Integrating renewable energy and plug-in electric vehicles into security constrained unit commitment for hybrid power systems

被引:2
|
作者
Dhawale, Pravin G. [1 ,2 ]
Kamboj, Vikram Kumar [1 ,3 ,4 ]
Bath, S. K. [5 ]
Raboaca, Maria Simona [6 ]
Filote, Constantin [7 ]
机构
[1] Lovely Profess Univ, Dept Elect & Elect Engn, Phagwara, Punjab, India
[2] Sanjay Ghodawat Univ, Kolhapur, Maharashtra, India
[3] Univ Calgary, Schulich Sch Engn, Calgary, AB, Canada
[4] Mt Royal Univ, Bissett Sch Business, Calgary, AB, Canada
[5] Maharaja Ranjit Singh Punjab Tech Univ, Bathinda, India
[6] Natl Res & Dev Inst Cryogen & Isotop Technol, ICSI Energy Dept, Ramnicu Valcea 240050, Romania
[7] Stefan Cel Mare Univ Suceava, Fac Elect Engn & Comp Sci, Suceava, Romania
关键词
Security constrained unit commitment problem; (SCUCP); Optimization; Benchmark functions; CAOA; Renewable energy; Electric vehicle; Reliability; GENERATION; OPERATION; WIND;
D O I
10.1016/j.egyr.2024.01.027
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Nowadays, the demand for power supply is increasing day by day due to industrialization, population growth, and civilization. Therefore, it is crucial to meet this rising demand by increasing electrical power generation while simultaneously taking care of the environment. This paper proposes a system in which renewable power generation is integrated with conventional and plug-electric vehicles in an effective manner to fulfill the demand for power utilization. The proposed system is tested with unimodal, multimodal, and fixed dimensions benchmark functions for 10-, 20-, 40-, and 100-unit systems using chaotic arithmetic optimization algorithms for the combination of renewable and plug-in electric vehicles to minimize generation costs. The convergence curve shows that the proposed system is effective as compared with the other methods. This study is helpful for scheduling the power generation effectively and at the same time taking care of security constraints and unit commitment problems associated with the system. The main contribution of this paper is testing the results for 10, 20, 40, and 100-unit systems and minimizing the operating cost from $563,427.8 to $547,620.4 for 10 units, $1123,401 to $529,223.7 for 20 units, $2246,014 to $2236,352 for 40 units, and $751,848.665 to $751,778.553 for 100 units using the proposed system. The percentage cost saving is 2.80%, 2.18%, 0.43%, and 0.0094% for 10-, 20-, 40-, and 100-unit systems respectively. The study examines parameters such as mean, median, standard deviation, finest value, power demand, scheduled units, and convergence curve. The results presented in the tables prove that the proposed system is superior to the existing ones. This can result in enhanced power system reliability, reduced emissions, and cost savings.
引用
收藏
页码:2035 / 2048
页数:14
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