4.7 Article

Multi-objective optimization of hybrid energy management system for expressway chargers

期刊

JOURNAL OF ENERGY STORAGE
卷 54, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.est.2022.105233

关键词

Electric vehicles; Energy recovery; Electric charging; Multi-objective optimization; Sensitivity analysis

资金

  1. National Natural Science Foundation of China [51975490]
  2. Science and Technology Projects of Sichuan [2021JDRC0096, 2021JDRC0118, 2021YFSY0059, 2020YFSY0070]

向作者/读者索取更多资源

This study proposes a hybrid energy management approach to increase the use of renewable energy in electric chargers for electric vehicles. Wind turbines and solar power generating modules are used to provide energy, and optimization algorithms are employed to determine the optimal energy cost and grid dependence. The results show that the system can balance energy cost and grid dependence, with a majority of the energy coming from renewable sources.
Fuel combustion is considered a vast energy source for transportation, resulting in the emission of pollutants into the environment. In contrast, electric vehicles (EVs) do not emit direct emissions and protect the environment from hazardous emissions. The rapid and enormous expansion of electric vehicles in China made electric chargers a crucial component of the transportation management system. The present study suggests a hybrid energy management approach to boost the amount of renewable energy going into the electric charger. Wind turbines and solar power generating modules generate energy for electric charging. Excessive energy is stored in energy storage modules and sent to power grid modules, making reverse supply more flexible. Three optimi-zation algorithms, including PSO, GA, and BBO, were employed to find the highest energy cost and power grid dependence with different combinations. The system is considered on-grid and can purchase or sell electricity to maintain energy balance for electric charging devices. The optimization results show that the highest energy cost in a reasonable scheme can reach 0.034546 $/kWh with a share of maximum renewable energy of 96.50 %. Finally, the balance between energy cost and dependency on the power grid can be reached based on the present analysis findings, as the energy cost of the final equilibrium scheme is 0.057475 $/kWh, with a share of 90.82 % in renewable energy. The proposed study can effectively balance energy supply and demand and further support the global agenda of UN-2030 for sustainable development, especially SDG-7.

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