The optimal plan selection framework of rail transit photovoltaic power station under probabilistic linguistic environment

Abstract Building the rail transit photovoltaic power station (RTPPS) to improve the utilization rate of renewable energy has become an effective way to reduce carbon emissions. Unlike the photovoltaic power stations built in the wide area, the urban rail transit in the big city must consider the demand of landscape, the nearby utilization of electric energy and the impact of light pollution on residents. Hence selecting a reasonable RTPPS plan is important, but it is still the research gap. There are still some problems encountered in the RTPPS plan selection. First, there is lack of an effective decision index system of RTPPS plan selection; second, the existing decision model cannot effectively balance three kind relationships: ①the expression convenience of decision preference and ability to deal with uncertainty; ② the subjectivity and objectivity of the criteria weights in the linguistic environment; ③ the overall effectiveness and local disadvantages of the RTPPS plan. Therefore, the proposed decision index system is established from five aspects: economic performance, rationality of photovoltaic integrated design, effectiveness of light pollution control, energy efficiency and support degree. Meanwhile, according to the principle of probabilistic linguistic term set, combination weighting method and VIKOR model, the corresponding model was proposed to balance tha above relationships. It has the following characteristics：① it improves the ability to deal with uncertain information without changing the expression habit of expert decision preference; ② The weight of decision criterion not only reflects the subjective intention of decision-makers, but also avoids too subjective decision-making; ③ The local disadvantages of the plan are considered in the final result, so as to ensure that the optimal alternative will not be abandoned because of the local disadvantages. The proposed decision index system and decision model jointly construct the optimal plan selection framework of RTPPS to improve the plan selection rationality. The effectiveness of this framework is proved by a China case study.