Decisions on design and planning of solar-assisted hydroponic farms under various subsidy schemes

Due to rapid urbanization in developing countries, it is necessary for respective governments to seek new approaches to providing sustainable fresh food and clean energy supplies. The implementation of photovoltaic (PV) systems in hydroponic farms offers an innovative solution to shortages of energy and fresh food in urban areas. These shortages have become increasingly serious during the Covid-19 lockdown periods. This paper proposes an approach to analyzing the impacts of the PV system subsidy schemes on solar-assisted hydroponic farm (SAHF) design and planning, in terms of the profit and outputs of the SAHF and the effectiveness of the subsidies. The subsidy schemes considered include the improving electricity tariff (IET), feed-in tariff (FIT) scheme, and investment co-funding (ICF) scheme. A quadratic programming model is developed to optimize the type and capacity of the PV system simultaneously. The proposed model can be solved by most commercial solvers using the linearization approach proposed in this study. A case study in Qatar is analyzed and incentive thresholds that promise PV system adoption profitability for SAHFs under IET, full FIT, surplus FIT, and ICF subsidies are identified. The thresholds are 0.0425 $/kWh, 0.0063 $/kWh, 0.027 $/kWh, and 14.90%, respectively. The subsidy conditions that lead to optimum benefits for hydroponic farmers and the government are identified via sensitivity analysis. Our method helps policymakers to optimize subsidy levels and therefore reduces subsidy inefficiency. For hydroponic farmers, it is profitable to take full advantage of the available space to enlarge their PV systems if the surplus electricity can be sold to the grid or other entities.