COMBINED CONTROL OF SEWER AND WASTEWATER TREATMENT PLANT UNSING IDENTIFIABLE MODELS THE SMArt CONTROL OF WASTEWATER SYSTEMS PROJECT

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1 COMBINED CONTROL OF SEWER AND WASTEWATER TREATMENT PLANT UNSING IDENTIFIABLE MODELS THE SMArt CONTROL OF WASTEWATER SYSTEMS PROJECT D. Thornberg*, M.K. Nielsen** and S. Bay Jørgensen*** * Helsingør kommune, 3000 Helsingør; det59@helsingor.dk **Krüger A/S, Gladsaxevej 363, DK-2860 Søborg ***CAPEC, Department of Chemical Engineering, Technical University of Denmark, DK-2800 Lyngby Denmark. ABSTRACT Coordinated control of the integrated sewer system and wastewater treatment plant can be ensured, provided suitable models are available. The SMAC project is focussed on grey-box models. The Danish part of the implementation will be performed in Helsingør where new operation techniques within the plant allows a larger part of stormwater flows to be treated biologically. The ATS method will be tested at a recirculation plant. Further biological nutrient removal can be improved by controlled biological hydrolysis of internal sludge streams. KEYWORDS Wastewater system, Control, Grey-box modelling, SMAC, Aeration Tank Settling, Biological phosphorus removal, Helsingør. BACKGROUND Wastewater systems, which comprise sewer network and wastewater treatment plants, are subject to large fluctuations in flow and concentrations of the wastewater. Since biological wastewater treatment processes rely on microorganisms, sudden changes in the influent load can deteriorate the nitrogen and phosphorus removal efficiency. Thus, to avoid shock loads during storm water situations for instance, large amounts of pollutants are diverted untreated to the receiving waters. New knowledge on the potential and limitations of wastewater treatment still needs to be implemented into the control of the wastewater systems. Furthermore, the control of wastewater systems is currently performed in local sub-optimising units and the effect of a local control action on the other units is not taken into consideration. Most systems are also designed for peak situations and thus a spare capacity is available in most situations but is currently not exploited. Coordinated control of the integrated sewer system and wastewater treatment plant can be ensured, provided suitable models are available.

2 STATE OF THE ART Several models and model conglomerates have been proposed for the description of wastewater systems. Three main model purposes can be listed: a) Detailed planning of system physical structures database registration, hydraulic deterministic. (for example MOUSE, Hydroworks). For wastewater treatment plants hydraulics is usually simple but bacterial kinetics is included (examples EFOR, Simba, GPS-X, STOAT, WEST). b) Overall planning of sewer system based on rain series and critical points (Example SAMBA) c) Models generally intended for on-line control. These must be valid for points in the system where control is possible such as basins or pumping stations. A promising possibility is the adaptive identifiable models (e.g.: grey box). The latter types of models are not yet well developed. In general, control of sewer systems is scarce or is only investigated at a research level. Design of storm water treatment in wastewater systems and modelling is based on flow and very little on compounds/pollution/matter measured as COD, SS, N or P. Attempts have been made to use calibrated deterministic models with many parameters to predict some hours ahead and thereby choose storage and overflow strategy but have not been very successful. The main problem has been that the type of model was not suitable for the purpose since parameters in the model were not easily identifiable on the basis of the information available from the sewer system. Calibration is tedious and not stable with time. Pipes and manholes and slopes may be well described but irregularities like tree-roots, sedimentation, holes, deformations, etc. are gradually becoming more important as a sewer system is ageing. It is thus important to develop a relatively simple model, which possibly can adapt to changing conditions in the sewer system. The model parameters should be identifiable using available on-line data. For wastewater treatment plants deterministic models (type a) are generally used for off-line process optimisation. In Denmark, the on-line measurement based and process oriented system STAR (Nielsen et al. 1993, 1995) has been implemented at a dozen full-scale wastewater treatment plants. This system mainly optimises the biological nutrient removal based on continuous measurements. In Aalborg a preliminary system has been investigated where the influent to the treatment plant was predicted one hour ahead. The prediction was based on one rain gauge and a simple double harmonic expression. The harmonic expression described the diurnal variation of flow and a transformation of the rain intensity into delayed flow. The flow prediction was used to change the operation of the plant to cope with an increased flow in stormwater situations. When the predicted flow reaches a defined maximum the operation of the plant was changed to Aeration Tank Settling (ATS) operation (Nielsen et al. 1999). The experience shows that up to 100 % increase in hydraulic load can be handled through the biological treatment plant without sludge loss. The prediction enables the plant operation to change the distribution of sludge in the tanks before the stormflow arrives at the plant. First flush phenomena in connection with stormwater incidents suggest the inclusion of concentrations in the control. Experience has been obtained with on-line in-situ measurements of

