The study presents a method for optimising the energy costs of a desalination plant by managing the working pressure according to variable electricity tariffs. A mathematical model was established that describes the relationship between desalinated water flow, brine pressure and pump power consumption, allowing the formulation of an optimisation strategy based on the allocation of loads in the periods of lowest energy cost. Based on these models, an algorithm was designed that adjusts the operation of the plant based on the hourly structure of the electricity tariffs, maximising the efficiency of the system. The results obtained show a significant reduction in operating costs, with a strong correlation between the lowest tariff times and the highest working pressure. It was verified that the algorithm was able to shift most of the energy consumption to the most economical hours, minimising activity in high-cost periods. Despite the variability in daily savings, the strategy proved to be effective in most cases, suggesting opportunities to improve the operational flexibility of the process.

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A Straigforward Method for the Optimisation of the Electricity Operating Cost of a Water Desalination Plant Under a Variable Tariff

  • Deivis Avila,
  • Yanelys Cuba Arana,
  • Ramón Quiza,
  • Graciliano N. Marichal

摘要

The study presents a method for optimising the energy costs of a desalination plant by managing the working pressure according to variable electricity tariffs. A mathematical model was established that describes the relationship between desalinated water flow, brine pressure and pump power consumption, allowing the formulation of an optimisation strategy based on the allocation of loads in the periods of lowest energy cost. Based on these models, an algorithm was designed that adjusts the operation of the plant based on the hourly structure of the electricity tariffs, maximising the efficiency of the system. The results obtained show a significant reduction in operating costs, with a strong correlation between the lowest tariff times and the highest working pressure. It was verified that the algorithm was able to shift most of the energy consumption to the most economical hours, minimising activity in high-cost periods. Despite the variability in daily savings, the strategy proved to be effective in most cases, suggesting opportunities to improve the operational flexibility of the process.