کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7936615 | 1513082 | 2016 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
On recent advances in PV output power forecast
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کلمات کلیدی
MBENARNARXConcentrated PVARIMACPVNARMAXLMSMLPIEAARMAXMAPEARIMAXARMAANNInternational energy agency - آژانس انرژی بین المللیGenetic algorithm - الگوریتم ژنتیکback propagation - انتشار عقبindependent system operator - اپراتور سیستم مستقلISO - ایزوdHI - بزMAE - بلهGlobal horizontal irradiance - تابش افقی جهانیDiffuse horizontal irradiance - تابش افقی متنوعdirect normal irradiance - تابش نور مستقیمAir mass - جرم هواMean bias error - خطای اشتباه متوسطauto-regressive - خودکار رگرسیونDNI - روزhybrid system - سیستم ترکیبیArtificial Neural Network - شبکه عصبی مصنوعیGHI - ضبطMoving average - متوسط حرکتMean Absolute Error - میانگین خطا مطلقAuto-regressive moving average - میانگین متحرک خودکار رگرسیونAuto-regressive integrated moving average - میانگین متحرک متحرک خودکار رگرسیونartificial intelligence - هوش مصنوعیDemand response - پاسخ تقاضاMulti-Layer Perceptron - چند لایه ی Perceptron
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
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چکیده انگلیسی
In last decade, the higher penetration of renewable energy resources (RES) in energy market was encouraged by implementing the energy polices in several developed and developing countries due to increasing environmental concerns. Among wide range of RES, Photovoltaic (PV) electricity generation get higher attention by researcher, energy policy makers and power production companies due to its economic and environmental benefits. Therefore, a large PV penetration was observed in energy market with rapid growth in the last decade. The PV output power is highly uncertain due to several meteorological factors such as temperature, wind speed, cloud cover, atmospheric aerosol levels and humidity level. The inherent variability of PV output power creates different issues directly or indirectly for power grid such as power system control and reliability, reserves cost, dispatchable and ancillary generation, grid integration and power planning. Therefore, there is need to accurately forecast the PV output over the spectrum of forecast horizon at different chronological scales. In this paper, a comprehensive and systematic review of PV output power forecast models were provided. This review covers the different factors affecting PV forecast, PV output power profile and performance matrices to evaluate the forecast model. The critical analysis regressive and artificial intelligence based forecast models are also presented. In addition, the potential benefits of hybrid techniques for PV forecast models are also thoroughly discussed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Solar Energy - Volume 136, 15 October 2016, Pages 125-144
Journal: Solar Energy - Volume 136, 15 October 2016, Pages 125-144
نویسندگان
Muhammad Qamar Raza, Mithulananthan Nadarajah, Chandima Ekanayake,