Energy-saving through remote control of a wastewater treatment plant S. Marsili-Libelli *, G.M. Maietti** * Department of Systems and Computers, University of Florence, Via S. Marta 3, 50139, Florence, Italy (E-mail:
[email protected]) ** Acque SpA, Ospedaletto (PI), Italy
Abstract
This paper describes an energy-saving project being implemented on a conventional wastewater treatment plant, where several management actions, previously manually operated, are now supervised remotely and operated by automatic controllers. The main energy-saving target is the control of dissolved oxygen in the context of nitrogen removal and automatic controllers are being designed around the oxidation section for adjusting the air flow to the timevarying treatment requirements. The other important aspect of the project is the plant capability of being remotely controlled via a complex data communication network over the internet. Keywords: Activated sludge process, Internet systems, Remote control, Automation
INTRODUCTION Energy saving is becoming the most important feature in wastewater treatment process operation and a considerable effort and funding is being devoted to achieving the goal of a safe and economical operation. A considerable research effort is being conducted in the EC and elsewhere to limit the energy expenditure during plant operation (Baeza et al., 1999; Ingildsen et al., 2002; Cadet et al., 2004; Ayesa et al., 2006). This goal is pursued with the aid of distributed and supervisory control (Baeza et al., 1999; Baeza et al., 2000; Ayesa et al., 2006) and advanced instrumentation (Olsson, 2002; Olsson, 2006; Olsson and Jeppsson, 2006). This paper describes an in progress research collaboration between the Department of Systems and Computers and Acque Ingegneria for the automation of a wastewater treatment plant with the aim of energy conservation. This paper describes the results achieved during the first part of this research, in which the main remote control system has been set up, enabling the monitoring of the plant operation from the company internet network and. The monitoring was made possible by installing a local programmable automation controller (PAC) at the plant site to manage all the acquired data, which are samples at 1 sec. intervals and stored every minute in the PAC non volatile memory, to be later transferred to the main archiving centre. This system enable close monitoring of the energy consumption, which is for now limited to the oxidation tanks, but will be extended to the nitrification/denitrification processes in the next phase. The plant being considered in this study is a conventional one, with predenitrification and internal recycle, as shown in Figure 1. The oxidation section of the plant consists of three parallel completely-stirred tanks, each with two independent surface aerators powered by an inverter-driven electric motor with a
built-in PID controller. For each tank there are two luminescent dissolved oxygen meters (LDO, Hach-Lange, Düsseldorf, Germany) which provide a continuous DO signal to the SC1000 digital controller which converts the probe signals into a 420 mA current loop to be acquired by the compact FieldPoint (cFP) unit, which closes the control loop through the inverters driving the aeration systems. Each DO probe thus controls the nearest surface turbine in the same tank. There are also two outer loops regarding the NOx measurement (Nitratax, Hach-Lange, Düsseldorf, Germany) in the denitrification tank and the oxidation output and an ammonium sensor (Amtax, Hach-Lange, Düsseldorf, Germany) at the oxidation output. The cFP can be accessed via an Ethernet link with TCP/IP protocol, being inserted in the company intranet system, as described later, through a local hub. The paper is organized as follows: first the internet/intranet system is described, then the automation of the secondary treatment is presented and discussed.
