Multi-Plant Photovoltaic Energy Forecasting Challenge: Second Place Solution
نویسندگان
چکیده
This paper presents the approach we took to solve the MultiPlant Photovoltaic Energy Forecasting Challenge for ECML/PKDD 2017. The approach we took granted us the second place of that challenge. In the paper, we will present how we moved from standard regression techniques to simple function optimization to tackle the challenge.
منابع مشابه
Multi-Plant Photovoltaic Energy Forecasting Challenge with Regression Tree Ensembles and Hourly Average Forecasts
In this paper, we present the winning solution to the ECMLPKDD Discovery Challenge 2017 on Multi-Plant Photovoltaic (PV) Energy Forecasting. The goal of the challenge is to utilize the historic data of three different PV plants in Italy regarding meteorological conditions and production in order to forecast their energy production. A major problem is that the data contains many missing value fo...
متن کاملNeuro-fuzzy short-term forecasting model for PV plants optimized with genetic algorithm
This paper presents a short-term forecasting model designed to forecast the hourly power production in a grid-connected photovoltaic plant. The model is based on neuro-fuzzy systems optimized with the use of a genetic algorithm. The model uses as inputs forecasted weather variables obtained with a meso-scale numerical weather prediction model. The model was applied to forecast the hourly produc...
متن کاملBayesian Based Neural Network Model for Solar Photovoltaic Power Forecasting
Solar photovoltaic power (PV) generation has increased constantly in several countries in the last ten years becoming an important component of a sustainable solution of the energy problem. In this paper, a methodology to 24-hour or 48-hour photovoltaic power forecasting based on a Neural Network, trained in a Bayesian framework, is proposed. More specifically, an multi-ahead prediction Multi-L...
متن کاملFinding Relevant Multivariate Models for Multi-plant Photovoltaic Energy Forecasting
Forecasting the photovoltaic energy power is useful for optimizing and controling the system. It aims to predict the power production based on internal and external variables. This problem is very similar to the one of multiple time series forecasting problem. With the presence of multiple predictor variables, not all of them will equally contribute to the prediction. The goal is, given a set o...
متن کاملB Jency Paulin and E Praynlin: Solar Photovoltaic Output Power Forecasting Using Back Propagation Neural Network
Solar Energy is an important renewable and unlimited source of energy. Solar photovoltaic power forecasting, is an estimation of the expected power production, that help the grid operators to better manage the electric balance between power demand and supply. Neural network is a computational model that can predict new outcomes from past trends. The artificial neural network is used for photovo...
متن کامل