关键词: 实时电价, 碳交易, 车辆路径, 光伏发电, 储能

Abstract: As an industry that is highly dependent on electricity and fuel, cold chain logistics faces a significant carbon emission challenge that cannot be overlooked. The consumption of these resources not only escalates operating costs but also exacerbates environmental degradation, posing a dual threat to the long-term viability of businesses and the stability of the global climate system. Thus, promoting the use of new energy logistics vehicles and renewable energy sources emerges as a crucial strategy not only to curtail carbon emissions and ease environmental pressure but also to foster a symbiotic enhancement of corporate economic gains and environmental health. This proactive approach is vital for forging a path towards sustainable industrial practices that benefit both the economy and the environment.
To rigorously investigate the potential within this sector, this study specifically targets cold chain logistics centers that are equipped with advanced “photovoltaic-energy storage-charging integration” system. The system is designed to offer clean and sustainable energy for new energy logistics vehicles, thereby significantly reducing carbon emissions. The introduction of such “photovoltaic-energy storage-charging integrated” system has undoubtedly revitalized the cold chain logistics industry and opened up new avenues for research and optimization that could lead to financial condition and environment improvements.
In this comprehensive study, the impacts of carbon trading prices and real-time electricity prices on the operations of cold chain logistics are thoroughly assessed. These pricing factors are crucial not only for their direct influence on the economic costs borne by enterprises but also for their role in shaping the deployment and operational strategies of “photovoltaic-energy storage-charging” facilities. The intricate dynamic relationships among photovoltaic installations, energy storage equipment, new energy logistics vehicle charging stations and external power grids are studied in depth. The purpose of the study is to optimize the management of these elements to maximize revenue from electricity sales while minimizing the economic costs associated with their operation. To this end, a mixed integer optimization model is constructed that combines the key aspects of cold chain logistics vehicle route optimization with “photovoltaic-energy storage-charging” energy management. This model seeks to establish an optimal operational framework that not only meets the logistical demands of transporting temperature-sensitive goods but also leverages renewable energy to its fullest potential to minimize carbon emission. In order to solve this complex model, the MOEA/D-IEpsilon algorithm is designed. This improved algorithm is capable of exploring a wider array of feasible solutions in large-scale, multi-decision scenarios compared to the traditional MOEA/D algorithm, thereby enhancing both the quantity and quality of potential solutions.
The efficacy of this model and algorithm is corroborated through a detailed case study involving the tertiary cold chain operations of Company M in Jiangsu Province. The findings reveal that: (1)it is more economical for new energy logistics vehicles to be charged between 11∶00 and 17∶00; (2)by strategically planning vehicle routes and managing the charging behaviors of new energy logistics vehicles, it is possible to significantly reduce the economic costs associated with cold chain logistics while simultaneously boosting electricity sales revenue; (3)cold chain logistics companies should make full use of the site for photovoltaic power generation and give priority to “self-use”; (4)energy storage facilities should be charged when the electricity price is low and discharged when the electricity price is high to reduce economic costs.

Key words: real-time electricity prices, carbon trading, vehicle routing, photovoltaic power generation, energy storage