INTERNET/INTRANET TELECONTROL SYSTEM The control and automation system of the Pagnana WWTP uses conventional hardware and software components and is part of a vast supervisory control system linking all the company resources in terms of WWT and potabilization plants, which are currently used for real-time management. General configuration of the network Figure 2 shows the general architecture of the network, which hinges on the main control centre (Centro Generale di Telecontrollo), located at Ospedaletto (PI), which can be accessed from the Measurement lines Command lines
Nitratax Oxidation NOx
Nitratax Denitro NOx
to secondary sedimentation
DO
DO
Denitrification
DO
from internal recycle
Amtax Oxidation NH4
Water flow
DO
from primary sedimentation
DO
DO
compact Field Point 4-20 mA WWW
SC1000 Inverter motor drives
Figure 1. Measurement and automation scheme around the secondary treatment stage of the wastewater treatment plant. internet address http://telecontrollo.acque.net, allowing the following functions to be performed in real-time: • plant operation monitoring • daily archiving of current measurements • process parameter control • energy consumption monitoring
• •
optimization of energy expenditure optimization of maintenance operations
The supervisory control network is composed of several data collection subcentres organized in a hierarchical mode. They are all linked to the main General Control Centre, which is manned around the clock and has the purpose of collecting and archiving the data coming from each sub-centre. Each plant is equipped with a Remote Terminal Unit (RTU) which collect the process data and relay them via low-speed dedicated modem lines, radio modems in the UHF band, GPRS and/or Ethernet lines. Some RTUs are subject to a regular polling by the Front-End computer, which supervises the queries and commands, whereas other, less critical RTUs transmit only in case of a variation of the process parameters. The RTUS using GPRS for their communication link implement this latter scheme for line savings, whereas those using an Ethernet link are continuously connected to the Front-End. The sub-centres are star connected to the main centre via a redundant link. In all, the whole network connects over 20 remote installations.
Figure 2. Schematic view of the Acque SpA supervisory information system, showing the internal branching of the company intranet.
Pagnana local control system The local telecontrol system, shown in Figure 3, is composed of three basic unit: • •
one compact Filed Point (cFP) (National Instruments, Austin, TX, USA) for the control of the oxidation and denitrification sections two remore data acquisition units for the local control of the other plant units (preliminary treatments, flow control and power distribution)
•
one SCADA server designed on the Movicon platform through which the plant local network is connected to the general network architecture
The field measurements are fed into the cFP as 4-20 mA current signals, generated by the SC1000 digital instrument controller. The data are then rescaled to their engineering units, filtered with a Bessel filter bank, processed and archived on a daily basis by a specific supervisory system developed in the LabView (National Instruments, Austin, TX, USA) software platform. The cFP controller communicates with the local SCADA system via its built-in OPC server. Through this link the real-time process data are made available to the Movicon SCADA from which they are broadcast through the entire network. The cFP can be accessed by a remote client via a Virtual Private Network (VPN) connection allowing direct connection through a web browser for data downloading via ftp or software update via proprietary web services.
Figure 3. Schematic view of the Pagnana sub-network, showing the compact Field Point device, operating as the local controller.
Connection of the compact Field Point (cFP) over the net As outlined in Figure 1, the cFP is directly connected to the field measurements coming from the digital instruments controllers SC1000 or via a direct 4-20 mA current loop. There are 34 analogue input signals and 8 analogue output commands. Compact FieldPoint is an expandable programmable automation controller (PAC) composed of customizable I/O modules and intelligent communication interfaces. The cFP I/O modules filter, calibrate, and scale raw sensor signals to engineering units, as well as perform self-diagnostics to look for problems, such as an open input port. Through its built-in Web and file servers, the cFP interface automatically publishes measurements over the Ethernet network.
•
Deploy real-time embedded controllers for stand-alone data logging, advanced analysis, and process control.
•
Access I/O points nearby or miles away on the network using the same simple read and write software framework.
•
Connect virtually any sensor directly to the wide variety of analogue and discrete I/O modules.
•
Download custom LabVIEW application to the embedded controller for stand-alone operation.
The real-time control software running in the unit is developed in the LabView 8.20 platform and deployed onto the cFP either via direct Ethernet connection or through another port in the communication network. This can be done by direct connection to a local hob in the Pagnana sub-centre or via a Virtual Private Network (VPN) connection form any authorized remote location. There are three main remote communication modes between a remote user (client) and the cFP (server): 1) Via Measurement and Automation Explorer (MAX): this is the basic monitoring device developed by National Instruments to supervise. It can be used to perform a number of important maintenance and operation tasks, among which Configure the National Instruments system hardware and software; Create and edit channels, tasks, interfaces, scales, and virtual instruments; Execute system diagnostics; View devices and instruments connected to the system. A view of the remote system installed at Pagnana via MAX is shown in Figure 4.
