Determination of optimal operating conditions for AC-powered electrocoagulation process coupling green additive...

A novel Python-based open-source optimization framework, namely Pyomo (Python optimization modeling objects), alongside a conventional optimization method, RSM (response surface methodology), was utilized to determine the optimal operating conditions of an alternating current-powered electrocoagulation (ACPE) process for nickel removal. In this regard, four mutable operating factors, current density (5-9 mA/cm²), initial nickel concentration (200-400 mg/L), initial pH of the solution (5-9), and electrolysis time (30-60 min), along with a fixed amount of an additional eco-friendly substance, Tartaric Acid (155 mg/L) were considered. Metal removal efficiency (OF₁) and operating costs (OF₂) were monitored and evaluated as objective functions with the aim of maximization and minimization, respectively. Experiments were conducted according to the central composite design (CCD), and validation outcomes established a reasonable agreement between the predicted models and the experimental data. The multi-objective optimization process yielded two sets of 30-optimal-solution obtained through Pyomo and RSM. Accordingly, the proposed solutions by the Pyomo were found to be more flexible and eclectic, supplying the local decision maker(s) with a diverse spectrum of optimal operating conditions. Adding TA was also effective in reducing electrical energy consumption by up to 46%.