technologically advanced wastewater facilities.
The job of each wastewater plant’s operational team is to maintain equipment and ensure that treatment meets compliance requirements so that effluent can be safely discharged back into the environment. Some facilities are built to reuse water, adding more processing and even more stringent regulations into the mix. Maximizing stable biogas production is becoming an increasingly important metric in sludge treatment and greenhouse gas (GHG) management at wastewater facilities as well. Because of the energy-intensiveness of secondary treatment and increasingly strict discharge limits, two trends are emerging in the wastewater treatment industry: self-sufficiency when it comes to energy use and moving towards zero discharge at facilities.
The Challenge of Maintaining Wastewater Compliance
Regardless of whether a plant is using traditional or more modern wastewater treatment technology, priorities for operational teams are similar, as are key performance indicators to keep on top of. The biggest issue for most operations is compliance, making sure that effluent does not exceed limits before being discharged back into the environment. This is a priority to both avoid hefty fines for exceedances, as well as to be good stewards of the environment by keeping local watersheds safe and healthy.
Metrics like total suspended solids (TSS), biological oxygen demand (BOD) and chemical oxygen demand (COD), ammonia, and phosphorous levels must be monitored and adjusted at both industrial and municipal wastewater facilities. As influent quality and quantity varies due to storms, heavy industrial processes, and the limited lifecycle of equipment, the quality of effluent can widely vary as well. Operators must monitor flow rate and pollutant load and adjust the system, as needed, but this becomes a challenge when lab sample results aren’t timely enough to allow for proactive decision-making.
Sensors that are connected to SCADA and PLC systems are helpful, although data quality can be an issue, especially if manual data capture is involved and readings are delayed, scattered, or inconsistently entered into the system. When urgent issues arise and teams find themselves in operational firefighting mode, accurate data capture can be disrupted, potentially affecting performance levels further. At most plants, SCADA, PLC, and DCS frameworks are not designed to process all of the “big data” that’s generated from every aspect of the treatment process. As a result, valuable information behind operational data is not revealed for process studies and improvement to operations is identified and implemented at a slow pace, if at all.
Site supervisors usually aim to make decisions based on the latest information, but if the latest information is incomplete or outdated already, it’s difficult to feel confident that they are considering all relevant factors before determining which action should be taken, and when.
These days, increasingly strict effluent discharge standards are stimulating the development of new process solutions and equipment. Yet, these innovations are not always ready to be adopted by a market that needs fast and accurate process control approaches to be available at scale. Ready-to-use solutions that can work with existing systems, while also improving current processes, are what's needed to really make a difference for wastewater treatment facilities and their operational teams.
The Opportunity for Biogas Production and Wastewater Reuse
Biogas produced during anaerobic digestion provides an opportunity to reduce energy consumption at a plant, which can enable the creation of a circular model of energy generation to reduce reliance on external sources. Establishing a stable supply is one way to work towards sustainability.
Another step towards more sustainable and resilient wastewater facilities comes from recycling wastewater for reuse, either for irrigation and other industrial purposes, or as the resource for potable consumption after rigorous additional treatment. Reuse usually requires additional processing after tertiary treatment and involves membrane filtration processes to produce water that’s at a quality safe enough for human consumption. This practice is also becoming more significant to address water stress and scarcity, with a focus on increasing reuse as demand for water continues to rise alongside a growing population.
Both of these opportunities have the potential to generate significant savings in wastewater treatment processes and water reuse, but require consistent, predictive intelligence about overall plant performance to do so. With sustainable practices climbing up the priority list, facilities and operational teams need to have effective tools in place to make the most out of their resources.
Innovating Wastewater Treatment Processes Using Artificial Intelligence
Energy savings and effluent quality have been part of the conversation at wastewater treatment plants for decades, but true optimization has been slow due to a gap in hardware versus software advancements. While pumps, blowers, and other process equipment have gotten more efficient over the years, the tools needed to monitor these assets, as well as to collect and process big data from sensors around the plant, have been historically limited.
