Overhead lines Dynamic Line rating based on probabilistic day-ahead forecasting and risk assessment

Dynamic Line Rating Day-ahead Forecasts – Cost Benefit Based Selection of the Optimal Quantile

Dynamic Line Rating (DLR) is a promising field of research aiming to help network operators face challenges, such as increased penetration of renewable energies and peak electricity demand. Research on realtime overhead line ampacity estimation is currently advanced and, in the last few years, research has started to address medium-term DLR forecasting. The focus is on probabilistic forecasts, ...

Day-Ahead Solar Forecasting Based on Multi-level Solar Measurements

The growing proliferation in solar deployment, especially at distribution level, has made the case for power system operators to develop more accurate solar forecasting models. This paper proposes a solar photovoltaic (PV) generation forecasting model based on multi-level solar measurements and utilizing a nonlinear autoregressive with exogenous input (NARX) model to improve the training and ac...

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...

One Day Ahead Stream Flow Forecasting

A Hybrid Artificial Neural Network and VEPSO based on Day-ahead Price Forecasting of Electricity Markets

In this paper a new Hybrid technique of Artificial Neural Network (ANN) and Vector Evaluated Particle Swarm Optimization (VEPSO) is presented as a forecasting strategy for day-ahead price of electricity market. The proposed technique the proposed intelligent technique is applied to weights and bias of ANN to improve the learning capability through the minimum error. A comprehensive comparative ...