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Physical and hybrid methods comparison for the day ahead PV output power forecast

Renewable energy, 2017-12, Vol.113, p.11-21

2017

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Comparison of different physical models for PV power output prediction

Solar energy, 2015-09, Vol.119, p.83-99

2015

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Editorial for Special Issue: “Feature Papers of Forecasting 2021”

Forecasting, 2022-03, Vol.4 (1), p.335-337

Leva, Sonia

2022

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Editorial for Special Issue: “Feature Papers of Forecasting”

Forecasting, 2021-03, Vol.3 (1), p.135-137

Leva, Sonia

2021

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Advanced Methods for Photovoltaic Output Power Forecasting: A Review

Applied sciences, 2020-01, Vol.10 (2), p.487

2020

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A Physical Hybrid Artificial Neural Network for Short Term Forecasting of PV Plant Power Output

Energies (Basel), 2015-02, Vol.8 (2), p.1138-1153

2015

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Innovative Automated Control System for PV Fields Inspection and Remote Control

IEEE transactions on industrial electronics (1982), 2015-11, Vol.62 (11), p.7287-7296

2015

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Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques

Energies (Basel), 2019-04, Vol.12 (9), p.1621

2019

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Recycling c-Si PV Modules: A Review, a Proposed Energy Model and a Manufacturing Comparison

Energies (Basel), 2022-11, Vol.15 (22), p.8419

2022

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Light Unmanned Aerial Vehicles (UAVs) for Cooperative Inspection of PV Plants

IEEE journal of photovoltaics, 2014-07, Vol.4 (4), p.1107-1113

2014

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Energy Resilience in Telecommunication Networks: A Comprehensive Review of Strategies and Challenges

Energies (Basel), 2023-09, Vol.16 (18), p.6633

2023

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User Behaviour Clustering Based Method for EV Charging Forecast

IEEE access, 2023-01, Vol.11, p.1-1

2023

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Transfer Learning Techniques for the Lithium-Ion Battery State of Charge Estimation

IEEE access, 2024, Vol.12, p.993-1004

2024

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Power Quality and Harmonic Analysis of End User Devices

Energies (Basel), 2012-12, Vol.5 (12), p.5453-5466

2012

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Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries: An Overview

Forecasting, 2023-09, Vol.5 (3), p.576-599

2023

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A Selective Ensemble Approach for Accuracy Improvement and Computational Load Reduction in ANN-Based PV Power Forecasting

IEEE access, 2022, Vol.10, p.32900-32911

2022

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Deep Learning-Based Predictive Control for Optimal Battery Management in Microgrids

IEEE access, 2024, Vol.12, p.141580-141593

2024

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Outdoor Performance of Organic Photovoltaics: Comparative Analysis

Energies (Basel), 2022-03, Vol.15 (5), p.1620

2022

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Hybrid Predictive Models for Accurate Forecasting in PV Systems

Energies (Basel), 2013-04, Vol.6 (4), p.1918-1929

2013

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Comparison of Training Approaches for Photovoltaic Forecasts by Means of Machine Learning

Applied sciences, 2018-02, Vol.8 (2), p.228

2018

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ANN Sizing Procedure for the Day-Ahead Output Power Forecast of a PV Plant

Applied sciences, 2017-06, Vol.7 (6), p.622

2017

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Development and experimental validation of hierarchical energy management system based on stochastic model predictive control for Off-grid Microgrids

Advances in applied energy, 2021-05, Vol.2, p.100028, Article 100028

2021

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Joint State of Charge and State of Health Estimation Using Bidirectional LSTM and Bayesian Hyperparameter Optimization

IEEE access, 2024, Vol.12, p.80244-80254

2024

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Computational Intelligence Techniques Applied to the Day Ahead PV Output Power Forecast: PHANN, SNO and Mixed

Energies (Basel), 2018-06, Vol.11 (6), p.1487

2018

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Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies

Forecasting, 2023-03, Vol.5 (1), p.297-314

2023

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Physical and hybrid methods comparison for the day ahead PV output power forecast

Comparison of different physical models for PV power output prediction

Editorial for Special Issue: “Feature Papers of Forecasting 2021”

Editorial for Special Issue: “Feature Papers of Forecasting”

Advanced Methods for Photovoltaic Output Power Forecasting: A Review

A Physical Hybrid Artificial Neural Network for Short Term Forecasting of PV Plant Power Output

Innovative Automated Control System for PV Fields Inspection and Remote Control

Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques

Recycling c-Si PV Modules: A Review, a Proposed Energy Model and a Manufacturing Comparison

Light Unmanned Aerial Vehicles (UAVs) for Cooperative Inspection of PV Plants

Energy Resilience in Telecommunication Networks: A Comprehensive Review of Strategies and Challenges

User Behaviour Clustering Based Method for EV Charging Forecast

Transfer Learning Techniques for the Lithium-Ion Battery State of Charge Estimation

Power Quality and Harmonic Analysis of End User Devices

Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries: An Overview

A Selective Ensemble Approach for Accuracy Improvement and Computational Load Reduction in ANN-Based PV Power Forecasting

Deep Learning-Based Predictive Control for Optimal Battery Management in Microgrids

Outdoor Performance of Organic Photovoltaics: Comparative Analysis

Hybrid Predictive Models for Accurate Forecasting in PV Systems

Comparison of Training Approaches for Photovoltaic Forecasts by Means of Machine Learning

ANN Sizing Procedure for the Day-Ahead Output Power Forecast of a PV Plant

Development and experimental validation of hierarchical energy management system based on stochastic model predictive control for Off-grid Microgrids

Joint State of Charge and State of Health Estimation Using Bidirectional LSTM and Bayesian Hyperparameter Optimization

Computational Intelligence Techniques Applied to the Day Ahead PV Output Power Forecast: PHANN, SNO and Mixed

Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies

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