Sustainable development through the balancing of photovoltaic charging facilities and agriculture for energy harvesting

Photovoltaics (PV) and electric vehicles (EVs) provide viable alternatives for powering rural areas and promoting sustainable development. However, solar energy and agricultural land compete with each other, necessitating a balance between energy needs and land preservation. Despite the potential of agricultural PV charging stations, there is a lack of research on their operational models, policies, stakeholder interactions, and feasibility of development. This study combines renewable energy and charging infrastructure subsidy policies, utilizes a public-private partnership model, and employs evolutionary game theory to establish a theoretical framework exploring strategic interactions among energy operators, EV users, and farmers. The model considers the impacts of generation, charging, and agricultural elements, conducting techno-economic research. A case study conducted in Sioux Falls, South Dakota, USA, revealed subsequent findings: (1) The players' evolutionary stable approach ultimately converges to (1,1,1). When renewable energy subsidies are decreased by 50 %, the likelihood of active engagement for energy operators drops to 0, and for farmers, it falls to 0.8. (2) As the usage duration of charging facilities grows by 50 %, energy operators and EVUs make steady progress before reaching 0.2 cycles, but farmers encounter a delay after 0.4 cycles. (3) It is feasible to fulfil the yearly charging requirements for EVs in Sioux Falls and South Dakota using only 7.4 ha and less than 22 ha of agricultural land area, respectively. Investors in Sioux Falls have the potential to earn an annual income of $1.1085 million, generate 7906.07 MWh of electricity, and reduce GHG emissions by 6525.91 tons of CO2-equivalent. Although farmers generate higher annual revenue, it typically takes them over a decade to reach the point of breaking even, and their return on investment is comparatively lower than that of energy operators.