AUTOMATIC SRT CONTROL

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1 AUTOMATIC SRT CONTROL Alex Ekster Ph.D.,P.E.,D.E.E. - Ekster and Associates Address: 1904 Lockwood Ave. - Fremont, CA , USA - Tel: (510) alex.ekster@iname.com ABSTRACT PICTURE NOT AVAILABLE The algorithm for automatic solids retention time (SRT) control is discussed. It is shown that utilization of an SRT automatic control system at the 7.3 m3/s San Jose/Santa Clara Water Pollution Control Plant stabilized the biological nutrient removal process, reduced effluent TSS and nitrite, eliminated Nocardia foam and low F/M bulking, and reduced number of laboratory TSS tests by 80%. The system required little maintenance and was very robust. KEYWORDS: Activated Sludge, Solids Retention Time, Automation, Wastage, Nocardia, Foam Control. INTRODUCTION Proper food to microorganism population (F/M) ratio, the single most important parameter affecting efficiency of an activated sludge system, is controlled by sludge wasting. Minimal variations of waste flow over time can have a profound effect on the performance of an activated sludge system. Inadequate wasting may cause clarifier overloading, low (F/M) bulking and foaming, and increased air demand for biomass endogenous respiration. Excessive wasting may cause poor removal of soluble pollutants, high (F/M) bulking, and, in the case of nitrification, excessive chlorine demand due to inadequate nitrite removal. Adjustment of waste activated sludge (WAS) flow usually is based on manual calculations using mixed liquor (ML) and often return activated sludge (RAS) total suspended solids (TSS) concentrations. TSS concentration is conventionally measured by a gravimetric analytical method. Use of this routine for WAS flow determination has at least three major problems: 1. Due to influent and RAS flows variations, TSS concentration in a grab sample can be 50% different than the daily average, which skews daily waste calculations. 2. Because sampling and analysis are time-consuming, the frequency of sampling and waste flow calculations are usually restricted to once or twice a day even though solids inventory is constantly changing. As a result, the optimum performance conditions for the activated sludge system are not met. 3. A gravimetric test takes between 2 and 4 hours to perform, which delays waste adjustment for several hours and adversely affects system performance. An automatic waste control system can provide constant accurate control over solids inventory, reduce the time required for sampling and sample processing, and eliminate human 20 o Congresso Brasileiro de Engenharia Sanitária e Ambiental 4144

2 errors associated with wastage calculations and lag time. In addition, the automatic waste control can stabilized sludge load to the sludge processing facilities. The system (see Figure 1) consists of two suspended solids meters, a controller (computer), and a waste flowmeter with a valve for adjustment. Information from the suspended solid meters is sent to the controller, the controller compares the operational criteria such as mixed liquor TSS or solids retention time (SRT) with the target value, calculates the necessary adjustment of the waste flow, and sends a signal to the control valve on the WAS line. Waste TSS Meter SRT set point CONTROLLER QWAS FLOW METER WITH VALVE MLTSS Meter Hydraulic flow Signal Figure 1. Automatic waste control system schematic METHODOLOGY The waste control algorithm consists of the following algorithm blocks: data processing, calculation, outcome filtration, and a safeguard (Figure 2). Data Processing Calculations Filtration Safeguard Signals Actuator Figure 2. Waste control algorithm. A data processing block filters the signals from the TSS meters and the waste flow meter. The filtering algorithm utilizes non-parametric statistics since TSS data usually is not normally distributed. It also detects malfunction of the TSS meters and waste flow meters, reports the malfunction to the operator, and prevents the utilization of a faulty signal in the control calculations. A calculation block is the pivotal part of the algorithm. The calculation block utilizes the proportional-integral (PI) control law. Preliminary analysis of the waste control loop showed that it would require up to a year to tune-up the PI controller. To reduce the time of algorithm development and tuning, a computer IAWQ wastewater treatment processes model (GPS-X version 2.2.1, Hydromantis Inc.) is utilized. The model is calibrated using field data. A match between calculated and factual wastage is used as a criteria for the 20 o Congresso Brasileiro de Engenharia Sanitária e Ambiental 4145

