The government offers subsidies to encourage farmers to adopt PV systems, while farmers determine the optimal PV system type and capacity, as well as the crops to grow throughout the planning horizon. Nevertheless, whether farmers invest in solar energy systems depends on both electricity demand from the optimal crop outputs and the economic profitability of the investment in the PV system. Thus, the effects of the subsidies should be examined explicitly to produce the most profitable SAHF design. This work addresses the effects of PV system subsidy policies on the development of multi-period, electricity-intensive hydroponic crop production systems. Distributed photovoltaic generation is typically less commercially attractive than the alternatives because it entails higher capital costs and longer payback periods. It is essential for the government to offer subsidies for PV system adoptions to bridge its environmental goals and farmers’ commercial success. Among them, the electricity tariff, Feed-in tariff , and the investment co-funding are the most popular tools to induce the individual entities’ installation. Thus, to develop SAHF, the farmers not only needs to make the investment decisions, such as the profitability for adopting the PV system and its optimum capacity, but also need to optimize crops production by making the best use of solar energy. Moreover, the governments also need to evaluate and select the most effective and efficient subsidy schemes to promote the adoption of the PV system with a lower subsidy expenditure.
The following research questions are tried to investigate in this paper: How to optimize the decisions when developing SAHF ? Under what subsidy levels the farmers can be induced by the government? How the performances of the SAHF are affected by the aforementioned subsidy schemes? A few previous studies have explored the impacts of various subsidy policies on the distributed PV adoption and its capacities, like Chen and Song, Zhu, Liao, Xin-gang and Yi-min, Xu and Ma. However, most of them focus on the effectiveness and efficiency of the subsidies and failed to address their impacts from the perspective of individual residents or firms. Furthermore, hydroponic nft channel a quantitative analysis of the effects of the subsidy schemes on SAHS is still absent. To bridge the two aforementioned research gaps, we have developed a quadratic programming model to assess the costs and benefits of installing PV systems in hydroponic farms. We have focused on the incentives in improving electricity tariff , FIT, and ICF subsidy policies. The IET scheme can be regarded as a negative incentive policy that affects entities’ decisions by increasing the current electricity tariff or reducing the existing subsidy to the electricity price. The proposed method considers various factors that impact PV system efficiency, including environmental factors, the type of PV system used, and the electricity demand from the SAHF. A set of experiments was conducted based on the case of SAHF development in Qatar. The results indicate the potential to enhance PV system installation capacity via small governmental subsidy expenditures and suggest an opportunity to develop a profitable SAHF. The contributions of this study are threefold. First, to the best of our knowledge, this is one of the first efforts to evaluate the effects of distributed PV system subsidy schemes on hydroponic farm design and planting decisions. Second, a quadratic programming model is built to determine simultaneously whether a PV system should be installed, which type of PV panel should be selected, and the optimal capacity.
The proposed model can be solved by most commercial solvers using the linearization approach proposed in this study. Third, the minimum effective incentive levels of the three subsidy policies, namely the IET, FIT, and ICF schemes, are identified in the SAHF design. The subsidy conditions that lead to optimum benefits for hydroponic farmers and the government are recognized. Our method helps policymakers to optimize their subsidy policies and therefore reduces subsidy inefficiency. The paper is split into five sections. The research problem is presented in Section 2. In Section 3, we formulate the quadratic programming model for SAHF design and planning under various subsidy schemes. In Section 4, a case study including a set of experiments is performed to provide policy and managerial insights. Finally, in Section 5, we provide the relevant conclusions and suggestions for future research directions.Solar energy is abundant, free, and clean. It has no noise nuisance or contributes any kind of direct pollution to the environment. However, a photovoltaic system is less economically competitive than the alternative electricity sources present in most countries, such as China and Austria. Thus, a wide variety of policy incentives have been used to reduce the costs incurred by end-users. The feed-in tariff scheme is one of the most popular subsidies in the world. A given feed-in tariff is used to boost the installed PV capacity. The FIT is a fixed price level that an energy producer is guaranteed to receive per unit of energy produced when surplus electricity is forwarded to the grid. FITs can be applied to all PV electricity or only to surplus PV electricity. A net-metering system requires a customer’s local utility to purchase energy produced by a customer-sited PV system at the retail price charged to the customer for energy consumption. In contrast, investment co-funding schemes allow investors to receive an initial one-time cash subsidy for a PV system.
