Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model

نویسندگانHamid Falaghi,Mahdi Farhadi,Amir Mosavi,Abouzar Estebsari
نشریهElectronics
شماره صفحات1143-1143
شماره سریال9
شماره مجلد7
نوع مقالهFull Paper
تاریخ انتشار2020
رتبه نشریهISI
نوع نشریهچاپی
کشور محل چاپسوئیس
نمایه نشریهISI،JCR،Scopus

چکیده مقاله

One of the essential aspects of power system planning is generation expansion planning (GEP). The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants. This paper proposes a method based on a genetic algorithm (GA) for GEP in the presence of wind power plants. Since it is desirable to integrate the maximum possible wind power production in GEP, the constraints for incorporating different levels of wind energy in power generation are investigated comprehensively. This will allow the maximum reasonable amount of wind penetration in the network to be obtained. Besides, due to the existence of different wind regimes, the penetration of strong and weak wind on GEP is assessed. The results show that the maximum utilization of wind power generation capacity could increase the exploitation of more robust wind regimes. Considering the growth of the wind farm industry and the cost reduction for building wind power plants, the sensitivity of GEP to the variations of this cost is investigated. The results further indicate that for a 10% reduction in the initial investment cost of wind power plants, the proposed model estimates that the overall cost will be minimized.

لینک ثابت مقاله

tags: generation expansion planning; wind power; genetic algorithm; least-cost generation expansion planning; machine learning; soft computing; mathematical programming; renewable energies; artificial intelligence; electronics; power plant; power station