3 particulate COD and soluble COD in sewers measured as turbidity and UV absorption respectively (Bechmann et al. 1999). Other authors have worked on the use of simplified models for real time control of stormwater incidents, for instance Duchesne et al THE SMAC PROJECT A 3-year research and development project with support from the EU 5 th framework program called SMArt Control of wastewater systems (SMAC) was commenced in March The research consortium consists of 11 partners from Denmark, Poland, Germany and the UK. The general aim of the SMAC project is to produce a so-called All-embracing control system which employs quality checked data from the whole collection and treatment system to optimise the capacity of the wastewater systems with improved control. Relatively simple identifiable models including models of type c above (grey-box) will be used to evaluate the correlation between the flows, processes and possible actions in the near future. The flow estimates will be improved and extended with estimates of the concentrations of major pollution components such as COD, nitrogen and phosphorus. These estimates will be used for suitable control actions that minimises the overall pollution output of the environment. The All-embracing Smart Control System Performance Assessment Performance Optimiser Level 4 Disturbances Situation Assessment Data Assessment Set point Optimiser Set point Manoeuvring 3 2 The Smart controller Sensor Handling Actuator Handling 1. Wastewater System Figure 1. An all-embracing control system The structure of data management of the all-embracing control system is illustrated in Figure 1. Four boxes in the left side (arrows up) represent data collection and treatment whereas the four boxes to the right (arrows down) represent the forming of control actions based on the collected data. Level 1 represents a simple closed loop control with one measurement and one actuator.

4 Higher levels introduce situation assessment and evaluation of performance in relation to effluent standards and economy. The results of the 3 years development will be tested in full-scale wastewater system in Scotland, Poland, Germany and Denmark. Today advanced control in STAR is limited to empirical adjustment of criteria functions to handle the non-linearity in the processes as shown in figure 2. The SMAC project intends to substitute these empirical rules with model based criteria. Ammonium end point Nitrate end point 4 Nitrification phase 10 Denitrification phase Nitrate gn/m3 Ammonium gn/m3 Figure 2. Criteria functions for shift from nitrification phase to denitrification phase The SMAC project will also focus on biological nutrient removal and the control of carbon source addition in combination with control of the internal carbon sources in the sludge using the aeration system and oxygen set-points. Long term effects of these control actions on population dynamics and sludge characteristics will be included. The grey box modelling of sewers Rain gauge Rain flow in pipe Time Plant capacity Dry weather flow Time Figure 3: The sewer flow is considered as a sum of rain flow and the dry weather flow

5 To model a total catchment area using grey-box models, the area must be divided into a few subareas where concentration and flow can be identified from a dry weather model describing the normal behaviour of flow and concentrations for the relevant of these areas. This model must be supplemented with a rain and settlement model for rain situations (figure 3). The first analysis must identify points that best characterise the main catchment parts. Figure 4. Sub-catchment areas in Helsingør For each area only the following a priori data is necessary: Fr = Reduced area, (Rain flow is proportional to this area and rain depth) Qs = The mean daily dry weather flow from the area (including infiltration and sewage) F = Physical area Qk = Critical flow during rain to meet the authorities demand n = number of discharges/year accepted by authorities V = Volume of controllable basins in the area. (To be designed) Pe = Pollution load from the area in population equivalents (1 pe = 60g BOD5/day) The identification of concentration and flow at major point of discharge of the water in the sewer system can be exploited to select which water must be treated, and what need to be discharged and where. The expected new demands from the government are normally handled by building equalisation basins. SMAC may prove that the volume needed can be reduced, by documenting that the mass transfer to recipients is reduced by treating more water and by treating the most polluted water. This can be accomplished by implementing a different distribution of equalisation basins

