This paper presents an optimization approach to the incorporation of electrocoagulation in the design of integrated water networks for oil refineries. A disjunctive programming formulation is developed to minimize the cost of the water-management system while including the characteristics of process water streams, recycle, reuse, and treatment of wastewater streams, performance of candidate technologies, and composition and property constraints for the process units and the environmental discharges. The performance of electrocoagulation was related to temperature pH and the concentration of phenols and sodium chloride. Ancillary units including pH adjustment, reverse osmosis, and heat exchangers were used to support the electrocoagulation unit. Two case studies are presented to show the applicability of the proposed model and the feasibility of using electrocoagulation as part of an integrated water management scheme for oil refineries.

Electricity is becoming one of the main forms of the final energy demand in the world; therefore, energy transition is one of the most important issues to achieve the internationally agreed target to limit global warming below 2 °C. This work addressed the optimal mix of renewable energy technologies to substitute any existing power system. A flexible multiobjective mixed-integer linear programming model was developed that can be adapted to any national power system. The proposed optimization framework considers simultaneously technical operating constraints, availability of renewable energy sources in different places, freshwater consumption as a function of technologies and location characteristics, direct and lifecycle greenhouse gas emissions, and total annual costs. The peninsular electricity system (PES) of Spain was chosen to show the applicability of the model due to the imminent decommission of its coal and nuclear thermal plants and its ambitious CO2 reduction targets. Results show the location, type, capacity, and generation structure of the optimal energy mix with existing and new power plants. The proposed energy transition shows a potential reduction of up to 37.5 and 49.7% in water consumption and greenhouse gas emission, respectively, with respect to the current system.

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This paper presents an optimization approach for designing cogeneration systems using flares and vents under abnormal conditions from different industrial plants. The aim of the proposed approach is to enhance resource conservation by utilizing waste flares and vents to produce power and heat while reducing the negative environmental impact associated with discharging these streams into the atmosphere. A nonlinear optimization model is proposed to determine the optimal design of the cogeneration system that maximizes the net profit of the system. The model addresses the inevitable uncertainties associated with the abnormal situations leading to venting and flaring. A random generations approach based on historical data and a computationally efficient algorithm are introduced to facilitate design under uncertainty and to enable the assessment of different scenarios and solutions with various levels of risk. A case study is presented to show the applicability of the proposed model and the feasibility of using cogeneration systems to mitigate flaring and venting and to reduce the environmental impact and operating costs.