3 modeling. After model calibration, computer simulated response of the system with SRT feed back is utilized for the selection of both reset time (Ti) and proportional gain (Kp). The following criteria are used for designing the SRT controller: At a proportional gain equal to twice the Kp design value, waste rate values shall not start to diverge. The magnitude of each successive oscillation peak of waste rate values during a change should not exceed one fourth of the previous peak. Kp and Ti values are investigated for the range of potential SRT set points. Both upward and downward steps toward target SRT values are simulated. The selection of each pair of optimum Kp and Ti for each SRT usually requires at least 10 simulations. Based on the simulation, the relationship between Kp and SRT is determined. The calculation block is programmed with Ti value and the relationship between Kp and SRT. The calculated waste flow signal is filtered using a low-pass filtration algorithm also utilizing non-parametric statistics, then the signal is sent into a safeguard block. A safeguard block is the most sophisticated block in the algorithm. The purpose of this block is to check that the waste flow calculated by the controller will not have a negative effect on the Plant processes. Before the output signal is sent to the actuator (valve or variable speed pump), the safeguard block checks whether new waste flow may cause one of the following problems: a) overload clarifiers b) overload sludge processing facility, c) underload sludge processing facility, d) excessive variation of waste flow (load), or e) excessive change in biomass inventory. If there are no negative effects of waste flow change, the new waste signal is sent to the actuator. In addition, the safeguard block informs operators about potential mass-disbalance problems that could be caused by a significant change of sludge depth level in the clarifiers, metering problems, or other operational problems. Part of the developed controlled algorithm was tested to control SRT for the biological nutrient removal process at the 7.3 m 3 /s (167 MGD) San Jose/Santa Clara Water Pollution Control Plant (SJ/SC WPCP). The Plant is treating mostly domestic sewage, however, during summer time the organic load increases by 20%-30% due to additional wastes coming from the cannery. Details of SJ/SC WPCP design and operation have been described in detail by Ekster and Jenkins (1996). The suspended solids meters (Royce Inc., model 7011) were checked twice a week using a portable suspended solids meter (Royce Inc., model 711). The portable TSS meter was calibrated once a week using laboratory data. The meters readings were checked against laboratory data twice a day for six months. RESULTS AND DISCUSSIONS Computer simulated and factual waste flows closely match each other (Figure 3). Suspended solids readings were within 4% of the laboratory values. The control algorithm was programmed with theoretical settings of Kp and Ti into the Distributed Control System, and then field-tested. After several transient observations, it was decided to leave theoretical settings as final. The controller closely maintained the set point 20 o Congresso Brasileiro de Engenharia Sanitária e Ambiental 4146

4 (Figure 4) and the change in BOD was closely followed by MLSS (Figure 5). Automatic SRT control provided better SRT stability than manual control (Figure 6). Effluent nitrite and TSS stabilized, and average concentrations were reduced by 50% (0.15 mg/l vs. 0.3 mg/l) and 20% (8 mg/l vs. 10 mg/l), respectively. No erroneous waste flow signals were observed and at no time was the system out of service because of SRT system malfunction. These results indicate good performance of suspended solids meters and the control algorithm. The reliable operation of the waste control system allowed the number of laboratory analysis to be reduced by 80% Wastage flow, m 3 /d physical plant WAS model predicted WAS SRT SRT, days Time, days Figure 3. Waste flow: computer simulation vs. factual data. 5.0 SRT, days Figure 4. SRT Target SRT WAS Flow Time, days Typical long-term performance of SRT controlled process WAS Flow, m 3 /d 20 o Congresso Brasileiro de Engenharia Sanitária e Ambiental 4147

5 BOD 3500 BOD, mg/l MLSS MLSS, mg/l Time, days Figure 5. Effect of SRT Automatic Control System on MLSS Average SRT = 5.1 days Average SRT = 6.3 days Manual Control (1996) Automatic Control (1997) SRT, days Nov 17-Dec 16-Jan 15-Feb 17-Mar Date Figure 6. Comparison of SRT controlled manually in 1996 vs. SRT controlled automatically in After the implementation of automatic SRT control no Nocardia foaming and low (F/M) bulking was observed, though prior to implementation of automatic waste control it was a significant operational problem (Ekster and Jenkins, 1996). Figure 6 shows that with manually controlled sludge wasting ( data) there were many high SRT incidents. The periods of very high SRT, even during a short time, may encourage the nocardioforms growth. These organisms concentrate in the foam layer and are retained in the system by the surface foam trapping even when the SRT is lowered. When waste flow was controlled automatically incidents of extremely high SRT did not take place, and no nocardiaform foam was observed. We postulate that conditions favored by nocardiaform is less of existence when waste flow is controlled automatically. SJ/SC WPCP experience showed that with automatic SRT control it is possible to operate without nocardioform foam even at a higher average SRT than with manual wasting. 20 o Congresso Brasileiro de Engenharia Sanitária e Ambiental 4148

6 CONCLUSION Utilization of an SRT automatic control system at the SJ/SC WPCP stabilized the BNR process, improved effluent quality, eliminated Nocardia foam and low F/M bulking, and reduced number of laboratory TSS tests by 80%. The system required little maintenance and was very robust. BIBLIOGRAPHIC REFERENCES 1. Ekster, A. and Jenkins, D. (1996) Copper Removal Efficiency of Biological Nutrient Removal (BNR) Activated Sludge. Proceedings of the Water Environment Federation, 69 th Annual Conference & Exposition, WEFTEC 96. Vol. 1, pp o Congresso Brasileiro de Engenharia Sanitária e Ambiental 4149

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