6 with the identified models. Key parameters from the identified Grey-Box models are fed back into the conventional design models, SAMBA or MOUSE, and used for off-line design evaluations. Traditionally sewer models only handle flow evaluation in the decision for control; newer work has proved that on-line identification of both water and material flow may be possible, by applying reduced models that can be identified from online data. The Danish implementation The Danish string of the SMAC project will be implemented in the municipality of Helsingør (Elsinore). As test community for the SMAC project, the municipality offers the sewer system and two plants from adjourned catchment. Further full access to all relevant information is available for the project. The construction changes needed at the central WWTP to implement the beneficial controls will be established. The modification of the sewer system will be implemented at a later stage, if the benefit of these changes can be shown feasible after the research work of the partners in the SMAC-project. The control and data handling system at both plants in Helsingør is up to date, with nutrient online sensors and tuning and reporting systems (STAR) that has been in operation for 2 and 6 years. The sewer system pumping stations are connected to the SCADA system, but no advanced monitoring or control is implement yet. The controllable volumes in the sewer system are limited. However there is a part of the catchment area that can be established as optional dividable load between the two plants. The flow could be divided on a continuous basis to either of the plants depending on a dynamic calculation of hydraulic and organic capacity. By introducing STAR control, at the plant the use of precipitation chemicals was reduced by 40%. Figure 5 shows that probably full biological phosphorus (Bio-P) removal is feasible. The daily mean value of the on-line data are, periodically stable at a very low value, even for a period of weeks, with low or no chemical addition. Experiments were performed from August to November 2000 (centre of figure). Figur 5. Phosphorus concentration in the outlet from Helsingør wastewater treatment plant. The improvement of Bio-P is obtained by balancing the pools of organic carbon in the sludge against the dissolved oxygen levels and the anoxic/anaerobic fraction of the sludge. By doing so

7 also the nitrogen discharge will be minimised and the sludge production and energy consumption will be minimised. This balancing demands the best distribution of the load to supplement the existing STAR tuning of aeration. This possibility is established by making dynamic adjustments of inlet distribution for raw water in the anoxic zones. The ATS control principle is used with great success at many alternating wastewater treatment plants. The ATS concept will be tested in the recirculation type plant of Helsingør. The hydraulic capacity of the plant is increased by introducing settling in the last sections of the aeration tanks at Helsingør wastewater treatment plant. The hereby-created extra capacity is planed used to control the distribution of wastewater to the plants, during storm situations, so the expected extension of equalisation tanks in the sewer system can be reduced. The last part of the aeration tank is periodically made settling by stopping aeration. When the sludge settles the water to the clarifier from the top of the tank will carry less sludge, so the clarifier can handle much more water, without overload of sludge. 3 kg/m 3 SS 0,5 kg/m 3 SS 8 kg/m 3 SS Figur 6. ATS in RC plant The critical question is whether the sludge will move towards the recirculation outlet in the bottom of the tank; or will it form channels, so the process will become unstable after a period. If only the period before channel forming is sufficient, e.g. 2-4 hours, the process will be feasible. The establishment needs for ATS control in the SMAC project is refitting of all 3 aeration tanks, so that the recirculation flow is extracted from the bottom of the outlet end of aeration tanks according to a Krüger patent. The existing pumps will be used for the return of the internal settling sludge, but the channel and suction funnels must be established. The capacity of ATS and the time delay before it is fully efficient are the main questions to be answered by the coming tests. Since most nitrogen removing plants in the world is of the recirculation type, a successful outcome of the ATS tests will have significant implications on stormwater control at wastewater treatment plants

8 REFERENCES Bechmann H.., Nielsen, M.K,. Madsen, H., Poulsen, N.K., (1999). Grey Box Modelling of Pollutant load from a Sewer System. Urban Water Duchesne S., Mailhot A., Dequidt E and Villeneuve JP. (2000). Simple Mathematical Modelling of Sewers under surcharge for Real Time Control of Combined Sewer Overflows. International Conference on Urban Drainage via Internet; Nielsen M.K., Lynggaard-Jensen A. (1993). Superior Tuning And Reporting (STAR) - A new concept for on-line process control of wastewater treatment plants. IAWQ ICA workshop 1993, Hammilton Canada Nielsen M. K., Önnerth T. B. (1995). Improvement of a Recirculating Plant by introducing STAR Control. Wat. Sci. Tech. Vol. 31 No 2, pp Nielsen M. K., Bechmann H., Henze M.,. (1999). Modelling and Test of Aeration Tank Settling ATS. Presented at IAWQ 8 th Conf. on Design and Economics of Large WWTP. Budapest, Sept 1999.