Prediction and management of solar energy to power electrochemical processes for the treatment of wastewater effluents

Abstract A highly versatile software tool able to predict and manage the solar power coming from photovoltaic panels and to assess the environmental remediation of wastewater effluents has been developed. The prediction software tool is made up of four modules. The first one predicts the solar radiation by a phenomenological model. Secondly, an energy optimization algorithm manages the solar power towards the third and fourth modules, an environmental remediation treatment (electrooxidation) and an energy storage system (redox flow battery), respectively. The software tool is aimed to the best solar power management to obtain the highest remediation treatment. Results shows a daily solar radiation prediction with a high accuracy, attaining correlation coefficients of 0.89. Furthermore, the prediction of the removal of an organochlorinated compound from a wastewater effluent at different time of the year was studied. Different percentages of the total solar power are sent directly to the electrooxidation reactor and to the redox flow battery. At non-solar production hours, the electrooxidation reactor is powered by the redox flow battery in order to exploit the total solar power produced. The results show that, the higher the solar radiation, the higher the power percentage that must be directly sent to the electrooxidation treatment in order to attain the best energy management and the higher remediation. Thus, an 82.5% of the total solar power must be sent to the electrooxidation treatment in summer days in contrast to the 25% that have to be powered in winter days to attain the highest removal of pollutant. Consequently, it is important to evaluate the connection between devices to get the best green energy management and the lower energy losses.