Artificial intelligence system for the analysis of theoretical and experimental current-voltage characteristics

Digitalization is one of the development priorities in the global scientific community. Digitalization at this point in time means the introduction of artificial intelligence systems in production, science, economics, management, etc. Artificial intelligence systems have shown their effectiveness in various fields of science and technology, including electrochemistry for such tasks as modeling membrane separation, controlling the variable operation of a simple seawater reverse osmosis plant, etc., however, the study and prediction of theoretical and experimental current-voltage characteristics of electromembrane systems by machine learning and artificial intelligence methods is still practically not carried out. The problem of finding connections between the regularities of changes in the current-voltage characteristics (CVC) and the regularities of the process of salt ion transfer in the electrodialysis apparatus (EDA) desalination channel, the classification of theoretical and experimental CVC depending on the values of the input parameters has not yet been set and investigated, and therefore is a new fundamental problem and an actual practical problem.

An Assessment of Renewable Energies in a Seawater Desalination Plant with Reverse Osmosis Membranes

The purpose of our study was to reduce the carbon footprint of seawater desalination plants that use reverse osmosis membranes by introducing on-site renewable energy sources. By using new-generation membranes with a low energy consumption and considering wind and photovoltaic energy sources, it is possible to greatly reduce the carbon footprint of reverse osmosis plants. The objective of this study was to add a renewable energy supply to a desalination plant that uses reverse osmosis technology. During the development of this research study, photovoltaic energy was discarded as a possible source of renewable energy due to the wind conditions in the area in which the reverse osmosis plant was located; hence, the installation of a wind turbine was considered to be the best option. As it was a large-capacity reverse osmosis plant, we decided to divide the entire desalination process into several stages for explanation purposes. The desalination process of the facility consists of several phases: First, the seawater capture process was performed by the intake tower. This water was then transported and stored, before going through a physical and chemical pre-treatment process, whereby the highest possible percentage of impurities and organic material was eliminated in order to prevent the plugging of the reverse osmosis modules. After carrying out the appraisals and calculating the amount of energy that the plant consumed, we determined that 15% of the plant’s energy supply should be renewable, corresponding to 1194 MWh/year. As there was already a wind power installation in the area, we decided to use one of the wind turbines that had already been installed—specifically, an Ecotecnia turbine (20–150) that produced an energy of 1920 MWh /year. This meant that only a single wind turbine was required for this project.

LEACHATE TREATMENT BY REVERSE OSMOSIS METHOD- REGIONAL SANITARY LANDFILL “ZELJKOVAC” CASE STUDY

The purpose of this paper is to elaborate a plan for the leachate treatment at the “Zeljkovac” sanitary landfill in Leskovac city. Different processes occur over time at the landfill. The processes of infiltration and transpiration occur continuously, distributing the humidity and affecting the water balance within the body of the landfill. The landfill body acts as a giant sponge, in which water moves, and from which water can be released - both into groundwater and into the atmosphere in the form of water vapour or as a filtrate at the bottom of the landfill. In this paper, particular attention is given to the kind of waterwhich is actually filtrate from a landfill, often called leachate. The efficiency of the most commonly used methods will be presented, depending on the most prevalent pollutants in leachate. As there are many methods for treating this kind of wastewater, the reverse osmosis method will be presented as one of the most widely used . The technological process of a reverse osmosis plant will be described, as well as the result that shows the output quality of the leachate after the treatment process. The major finding of this paper reflects a clear justification for using this method to achieve the desired efficiency of leachate treatment.

Self-Learning Salp Swarm Optimization Based PID Design of Doha RO Plant

In this investigation, self-learning salp swarm optimization (SLSSO) based proportional- integral-derivative (PID) controllers are proposed for a Doha reverse osmosis desalination plant. Since the Doha reverse osmosis plant (DROP) is interacting with a two-input-two-output (TITO) system, a decoupler is designed to nullify the interaction dynamics. Once the decoupler is designed properly, two PID controllers are tuned for two non-interacting loops by minimizing the integral-square-error (ISE). The ISEs for two loops are obtained in terms of alpha and beta parameters to simplify the simulation. Thus designed ISEs are minimized using SLSSO algorithm. In order to show the effectiveness of the proposed algorithm, the controller tuning is also accomplished using some state-of-the-art algorithms. Further, statistical analysis is presented to prove the effectiveness of SLSSO. In addition, the time domain specifications are presented for different test cases. The step responses are also shown for fixed and variable reference inputs for two loops. The quantitative and qualitative results presented show the effectiveness of SLSSO for the DROP system.