Remote system name
Remote system configuration
Real-time check of input channels (first module) cFP-AI-111 @1
Figure 4. A view of the cFP remote system installed at Pagnana. The left column shows the system configuration, whereas the right panel shows the real time operation of the analogue input modules of the fist data acquisition bank, named cFP-AI 111 @1. 2) Via FTP remote client: this is the most convenient model for downloading the file data where the cFP stores daily operational data at 1-minute sampling intervals. At midnight each day the system closes the current file, bearing the date in the file name, and opens a new one with the new date tag. Each daily file is about 300 Kb and stores 38 variables.
3) Via LabView Web services: by enabling the LabVIEW Web Server on the server machine (in this case the cFP) and the embedded networking functionalities, the data and originating in the cFP can be interactively published in the WEB (National Instruments, 2002). Four main sets of functionalities are available for publishing data, sharing data, remote control, distributed execution. Of these capabilities, the one which is used here most prominently is remote control, whereby a remote PC can control the execution of a cFP-based application. Though the application still runs on the host computer, the remote user has complete control over it through the control handles of the user interface that appears in the Web browser. Other users also can point their Web browser to the same URL to view the test, but to avoid confusion, only one client can control the application at a time, but that control can pass easily among the various clients at run-time. Errore. L'origine riferimento non è stata trovata. shows the front panel of the main real-time control application running in the cFP. Any authorized user can access this controller just by typing the cFP IP in the net followed by the software file name. The control panel shown in Errore. L'origine riferimento non è stata trovata. includes the six control loops from a DO probe and the nearest aeration surface turbine. Each controller is represented by a green triangle, representing the current DO set-point superimposed to a red bar, showing the actual DO value in that part of the tank. Coincidence between the two indicated a good regulation. Below, a numeric display shows the power consumption of each turbine and in each tank. More indicators in the lower part show the current values of nitrate, ammonia, sludge concentration in the oxidation tanks and in the settler underflow, process flow-rates, pH ORP, etc.
Figure 5. Front panel of the main LabView real-time control application running in the cFP. The user interface shown above can be accessed via the web just by typing the cFP IP in the net followed by the software file name.
CONTROL SYSTEM DESIGN AND PERFORMANCE The control loops implemented so far include the six DO control loops, comprising the DO sensors Rate and the inverters driving the Filtering cFP-AI-111 cFP-AO-200 PID limiter surface turbines. Given the flow 4 – 20 mA 4 – 20 mA configuration in the three parallel oxidation tanks, the best control arrangement was found to be the one with each DO error driving the nearest turbine, as illustrated in Figure 1. Each DO control loop has the structure shown in Figure 6. The DO signal is processed by the SC1000 instrument interface and Figure 6. Single DO control loop. The blocks sent to the cFP over a 4-20 mA in the box are the functions performed by current loop. The cFP performs the analog-to-digital conversion, after the cFP. which the digital signal is filtered with a 3rd order Bessel low-pass filter, after which it is fed into the ProportionalIntegral-Derivative (PID) controller driving the power drive, which in turn controls the speed of the surface turbine. The DO set-points are determined in a way to minimize energy consumption, which depends on the current oxygen consumption for carbon and nitrogen degradation. As an example Figure 7 shows the energy saving of 1 MWh in one week of controlled PID operation, by comparing tank 1, where the control was applied, to tank 2, where constant power was maintained. This I result is in line with other experiences (Ingildsen et al., 2002; Cadet et al., 2004). cFP
DO Set-point
analog output module
analog input module
Power lines
SC1000 instrument interface
Power drive
Surface turbine
LDO probe
Oxidation tank
16 – 23 Febbraio 7000
Vasca 1: Regolazione PID interna 9 – 11 Marzo DO (mg/L)
ΔE ~ 1000 Kwh su 7 giorni 6000
5000
0.9 0.8 0.7 0.6
Vasca 2 senza controllo
0.5
Vasca 1 con controllo PID Inv3 (Kw)
3000
2
2.5
3
3.5
2
2.5
3
3.5
2
2.5
3
3.5
15 10
0.5
1
1.5
Inv4 (Kw)
giorni
1000
0
1.5
20
2000
0
1
giorni
4000
1
2
3
4
5
6
7
24 22 20 18 16 14 12
0.5
1
1.5
giorni
giorni
Figure 7. Energy saving results of one week of controlled operation. The load input fluctuation is completely offset by the PID controller. 1200 Turbine speed (rpm)
It is interesting to notice that during the DO regulation period, the load fluctuations are reflected by the varying power delivered to the turbines, as a consequence of the changing oxygen consumption requirements.
