How To Optimize RO Membrane Performance Using Data Normalization

Troubleshooting reverse osmosis systems can be daunting for system operators, especially when persistent operational issues lead to frequent downtime, increased maintenance expenses, and substandard permeate water quality.

The solution to these operational challenges lies in a standardized method for system operators to monitor and interpret day-to-day reverse osmosis (RO) system performance using a common set of values.

The solution lies in Data Normalization.

What Is Data Normalization?

Normalization refers to calculations that adjust recorded daily performance values to a common reference or baseline value by accounting for variations in feed water temperature, feed water total dissolved solids (TDS) and system pressures.

The sooner you normalize your data, the sooner you’ll be able to start tracking performance changes and compiling an extensive operating data history over time. This becomes invaluable in distinguishing between expected changes and potential problems, providing clarity in every stage of your system analysis.

NormRO data normalization is a program offered to Avista customers that allows for early warning and detection by monitoring the trends in the key indicators of membrane performance (e.g., flux, rejection, and pressure differential).

With RO normalization, troubleshooting processes are streamlined to overcome unstable operations and increased downtime and maintenance expenses.

In-Depth Explanation of the RO Normalization Process

The goal of RO normalization is to use the collected performance data to calculate normalized permeate flow, normalized pressure differential, and normalized salt rejection.

Let’s define each:

• Normalized Permeate Flow (NPF)
  NPF is a calculated value that represents the adjusted permeate flow rate in RO systems, accounting for variations in operating conditions.
  
  By accounting for external factors that may influence permeate flow, such as temperature fluctuations and water quality, normalized permeate flow provides a more accurate assessment of the RO system’s efficiency and allows for consistent performance monitoring.
• Normalized Pressure Differential (NPD)
  NPD is a calculated value that accounts for variations in pressure conditions within an RO system. It adjusts the differential pressure for change in concentrate and permeate flow to provide a standardized measure of the pressure difference across RO membranes.

Operators can identify trends, deviations from baseline values, and potential issues by standardizing the constantly changing pressure differentials and facilitating effective troubleshooting and maintenance.

• Normalized Salt Rejection (NSR)
  NSR is a calculated value that measures the system’s ability to remove salts and dissolved solids from the feedwater.

Normalizing salt rejection allows operators to evaluate the RO membrane performance consistently, regardless of variations in feed water quality or operating temperature. This metric is crucial for assessing the health and effectiveness of membranes in rejecting salts and maintaining the desired water quality standards.

These normalized values allow you to identify the optimal time for membrane cleaning and investigate potential pretreatment issues that may be causing increased fouling, enabling operators to make informed decisions and ensure optimal operation.

Let’s delve into the key parameters and factors involved in this optimization process.

Four Key Parameters for RO Normalization

These operating conditions collected as raw data, are crucial in calculating normalized values that provide a standardized measure of RO system performance.

The reference data set may be taken from the design projection measured at the initial start-up or after the latest membrane changeout.

• Normalization with reference to the original design or warranty is useful to verify that the plant performs as designed.
• Normalization with reference to the start-up values, is useful to show any performance changes in new membranes between day one and the actual date.
• Normalization with reference to the latest membrane changeout is useful to show the health of membranes compared to their performance when new.

Let’s explore the impact of these parameters:

1. Feed water temperature

As feed water temperature rises, water viscosity decreases, leading to a faster permeation rate through membranes. This temperature-driven effect can be significant, with typical figures showing a 1.5-2.5% change in RO membrane performance per degree Celsius.

Higher temperatures also increase the rate of salt passage, influencing overall system performance and permeate water quality.

2. System Pressure and Net Driving Pressure, NDP

Net driving pressure, or the difference between the feed pressure and the osmotic pressure, is the driving force for moving the feedwater through the RO membranes. As the net driving pressure increases, more permeate is produced. 

This increased production, in turn, dilutes the salt passing through RO membranes, leading to improved permeate quality. Hence, understanding and managing system pressure is vital for maintaining optimal RO performance.

3. Feed water TDS

Any change in feed water TDS directly influences the osmotic pressure. This is because the pressure applied must overcome the osmotic pressure of the feed water, which is proportional to the total dissolved solids present. So, fluctuations in feedwater TDS will cause a corresponding change in the RO membrane system performance, particularly in water quality and feed pressure.

4. Feed and permeate flowrates

The ratio of permeate water produced to feed applied, known as percent recovery, is a key metric influencing the average feed-concentrate salt concentration. This, in turn, affects the osmotic pressure and the net driving pressure within the system.

Understanding these water flow rates and recovery percentages is essential for calculating normalized values such as normalized permeate flow.

In the normalization process, these key parameters provide the raw data for precise calculations. The significance of the data collected in this process cannot be overstated.

Case Study: Addressing RO Membrane Fouling in a BWRO Plant

Let’s explore a real-world scenario in a case study example to provide a deeper understanding.

A brackish water reverse osmosis (BWRO) plant encountered difficulties improving feed water quality, leading to a notable increase in the first-stage differential pressure (dP). The need for cleaning became evident, and the initial attempt was triggered by the heavily fouled cartridge filters and the rise in normalized dP.

Here’s how NormRO data normalization helped in addressing the challenges faced by the BWRO plant:

• Normalized values provide a standardized reference, enabling operators to discern changes in performance against a consistent baseline value. In this case, the increase in normalized dP served as a key indicator, prompting the Avista site team to recognize the need for intervention.
• The consistent review of normalized data indicated the need for a clean-in-place (CIP) to be performed. The CIP was performed in a timely manner, preventing any damage to membranes from severe fouling.
• The CIP process improved the RO system’s normalized flow by about 10%. However, the rapid fouling recurrence post-CIP highlighted the necessity for a more tailored approach.
• The ability to track normalized flow and pressure differentials post-CIP facilitated ongoing adjustments, leading to a proactive and iterative approach to optimizing membrane performance.

After the third CIP procedure, Avista system operators returned the flow to the baseline value, sustaining the performance for 171 days.

Why Data Normalization Matters

Data normalization is a cornerstone for maintaining a transparent record of operational data, enabling operators to distinguish between normal and unexpected system behavior.

Normalization will streamline your troubleshooting process by facilitating error detection, locating problem areas, and initiating timely corrective actions to address the problem before it gets more expensive.

Benefits of Data Normalization

RO normalization offers numerous benefits, enhancing the efficiency of RO systems:

1. Web-based System Accessibility: Authorized users can securely access data from anywhere globally.
2. Predictive Analysis: Trends in premeate production, rejection, and pressure drop allow for predictive plant cleaning schedules and optimization work.
3. Early Problem Detection: Monitoring trends in key indicators facilitates the early detection of problems, preventing escalation.

Download Our Normalization Technical Guide

Our Normalization Technical Guide was created for membrane operators worldwide to understand the importance and simplicity of proper data collection and tracking for improved results, minimized downtime, and cost savings.

It’s organized into four parts, one for every key parameter, ensuring it covers all essential aspects while maintaining ease of comprehension.

Download the technical guide for a comprehensive understanding of these intricate dynamics. Use this as a valuable resource in equipping operators with the knowledge needed for effective implementation.

As a supplement, we have created a technical guide on record keeping, too!

Normalize your data to guarantee stable performance and predictable operational results. Check out our RO Normalization Technical Guide to learn more.