Design and optimization of photovoltaic system with a week ahead power forecast using autoregressive artificial neural networks-Reference-Cited by-同舟云学术

Design and optimization of photovoltaic system with a week ahead power forecast using autoregressive artificial neural networks

Published:2021-10 Issue: Volume: Page:
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

Mughal Shafqat Nabi,Sood Yog Raj,Jarial R.K.

Publisher

Elsevier BV

Subject

General Medicine

Reference38 articles.

1. IPCC (2014) Climate Change Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, in: Core Writing Team, R.K. Pachauri, L.A. Meyer (Eds.). IPCC, Geneva, Switzerland, 151.

2. Riahi K (2012) In Global Energy Assessment: Toward a Sustainable Future, Chapter 17: Energy Pathways for Sustainable Development, 1205–1305 (Cambridge Univ. Press and IIASA, 2012) http://www.iiasa.ac.at/web/home/research /FlagshipProjects/GlobalEnergyAssessment/GEA_Chapter17_pathways_lowres.pdf

3. The irreversible momentum of clean energy;Obama;Science,2017

4. Empirical evaluation of the stringency and design of renewable portfolio standards;Carley;Nature Energy,2018

5. “Renewable Energy: Scenario and Model of Development”.Appl;Avezova;Sol.,2019

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