Methodology for Energy Optimization in Wastewater Treatment Plants. Phase II: Reduction of Air Requirements and Redesign of the Biological Aeration Installation

Abstract

Phase I of the proposed energy optimization methodology showed how the selection of best management criteria for the biological aeration process, and the guarantee of its control at the wastewater treatment plant (WWTP) in San Pedro del Pinatar (Murcia, Spain) produced reductions of around 20% in energy consumption by considerably reducing the oxygen needs of the microorganisms in the biological system. This manuscript focused on phase II of this methodology, which describes the tools that can be used to detect and correct deviations in the optimal operating points of the aeration equipment and the intrinsic deficiencies in the installation, in order to achieve optimization of the oxygen needs by the microorganisms and improve the efficiency of their transfer from the gas phase to the liquid phase. The objectives pursued were: (i) to minimize the need for aeration, (ii) to reduce the pressure losses in the installation, (iii) to optimize the air supply pressures to avoid excessive energy consumption for the same airflow, and (iv) to optimize the control strategy for the actual working conditions. The use of flow modeling and simulation techniques, the measurement and calculation of air transfer efficiency through the use of off-gas hoods, and the redesign of the aeration facility at the San Pedro del Pinatar WWTP were crucial, and allowed for reductions in energy consumption in Phase II of more than 20%.

Methodology for Energy Optimization in Wastewater Treatment Plants. Phase III: Implementation of an Integral Control System for the Aeration Stage in the Biological Process of Activated Sludge and the Membrane Biological Reactor

“…-It guarantees energy savings of more than 20% in the aeration process of the AS system, by means of exhaustive control of the nitrification and denitrification processes and by adjusting the higher air demand to the most economical electricity rates. Results are in line with those obtained in Phase II of optimization [9]. -Increased control of the aeration of the MBR system reduces the energy consumption of the plant by more than 9.3%.…”

“…As can be seen in Figure 12, the new configuration of the control system led us to work most of the time at the lowest possible blower operating frequencies. This resulted in improved oxygen transfer and lower air velocities, reducing the pressure drop in the diffusers and pipe network, as already verified in the studies carried out in Phase II of the optimization methodology [9].…”

“…This was largely associated with the aeration of the biological reactors, the pumping and stirring of active sludge and the aeration of the bioreactor membranes necessary to prevent their contamination. This value of specific energy consumption was reduced by around 0.67 kWh/m 3 after the first two phases of optimization of the proposed methodology [8,9] (Figure 3). In the first phase of optimization (Phase I), the oxygen requirements of the microorganisms in the biological system were reduced.…”

“…Oxygen transfer depended largely on the concentration gradient between the oxygen saturation value and the concentration in the reactor itself according to Equation (1). This meant that the lower is the working concentration in the reactor, the higher is the transfer [9]. Therefore, the criteria used to establish the oxygen setpoints in each chamber were to set lower working setpoints in the head-end aerated areas, since it was in this area that the highest oxygen demands and the lowest alpha values (α) or transfer coefficient [43][44][45][46] coincided.…”

“…The first phase of this energy optimization methodology consisted of adjusting the concentration of suspended solids in the liquor mixture in the biological reactor to minimize the oxygen requirements of the microorganisms [4]. The second phase was based on optimizing the operating conditions of the air injection systems and redesigning the installation so that the supply of the necessary oxygen was made as efficiently as possible and the air supply requirements were reduced [9]. The third and final phase of optimization, which is the subject of this article, was the implementation of a new control strategy with the main objective of minimizing the deviations between the target set values and the actual values of the parameters to be controlled, as set in previous phases.…”