Water reuse, energy consumption control, management of GHG emissions, biosolids hazard management, and zero discharge are factors that current and future facilities will need to have an accurate understanding of. This understanding can come easily when the right tools are leveraged, with facilities today being able to adopt advanced data-driven process modelling technologies that are integrated with existing process operations and controls to optimize their operations.
Through cloud computing and digital technology advances in artificial intelligence (AI) and machine learning (ML), the opportune moment for wastewater to innovate using AI is finally here. While accurate data access can be a challenge, especially at plants where data gathering is dependent on manual readings taken on physical logbooks and analyses done through compiling spreadsheets, online software solutions will deliver savings in staff time, power and chemical consumption, and overall operational expenditure, while making it easier for teams to stay on top of water quality and regulatory compliance.
Water quality sensors can be helpful, though they often require regular maintenance. Failing sensors can cause unstable readings and lead to misleading information, which then needs to be verified or troubleshot. Digital technology can make up for that through creating a digital twin and running simulations with AI. By establishing baseline performance metrics through digitized or digitalized monitoring of the plant and allowing algorithms and models to adjust parameters and recommend more efficient setpoints, tools like the Pani platform support operational teams in managing this expanding workload by monitoring sensors and detecting when readings are drifting out of calibration. The platform can also provide actionable recommendations to operators on how to resolve issues when they are detected to get things back in order quickly.
A Holistic, Real-Time View of Plant Performance
Having a digital layer of process operations allows operators, supervisors, and site managers to all take a holistic look at the plant to balance competing priorities, at the same time. Knowledge sharing and transfer become simplified using one platform as a single source of truth. Anomalies are also detected faster, variable influent can be monitored in real time to proactively adjust the system and stay within compliance, and optimization opportunities for both energy and chemical consumption helps cut down on costs. For facilities that want to maintain or increase biogas generation or wastewater reuse, production capacity can be tracked and optimized as well.
Digital technology can provide a simpler way for operational teams to conduct troubleshooting of issues and rapidly process the vast amounts of information necessary to run operations. AI- and ML-enabled technologies have been designed, engineered, and purpose-built to compute countless data points in order to deliver accurate diagnostics and performance audits at lightning speed. Even when taking the diversity, complexity, and varying hardware and software setups of different wastewater treatment facilities into account, these tools can custom scale and are invaluable at every plant.
An additional benefit of adopting AI technology at both municipal and industrial wastewater facilities is the ability to identify valuable or necessary upgrades to infrastructure. Having an accurate understanding of asset health can help identify the right time and type of cleaning a membrane needs, how long a cleaning can be delayed until its status becomes critical, and best practices for cleaning to get better results that extend membrane life. By optimizing cleanings to be the most efficient they can be, chemical costs can also be reduced, with plants saving thousands of dollars on early or avoidable replacements of equipment. Instrumentation may also need upgrading, and AI can identify failing or unstable sensors to alert operators before they lead to compliance exceedances.
Compared to equipment and infrastructure upgrades, adopting AI to support operational decision-making is a relatively inexpensive investment that can lead to improved processing and production performance using existing assets and setups. This solution helps teams automate the collection, tracking, and analysis of key metrics so that operators can save time on manual data gathering and processing. Through specific, timely recommendations and forecasting, teams can prioritize actions to reduce risks at their facility, while saving on costs for energy use and consumables.
The Pani platform has been developed specifically as a decision-making support tool that is designed and configured for water and wastewater treatment plant operations. It offers a robust framework to support facilities in maintaining compliance, enabling stable biogas production and water reuse levels, and assessing and addressing potential issues, as well as infrastructure upgrades that can help compound the platform’s benefits. By adopting Pani, teams can bring their facility into a state-of-the-art workflow that features optimized processes, equipment, and plant performance, making their operations more resilient and sustainable.
Curious about what Pani’s process operations AI can do at your wastewater treatment plant?
Reach out to get started today.