Application of Artificial Neural Networks and Fuzzy Logic Methods for Short-Term Load Forecasting of the Western Libyan Electric Network

Domaine:

environment and energy

Type de record:

paper

Créateur:

HigAbdOmaHig

Éditeur:

Lib

Hôte:

This research paper investigates the application of artificial neural networks (ANNs) and fuzzy logic methods for short-term load forecasting in the Western Libyan Electric Network. Historical hourly load data collected during the year 2023 by the General Electricity Company of Libya (GECOL). The study aims to develop accurate and reliable load forecasting models to support efficient grid operation and resource planning. Historical load data and meteorological variables are utilized to train and evaluate the forecasting models. The performance of the ANNs and fuzzy logic methods is compared, and the suitability of each approach for load forecasting in the Western Libyan Electric Network is assessed. The results demonstrate the effectiveness of both ANNs and fuzzy logic methods in short-term load forecasting, providing valuable insights for electricity providers and policymakers in the region. Keywords: neural' networks, fuzzy logic, load forecasting

Visit

doi.org

Similaires

A Fuzzy Logic Model for Short-Term Load Forecasting in the Libyan Power NetworkComparative Application of Artificial Neural Networks and ANFIS Techniques for Short-Term Load Forecasting in the Western Libyan Power GridInterval Type-2 Fuzzy Neural Networks for Short Term Electric Load Forecasting: A Comparative StudyUse of Artificial Neural Networks for Short-Term Electricity Load Forecasting of Kenya National Grid Power SystemShort-term electric load forecasting in uncertain domain: A fuzzy decision tree approachShort-Term Load Forecasting Based on CNN and LSTM Deep Neural Networks

A Fuzzy Logic Model for Short-Term Load Forecasting in the Libyan Power Network

Short-term load forecasting is an essential system for predicting electricity demand, with a lead ti

Comparative Application of Artificial Neural Networks and ANFIS Techniques for Short-Term Load Forecasting in the Western Libyan Power Grid

The stability and economic efficiency of modern power systems rely profoundly o

Interval Type-2 Fuzzy Neural Networks for Short Term Electric Load Forecasting: A Comparative Study

This paper focuses on the study of short term load forecasting (STELF) using interval Type-2 Fuzzy L

Use of Artificial Neural Networks for Short-Term Electricity Load Forecasting of Kenya National Grid Power System

Short-term electric load forecasting in uncertain domain: A fuzzy decision tree approach

The objective of the research reported in this paper is the development of a model for shor

Short-Term Load Forecasting Based on CNN and LSTM Deep Neural Networks

International audience In the coming years, the world will witness a global transitio