关键词:

光伏系统可持续评价, 粒计算, 区间二型模糊集, 随机多准则可接受度分析, 自适应粒子群算法

Abstract:

In response to the practical issue of how to assess the photovoltaic(PV) systems from multi-perspectives and assist the green and low-carbon development of China’s PV industry under the background of “carbon peak and carbon neutrality”, a data-driven decision-making model for PV systems is proposed under the dimension of sustainable development assessment. First, the comprehensive assessment criteria system of PV system is established based on the sustainable assessment dimension. Next, to address the uncertainty and volatility in the performance level of PV systems, interval-based granules, and interval type-2 fuzzy sets (IT2FSs) are constructed to quantize the information. Then, to address the preferences of unknown weights of PV system evaluation criteria, the Monte Carlo method is used to generate criteria weight space, and the stochastic multi-criteria acceptability analysis(SMAA) is applied to acquire the criteria weights vector. Afterwards, the adaptive particle swarm optimization(APSO) algorithm is arranged to find the optimal PV system and obtain the ranking result. Finally, the feasibility and effectiveness of this model are verified by a real-world PV systems case.

Key words:

sustainability assessment of photovoltaic (PV) system, granular computing, interval type-2 fuzzy set (IT2FSs), stochastic multi-criteria acceptability analysis (SMAA), adaptive particle swarm optimization (APSO) algorithm