Direct Short-Term Net Load Forecasting Based on Machine Learning Principles for Solar-Integrated Microgrids-Reference-Cited by-同舟云学术

Direct Short-Term Net Load Forecasting Based on Machine Learning Principles for Solar-Integrated Microgrids

Published:2023 Issue: Volume:11 Page:102038-102049
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tziolis Georgios¹^ORCID,Livera Andreas¹^ORCID,Montes-Romero Jesus¹^ORCID,Theocharides Spyros¹^ORCID,Makrides George¹,Georghiou George E.¹

Affiliation:

1. Department of Electrical and Computer Engineering, PV Technology Laboratory, FOSS Research Centre for Sustainable Energy, University of Cyprus, Nicosia, Cyprus

Funder

European Regional Development Fund and the Republic of Cyprus through the Cyprus Research and Innovation Foundation (RIF) in the Framework of the Project ‘‘ELECTRA’’

European Union—NextGenerationEU

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10252050.pdf?arnumber=10252050

Reference53 articles.

1. A Probabilistic Competitive Ensemble Method for Short-Term Photovoltaic Power Forecasting

2. Short-term forecasting of power production in a large-scale photovoltaic plant

3. Machine Learning Based PV Power Generation Forecasting in Alice Springs

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