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Conference Paper Multi-Site Photovoltaic Power Generation Forecasts based on Deep-learning Algorithm
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Authors
Jeong-In Lee, Il-Woo Lee, Sang-Ha Kim
Issue Date
2017-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2017, pp.1119-1121
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC.2017.8190872
Project Code
17ZH1400, Development of Energy Sharing Networking for Zero-Energy Community, Lee Il Woo
Abstract
This paper presents the multi-site photovoltaic (PV) power generation forecast using the deep-learning algorithms. South Korea PV power generation is the most popular among renewable energy sources as government policy. Form of PV power business is small scale which need to forecast the generation of energy. This paper present the forecast model for multi-site PV power plant using deep-learning algorithm connected with renewable energy management system.
KSP Keywords
Energy management system, Forecast model, Government policy, Multi-site, PV power plant, Photovoltaic (PV) power generation, Power business, Renewable energy management, Renewable energy sources(RES), Small-scale, South Korea