Stochastic energy management of large industrial-scale aquaponics considering robust optimization-based demand response program

Large industrial-scale aquaponics systems, which combine industrial water recycling aquaculture technology with soilless culture technology, are innovative and sustainable alternatives for food production in regions with limited agricultural land and water resources. Industrial-scale aquaponics is heavily dependent on fossil fuels and the electricity expenditures account for a high percentage of operating costs. The differentiated operating characteristics of the electrical facility and varying ideal environment conditions of the paired fish and vegetables create challenges when it comes to devising an optimization strategy. By analyzing the flexible characteristics of the dispatchable units, this study proposes a demand response-based load scheduling approach that optimizes the unit operating schemes for cost minimization. Based on the assumptions, the case study exhibits that the optimized operation scheme decreases the energy consumption by 11.73% and 8.49%, and reduces the operating costs by 18.15% and 16.37% for 3 typical summer days and winter days, respectively. The proposed approach was applied to scenarios integrating varying fish species and plant choices to demonstrate the efficiency and effectiveness of the proposed energy-saving technique.