Rule extraction and performance estimation by using variable neighborhood  search for solar power plant in Konya

Yusuf UZUN; Muciz ÖZCAN

doi:https://doi.org/10.3906/elk-1901-232

Makale detayları

Rule extraction and performance estimation by using variable neighborhood search for solar power plant in Konya

Yazarlar:

Yusuf UZUN | Muciz ÖZCAN

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2020 Vol.28 Issue 2, pp.635-645

Belge Tipi:

Makale

Yayın Tarihi:

2/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000733193

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

DOI:

https://doi.org/10.3906/elk-1901-232

Özet:

 

The use of renewable energy sources in the production of electricity has become inevitable in order to reduce  the greenhouse gases left in the atmosphere that cause the Earth to warm up. Although countries on a national basis  have implemented a number of policies to support electricity generated from renewable energy sources, investments to  produce electricity without a license on a local basis are not desirable. Those who want to invest medium and small scale  for the most reason expect that this work will be supported by real data. Although the electricity generated by renewable  investments is generated by simulation data, these data are not realistic for such investors. In this study, the climatic  conditions of the power plant of 1 MW installed in Konya and power plant production data are monitored. The artificial  neural network  ANN  can achieve a high value for accuracy, but these values are sometimes complex and unclear. In  the literature, a number of studies have been conducted using different methods to overcome such problems. Real-time  solar power plant  SPP  data were used to determine the feasibility and success of the proposed method. The variable  neighborhood search  VNS  metaheuristic method was used to acquire the optimal values belonging to input vectors,  Gh , which were maximized to the value of the fitness function Fs belonging to output class node s. The results obtained  by the VNS method showed that the proposed method has the potential to produce the correct rules. Generally, energy  investors are curious about the return on their investment. It is very important for energy providers to estimate how  much electricity will be generated from existing solar power plants and accordingly determine the measures they will  take to meet the electricity demand in the future. In this study, the performance estimation value obtained from the  solar power plant depending on the weather conditions was obtained with 95.55% accuracy.

Makale detayları

Rule extraction and performance estimation by using variable neighborhood search for solar power plant in Konya

Yazarlar: Yusuf UZUN | Muciz ÖZCAN

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2020 Vol.28 Issue 2, pp.635-645

Belge Tipi: Makale

Yayın Tarihi: 2/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000733193

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

DOI: https://doi.org/10.3906/elk-1901-232

Sayı

Yazarlar:

Yusuf UZUN | Muciz ÖZCAN

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2020 Vol.28 Issue 2, pp.635-645

Belge Tipi:

Makale

Yayın Tarihi:

2/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000733193

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

DOI:

https://doi.org/10.3906/elk-1901-232