Abstract
Chlorination in drinking water treatment plants (DWTP) is the final process applied to water before it is sent to storage tanks in the supply network for subsequent human consumption. An excessive dosage of chlorine or, conversely, too small a dosage, may breach existing legal regulations on mandatory limits. Furthermore, excessive amounts generate an unnecessary cost in terms of chlorine and, collaterally, problems due to an increase in the maximum permitted amounts of such by-products as trihalomethanes, which are carcinogenic compounds for humans. In DWTP where there is no significant variability in the quality of the water to be treated, a type of control that is proportional to the flow rate in the effluent can have fully satisfactory results. However, in a control strategy applied when there are inherently long delays in the process, variability in the quality of the water to be treated and considerable variations in flow, a proportional type of control does not tend to work and an alternative type is needed. This article presents the strategy and results of a control method that combines a feed-forward system with gain scheduling in a (Proportional-Integral) PI control. The control system design was validated beforehand by simulation and then applied to a real DWTP, producing satisfactory experimental results.
Highlights
Chlorine is the most widely used disinfectant in drinking water treatment plants (DWTP) due to its high efficiency as a germicide and its excellent capacity to eliminate odors and tastes from water destined for human use
It is used in Wastewater Treatment Plants (WWTP) to minimize the public health risks associated with exposure to reclaimed water, where the most important goal is the reduction of pathogens during tertiary treatments [1]
Chlorination processes at output from DWTP have been extensively analyzed in terms of control
Summary
Chlorine is the most widely used disinfectant in drinking water treatment plants (DWTP) due to its high efficiency as a germicide and its excellent capacity to eliminate odors and tastes from water destined for human use. The problem is heightened by the occasional existence of ammonia, which might vary the process gain in a non-linear manner and cause what is called a ‘breakpoint scenario’ In these cases, the measurement of residual chlorine at output, the controlled variable, goes through three states with different behaviors. Reference [15] addresses the problem of chlorination control in supply tanks using an MPC based on the flow to be treated and the system model In this case, the chlorine decay for different flow rates is known, and the controller can predict and anticipate before detecting deviations on the setpoint in the effluent. For DWTP in which variability in the quality of the water to be treated is minimal, this manual strategy may work well The technician in this case sets the dosage and is aided by an output instrument that can make rectifications if it veers from the desired setpoint.
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