The DO control system, implemented in LabView, was based on the stepresponse identification of the DO probe, inverter, turbine chain, which showed the experimental response of Figure 8. This was approximated with a second-
1100 1000 G( s ) =
900
ωo = 0.0946 ζ = 2.4193
800 700
0.0090 s 2 + 0.4578 s + 0.0090
0
50
100
150
Time (s)
Figure 8. Identification of the control loop dynamics by the step-response method.
order overdamped transfer function and from the close loop transfer function the digital PID coefficients were computed (Aström and Wittenmark, 1984; Aström and Hägglund, 1995).
CONCLUSION A research collaboration is in progress between the Department of Systems and Computers and Acque Ingegneria for the automation of a wastewater treatment plant with the aim of energy conservation. In the first part of the research, the main remote control system has been set up, enabling the monitoring of the plant operation from the main computing centre and from an authorized client via a VPN connection. A local programmable automation controller (PAC) was installed at the plant site to manage all the acquired data, which are samples at 1 sec. intervals and stored every minute in the PAC non volatile memory, to be later transferred to the main archiving centre. This system enable close monitoring of the energy consumption, which is now limited to the oxidation tanks, but will be extended to the nitrification/denitrification processes in the next phase. Even in this first stage the research has shown that a considerable energy saving can be achieved by automatic control of the dissolved oxygen level.
REFERENCES Aström K.J. and B. Wittenmark (1984). Computer controlled systems: theory and design. Prentice-Hall. Aström K.J. and T. Hägglund (1995). PID controllers: theory, design and tuning – second edition, Instrument Society of America. Ayesa E., A. De la Sota, P. Grau, J.M. Sagarna, A. Salterain and J. Suescun (2006). Supervisory control strategies for the new WWTP of Galindo-Bilbao: the long run from the conceptual design to the full-scale experimental validation. Water Science & Technology, 53 (4–5), 193–201. Baeza J., D. Gabriel and J. Lafuente (1999). An expert supervisory system for a pilot WWTP. Environmental Modelling & Software 14, 383–390. Baeza J.A., E.C. Ferreira and J. Lafuente (2000). Knowledge-based supervision and control of wastewater treatment plant: a real-time implementation. Water Science and Technology, 41 (12), 129–137. Cadet C., J.F. Béteau and S. Carlos Hernandez (2004). Multicriteria control strategy for cost/quality compromise in Wastewater Treatment Plants. Control Engineering Practice 12 335–347 Ingildsen P., G. Olsson and Z. Yuan (2002). A hedging point strategy – balancing effluent quality, economy and robustness in the control of wastewater treatment plants. Water Science and Technology 45 (4–5), 317–324. National Instruments (2002). Taking Your Measurements to the Web with LabVIEW. White Paper 2218. Olsson G. (2002). Lessons learnt at ICA2001. Water Science and Technology 45 (4–5), 1-8. Olsson G. (2006). Instrumentation, control and automation in the water industry – state-of-the-art and new challenges. Water Science & Technology 53 (4–5), 1– 16. Olsson G. and U. Jeppsson (2006). Plant-wide control: dream, necessity or reality? Water Science & Technology 53 (3), 121–129.
