A Computer Based Tool for Integrated Design of Wastewater Treatment Plants and Advanced Control Systems
Systematic methods and tools for managing the complexity
Tools Integration - CAPE Methods & Tools (T4-10)
Keywords: Process and Control Integrated Design, Advanced Control, Multi Objective Optimization, System Identification
Motivation and objectives
The public view concerning wastewater treatment these days is fairly positive. The EU Urban Water Directive (91/271/EC) adopted years ago, together with the newly adopted EU Water Framework Directive (2000/60/EC), define stringent requirements for urban wastewater treatment and a time frame for the step-wise implementation by the member countries. The application of the directive has lead to the construction of new plants and redesigns of the existing ones with the aim of reducing as much as possible the environmental impact. The associated costs to these actions have been very huge.
In this sense, the norm imposes several objectives, to be achieved by engineers that should be pointed out. First, the design of more complex but more flexible plants considering the new environmental restrictions facilitating their adaptation to future legislations, avoiding redesigns. Second, a stricter operation and control at must be guaranteed. To achieve the above mentioned aims, its necessary the use of Integrated Design Techniques, combining Optimization and Advanced Control, together with Computer Aided Tools to allow for the simultaneous design of plants and control systems at lowest costs.
Traditionally, process design and control system design have been performed sequentially. It is only recently displayed, that a simultaneous approach to the design and control leads to significant economic benefits and improved dynamic performance during plant operation. The Integrated Design (ID) methodology allows for the simultaneous design and evaluation of plants and control system parameters and brings together the development of a variety of design tools for the process design which has immense potential because of its several advantages. The biggest is that it will reduce costs significantly. It will also reduce the iterations between separate design operations - like synthesis and control system design, in addition to save design time, and improve design efficiency. The field of integrated process design and control has reached a maturity level that mingles the best from process knowledge and understanding control theory on one side, with the best from numerical analysis and optimization on the other. Direct implementation of integrated methods should soon become the mainstream design procedure.
On the other hand, today's designers need to consider several critical parameters and objectives. All of these parameters are closely coupled-optimization of one affects the others. Their interrelationships require design tools that can perform concurrent optimization, which can only be accomplished when the tools are part of an integrated design-tool suite and used within the right design flow. Concurrent optimization lets the designer solve problems that affect multiple design parameters.
Within this context, the objective of this work was the development of a Computer Based Tool for the Simulation and the Integrated Design of Activated Sludge Processes and their Control Systems to support engineers during the complex task of designing and control Wastewater Treatment Plants. The integration of Numerical Optimization, Model Identification, Dynamical Model Simulation and Model Based Predictive Control, is the most relevant feature of the package and, in our opinion, the key point to succeed in the design of flexible processes reducing the operation costs while legal specifications on the quality of the treated water are fulfilled.
The software allows dealing with different type of treatment processes, several plant configurations and scenarios. Some of the available models and data records, representing real Wastewater Treatment Plants, can be taken as starting point either for being redesigned or just as simulation models (to be compared with others, for its control system design, etc.). In fact, the software is very flexible and, apart from the first main functionality (Integrated Design), the use of other implemented modules can lead to the integration of various related fields (Simulation, Control System Design, Fault Detection and Diagnosis, Adaptive Control, etc).
Integrated design methodology
In this work, the Integrated Design problem is stated mathematically as a constrained non-linear multi-objective optimization problem, in which economic and control objectives are considered together with some constraints. The solution of the ID problem is obtained following a constrained numerical cost optimization procedure that uses dynamic models and real data records of disturbances together with a set of predefined constraints to evaluate the plant dimensions, the optimal operation points and the control system parameters.
The cost functions include the investment, operation costs, and dynamical indexes. The constraints are selected to ensure that the process variables and some closed loop controllability measures and several closed loop performance criteria lie within specified bounds.
The methodology corresponding to the integrated design step is implemented with the help of a design tool (See Figure 1). The tool facilitates a systematic design process by keeping a record of the design parameters together with the design objectives (cost functions, performance indexes, constraints, ..) and the alternatives that were generated to satisfy those objectives. The objective functions are defined in an economical and environmental context that restricts the amount of potential solutions from the beginning of the project.
The methodology for the integrated design is subdivided in several blocks:
1. Initial plant information: where all the information necessary is defined to carry out the WWTP design. It includes wastewater and control system characterisation (plant and control type, models, plant load,…)
2. Definition of design objectives, performance and controllability criteria and constraints: where the preliminary goals and the corresponding measurement criteria are proposed and classified according to different categories (environmental, economic, operational, control..).
3. Optimization procedure: where the optimization algorithm and a dynamical simulation cooperate to complete the whole design of the facility.
4. Validation of results: where the optimal plant can be simulated, several criteria evaluated, and comparison with other plants can be carried out.
The computer based tool
The objective of the application of an optimization procedure is to find values of the parameters describing the plant dimension, and to find values of the parameters describing the control strategy so that minimum possible adverse impacts of the strategy are applied to the environment. Solutions resulting not only in minimum impacts but also those leading to less detrimental impacts than the currently applied strategies minimizing a cost functions.
When tackling the integrated design mathematical problem, specific features of the process (non-linearities, different sensitivity for plant parameters and controller parameters, etc.) increase the complexity of the problem. For this reason, when solving closed loop integrated design, we used a methodology consisting of an iterative two steps approach. The first step performs the plant design optimizing f1, and the second step the controller tuning optimizing f2. At every step, plant or controller parameters obtained are used as constant values for the following optimization step. The loop ends when a convergence criterion is reached. (
An important issue is that within the optimization procedure a dynamical simulation can be carried out as a means of computing the objective function or any other dynamical performance indexes (as the ISE) including real data records as disturbances. The control strategy is applied during the simulation. The tool has the strategy parameters as input ( controller type, control parameters, identification parameters, initial values, process restrictions…etc) and the value of objective function, plant dimension, and control strategy parameters as output.
This tool has been developed as a prototype tool for the Simulation, Integrated Design, and Control System Design Process for activated sludge process, beside the Integrated Design module, the tool contains a simulation module that able the user to simulate the most common fault occurs in the waste water treatment plants, and a Control System Design Module for the design of Wastewater Plants control loops.
The tool contains considerable number of user case like Plant Design, Integrated Design (Plants + controller), various types of controller (PID, MPC....etc),different optimization algorithm, various cost function formulate, simulation with/without faults, control system design (PID, MBPC, GMV…etc).
The package is an integrated tool for optimization system which integrates programs for the optimization and predictive control of WWTP (Activated Sludge Processes), simulators (SIMULINK), computer aided control system design (Matlab, toolboxes) and user interface (GUIDE toolbox).
References
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See the full pdf manuscript of the abstract.
Presented Thursday 20, 09:37 to 09:55, in session Tools Integration - CAPE Methods & Tools (T4-10).
