دورية أكاديمية

Power Prediction and Technoeconomic Analysis of a Solar PV Power Plant by MLP-ABC and COMFAR III, considering Cloudy Weather Conditions

التفاصيل البيبلوغرافية
العنوان: Power Prediction and Technoeconomic Analysis of a Solar PV Power Plant by MLP-ABC and COMFAR III, considering Cloudy Weather Conditions
المؤلفون: M. Khademi, M. Moadel, A. Khosravi
المصدر: International Journal of Chemical Engineering, Vol 2016 (2016)
بيانات النشر: Wiley, 2016.
سنة النشر: 2016
المجموعة: LCC:Chemical engineering
مصطلحات موضوعية: Chemical engineering, TP155-156
الوصف: The prediction of power generated by photovoltaic (PV) panels in different climates is of great importance. The aim of this paper is to predict the output power of a 3.2 kW PV power plant using the MLP-ABC (multilayer perceptron-artificial bee colony) algorithm. Experimental data (ambient temperature, solar radiation, and relative humidity) was gathered at five-minute intervals from Tehran University’s PV Power Plant from September 22nd, 2012, to January 14th, 2013. Following data validation, 10665 data sets, equivalent to 35 days, were used in the analysis. The output power was predicted using the MLP-ABC algorithm with the mean absolute percentage error (MAPE), the mean bias error (MBE), and correlation coefficient (R2), of 3.7, 3.1, and 94.7%, respectively. The optimized configuration of the network consisted of two hidden layers. The first layer had four neurons and the second had two neurons. A detailed economic analysis is also presented for sunny and cloudy weather conditions using COMFAR III software. A detailed cost analysis indicated that the total investment’s payback period would be 3.83 years in sunny periods and 4.08 years in cloudy periods. The results showed that the solar PV power plant is feasible from an economic point of view in both cloudy and sunny weather conditions.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1687-806X
1687-8078
Relation: https://doaj.org/toc/1687-806X; https://doaj.org/toc/1687-8078
DOI: 10.1155/2016/1031943
URL الوصول: https://doaj.org/article/2c89d716d9cf4a8cacf54e35e1655abf
رقم الأكسشن: edsdoj.2c89d716d9cf4a8cacf54e35e1655abf
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1687806X
16878078
DOI:10.1155/2016/1031943