How the Water & Wastewater Industry Can Reduce Energy Consumption
(Hint!) It Involves Advanced Industrial Analytics Tooling
Water is life. We cannot live without it. And we must protect the water that we have and secure it for our future. Given this, the water & wastewater industry has serious work ahead and faces several significant challenges if it is to succeed. One challenge is to manage the amount of energy used in treatment processes and thus reduce the related carbon footprint.
Water reuse and wastewater treatment are intrinsically energy intensive. This is due to the need to move large volumes of water with pumps and electric motors in addition to the water treatment process needed to meet stringent regulatory requirements. In conventional wastewater treatment plants (WWTPs), aeration is one of the biggest, if not the biggest, energy consumers for treating wastewater. Other significant energy consumers include filtration and disinfection processes.
To cope with increasing energy consumption, the Water & Wastewater Treatment industry is adopting new technologies like advanced industrial analytics software.
Why an Environmentally Sound Water Treatment Cycle Is Needed
Water one of the most essential requirements for human health, environmental sustainability, and economic development. Due to population growth, urbanization, climate change, and lack of proper water management, this vital resource has become scarcer in many communities around the world.
In order to meet the increasing demand for clean water, there is a growing need for societies to shift towards a more organic and environmentally sound cycle. Instead of just discharging wastewater into the environment, it needs to be captured, treated, and distributed back to the consumer. This treatment cycle, however, requires a great deal of energy. But with the help of advanced industrial analytics, the industry can make greater strides at improving treatment process efficiency and reduce its energy consumption.
A Quick Look at Evolving Approaches
These days many companies are engaging technology pilots to explore options for reducing costs, increasing overall equipment effectiveness (OEE), and meeting regulatory standards. One example is the use of anaerobic membrane bioreactors (AnMBR) which are used in WWTPs to separate and treat sludge from wastewater, generating biogas as a byproduct. This technology can drastically reduce the energy consumption in large plants by generating renewable energy on site. In addition, the industry is looking into using microbial electrical systems to generate electricity while treating wastewater with microbial fuel cells (MFC), but this approach is still in its early stages of development.
In treating water, aeration is a key energy consumer in wastewater facilities, and because of this, a lot of research has been conducted to optimize these processes. To give some examples, membrane aerated biofilm reactors are an emerging technology in which oxygen is transferred much more efficiently. In addition, improved and more efficient mixing can be achieved by optimizing large bioreactors. This results in less greenhouse gases like methane and nitrous oxides.
Additionally, improved disinfection and filtration processes can significantly contribute to the reduction of total energy consumption; however, this depends largely on the level of water quality standards required for the application. Another novel technology that can reduce energy consumption is the use of UV light. Also, improved membrane technologies like ultrafiltration and reverse osmosis are gaining more attention for reducing the energy impact. Yay, science!
Unlocking the Value of Captured Plant Sensor Data
One of the best ways to leverage these new innovative technologies is to apply advanced industrial analytics to process data generated by sensors. This data provides unique opportunities for improving energy efficiency. As data is only as valuable as the solutions it unlocks, understanding its potential is essential. Complex optimization problems are frequently tackled by a limited group of data scientists who use the data for building and validating mathematical models. For instance, computational fluid dynamics (CFD) modelling is gaining much more traction in this industry.
Another strategy is to empower subject matter experts with analytics, for they are the ones that have deep knowledge of the production process itself. If these experts can quickly access, search, and analyze the historical time series data, they will be able to answer relevant questions in their day-to-day jobs at the time these questions need answering, without the delay of having to rely on data scientists.
Using advanced industrial analytics solutions to analyze plant data allows process experts to generate and test hypotheses by using descriptive, discovery, diagnostic, and even predictive analytics. Many other industries such as Oil & Gas, Chemicals, Metal & Mining, Pharmaceuticals, and Food & Beverage, have found tremendous value in using these solutions.
Reducing Energy Consumption with Advanced Industrial Analytics
Before starting any energy management project, it is crucial to first define your problem and identify the high energy consumers. First, you can benchmark optimal operating conditions using descriptive analytics. These benchmarks can be used to assess cost saving opportunities and set priorities for optimization projects. Second, you can use discovery analytics to determine optimal operating conditions to configure monitors and set alerts for process issues.
For example…
- When leaks occur which can be detected if levels in tanks decrease abnormally fast.
- When sensors need to be replaced or calibrated.
- When flow control valves start to wear out or get plugged.
- When membranes become fouled as detected by increased hydraulic head losses.
These anomalies can be detected and used as a premise to prompt process experts in the field to take action, as seen by experts in these following successful use cases…
PWN Use Case
PWN, a Dutch water company, used an advanced industrial analytics tool to analyze time-series data. Engineers wanted to calculate the hydraulic head to analyze and monitor the performance of their water network. By performing a descriptive analysis, they were able to distinguish between the two operating zones and found that hydraulic head losses increased after construction works (Figure 1).
Figure 1. Calculated hydraulic head as a function of flow.
Similarly, an advanced industrial analytics tool can also be used to optimize and follow-up the pump performances by comparing the actual pump performance curve to the pump performance curves of the manufacturer. This comparison can provide insights to the energy efficiency of the pumps. Moreover, the current state of the installed system can be monitored live and can be used to better predict the need for possible maintenance.
Evides Use Case
Evides, also a Dutch water company, found that a significant amount of energy could be saved by using a redundant reverse osmosis skid to deliver the same production rate. This became clear after using an advanced industrial analytics software to preprocess, filter, and plot the relevant data of a reverse osmosis unit at an industrial WWTP in Antwerp. (Figure 2).
Figure 2. Production rate as a function of Energy consumption.
Covestro Use Case
As mentioned before, other industries such as Oil & Gas, Chemicals, Food & Beverage and more have obtained tremendous value from using advanced industrial analytics, especially in reducing energy consumption. Covestro, a global chemicals company is an example. Covestro initiated three major energy savings projects for their polyether plant in Antwerp Belgium as part of its energy savings goals and ISO50001 directives. An advanced industrial analytics solution was used to analyze plant data for online detection, logging and explaining unexpected energy consumption, and comparing the results with the 2013 reference year.
The comparison of the averages of steam consumptions and production rates for four consecutive years are shown in Figure 3. Using specific formulas and calculated tags, various energy consumers were monitored and controlled. Through monitoring the performance against the reference year, the energy consumption was effectively decreased year after year, meeting corporate goals. More importantly, by fully utilizing process data with the help of an advanced industrial analytics tool, Covestro gained a growing knowledge and insight into the production process and was able to continuously improve their overall performance.
Figure 3. Comparing results of energy measures to reference year 2013 at Covestro, Antwerp.
Energy Management 4.0 Is Here
It is critical to raise data analytical awareness in all energy intensive industries. New advanced industrial analytics software brings subject matter experts to the forefront of the analytical process by enabling them to analyze, monitor and predict process and asset performance. This can significantly contribute to meeting an organization’s energy management and carbon footprint goals, especially when process knowledge is needed to improve operational performance and asset reliability. An added benefit is that these improvements come together with increased safety and profitability.
Yes, it is now possible for the Water & Wastewater Treatment Industry to reduce energy consumption, and this can be done by adopting an advanced industrial analytics tool. This is key.