Furthermore, the electricity tariff design can also be regarded as a positive or negative incentive for renewable energy adoption. A higher electricity tariff may force the industry to use solar energy to reduce energy costs while a low electricity tariff may constrain the firms’ ambition of renewable energy adoption. For the benefit of both governments and investors, these subsidy schemes should be carefully selected and designed to provide the social and economic benefits of PV system adoption. Several previous studies have been devoted to evaluating the effectiveness of these subsidies on PV energy adoption. Based on a dynamic generation cost simulation, He, Pang established dynamic subsidy models that targeted emission reduction benefits. Dong, Zhou investigated China’s PV capacity using a difference-in-difference framework that considered China’s zonal feed-in tariff policy design and the various changes that it has undergone over time. Bakhshi and Sadeh introduced a dynamic FIT strategy where the FIT is updated based on the prices of retail goods and the Euro exchange rate rather than the retail electricity cost to attract foreign investment in Iranian PV systems. Similarly, Hayat, Shahnia used fuzzy logic to convert the parameters, including the value of electricity, hosting capacity, ambient temperature, and time of day, into a time-varying FIT. Ramírez, Honrubia-Escribano developed an economic model that could evaluate the profitabilities of PV projects that combined FIT and net-metering schemes in European countries. Jia, Du assessed the effectiveness of China’s net-metering subsidies for household distributed PV systems. The results show that net-metering scheme effectiveness is a function of solar radiation and electricity demand. Using a system dynamics simulation, the study performed by Castaneda, Zapata revealed that cutting subsidies to PV users could result in a reduction in the number of PV installations in the UK. The net present value model was used by Firozjaei, Firozjaei to evaluate optimum FIT levels for PV electricity production.Yamamoto examined combinations of FIT schemes and capital subsidies using a microeconomic model. Xu and Ma investigated a nonlinear dynamic PV system to study long-term operation strategies under FIT and tax-rebate regulations.
The results showed the types of PV systems, locations, and minimum tariff prices that should be used to promote PV system adoption. The tripartite evolutionary game model is used by Zhu, Liao to analyze the decisions of the government, banks, and PV investors in China’s distributed PV market. This investigation reveals that a larger capacity PV system is preferred by both the government and banks. Szeląg-Sikora, Sikora conducted a comparative verification analysis of two micro-power installations in Poland and recommend the ranges between 27.20 and 19.10% as the best net subsidy level for the total investment costs. To summarize, most existing studies evaluate subsidy scheme effectiveness based on the installed PV system capacity on a macro level. Only a very limited number of articles, like Yamamoto and Xu and Ma, nft growing system have addressed the subsidy implications regarding distributed PV system adoption and analysis of economic returns. Thus, it is still not clear which policy design is better from the both perspectives of investors and the government, respectively. In addition, although quantitative models have often been used in the field of agriculture to help manage operation and production plans, we are not aware of any published studies that attempt to quantitatively optimize hydroponic farm design and planning. The decisions on the adoption of PV electricity in energy-intensive hydroponic farm provides a novel but untouched research area, where the government designs the subsidy schemes and farmers take advantage of subsidies to optimize the solar-assisted hydroponic farm design and planning. Sensitivity analysis is an indeterminate analysis technique that examines the degree of influence of a certain change on a certain key or a set of key indicators from the perspective of quantitative analysis. The sensitivity analysis tests are often incorporated in the model validation processes to ensure that changing the values of the relevant parameters creates the circumstances in which the strategy should be changed. In order to verify the reliability of the results, it is essential to perform sensitivity analysis to understand how the proposed model responds to changes in the subsidy levels. In this investigation, the ‘one-factor-at-atime’ method is adopted by changing the value of one input factor at a time while keeping the others constant. It not only assistants the policy makers to identify the sensitivity factors whose small change could result in a large change in the performance indicator of the SAHF, but also offers the farmers ‘‘how’’ and ‘‘how much’’ changes in the subsidy levels of the SAHF modify the expected profit and the point how the optimum can be achieved. The investment co-funding scheme can be combined with net metering to improve subsidy effectiveness and efficiency.
The total profit and capacity of a PV system with an available area of 3000 m2 is presented in Fig. 7. Once the subsidy level exceeds 15% of the PV system investment, the total profit and system capacity are higher under net metering than without net metering. The analysis shows that the lowest effective ICF subsidy level is 14.9% regardless of the area available. The subsidy is the main reason for the increase in the total profit in Fig. 7. Additional revenue is gained by selling excess energy via the netmetering system. When the subsidy level increases from 19% to 21%, the type-3 PV system is replaced by a type-2 system for reasons similar to those mentioned in Scenario 2. As a result, the PV system capacities change due to the different energy-conversion efficiencies of the two types of systems . However, further analysis shows that the quantity of electricity generated can be improved by more than 10.6% using a type- 2 PV system. The capacity of the PV system does not vary when the subsidy level is lower than 19% or higher than 21%. With net metering, the vegetable output is stable when the available area is between 600 m2 and 3000 m2 and the subsidy is lower than 25%. However, the total output increases by 12.1% when net metering is not implemented. Fig. 9 shows that cucumbers provide the main contribution to this increase. It is also observed that the quantities of lettuce and pepper grown decline to zero as the subsidy level rises. Without the netmetering system, the ICF subsidy reduces the cost of the electricity consumed by the vegetables, making lettuce and peppers less profitable. The net-metering system allows the farm to sell surplus electricity. Consequently, the cost of the electricity consumed by the vegetables is higher than without net metering. The implementation of PV systems in hydroponic farms creates opportunities for farmers to enhance their profits but poses little effects on the vegetable outputs. When an available area of 600 m2 is considered, 345,200 kWh/year of grid energy can be saved. If all of the energy consumption is satisfied by the PV system, more than 941,000 kWh of clean electricity is generated per year.