A combined system based on data preprocessing and optimization algorithm for electricity load forecasting

L Gu, J Wang, J Liu - Computers & Industrial Engineering, 2024‏ - Elsevier
Creating steady models for predicting electricity load can enhance the equilibrium between
power supply and demand, a critical factor in advancing precise distribution management …

[HTML][HTML] Multi-model prediction for demand forecast in water distribution networks

R Lopez Farias, V Puig, H Rodriguez Rangel, JJ Flores - Energies, 2018‏ - mdpi.com
This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus
(QMMP+) for demand forecast in water distribution networks. QMMP+ is based on the …

Demand forecasting with integration of time series and regression models in pharmaceutical industry

S İmece, ÖF Beyca - … Journal of Advances in Engineering and Pure …, 2022‏ - dergipark.org.tr
Accurate demand forecasting is crucially important to reduce inventory and backlogging
cost. In this study, we analyze how promos, holiday statements, price changes, stock …

Design of Power Transformer Fault Detection of SCADA Alarm Using Fault Tree Analysis, Smooth Holtz–Winters, and L-BFGS for Smart Utility Control Centers

R Taksana, N Janjamraj, S Romphochai… - IEEE …, 2024‏ - ieeexplore.ieee.org
When a trip occurs, the utility of company-type 115/22 kV loading transformer trips out of the
electrical system, cutting off power to the distribution of a company customer. The outage …

PSGformer: A novel multivariate net load forecasting model for the smart grid

Q Zhang, S Zhou, B Xu, Z Shen, W Chang - Journal of Computational …, 2024‏ - Elsevier
Smart grid intelligently transforms modern power system through the introduction of various
advanced techniques, promoting the growth of distributed renewable energy sources and …

[HTML][HTML] Things2people interaction toward energy savings in shared spaces using BIM

B Mataloto, H Mendes, JC Ferreira - Applied Sciences, 2020‏ - mdpi.com
People in shared building space have an important role in energy consumption because
they can turn on/off equipment and heat/cooling systems. This behaviour can be influenced …

Short-term demand forecast using a bank of neural network models trained using genetic algorithms for the optimal management of drinking water networks

HR Rangel, V Puig, RL Farias… - Journal of …, 2017‏ - iwaponline.com
Efficient management of a drinking water network reduces the economic costs related to
water production and transport (pum**). Model predictive control (MPC) is nowadays a …

Türkiye'de elektrik tüketiminde talep tahmini: zaman serisi ve regresyon analizi ile karşılaştırma

EE Nebati, M Taş, G Ertaş - Avrupa Bilim ve Teknoloji Dergisi, 2021‏ - dergipark.org.tr
Değişen Dünya koşullarında ve artan nüfusa bağlı olarak, Ülkelerin ekonomik ve sosyal
süreçlerinin gelişmesinin en temel ihtiyaçlardan biri, enerjidir. Tüketimin artması sonucu …

[PDF][PDF] HOLT-WINTERS TAHMİNLEME YÖNTEMLERİNİN KARŞILAŞTIRMALI ANALİZİ: TÜRKİYE İŞSİZLİK ORANLARI UYGULAMASI

A Tüzemen, Ç Yıldız - Atatürk Üniversitesi İktisadi ve İdari Bilimler …, 2018‏ - dergipark.org.tr
İşsizlik sorunu modern çağın en büyük problemlerinden biridir. Gelişmekte olan ülkeler
kategorisinde yer alan ülkemiz de bu sorundan oldukça muzdariptir. İşsizlik sorununa kısa …

Peak forecasting for electricity loads in jordan using a weighted combination of feed forward back propagation neural network and holt-winter

AA Sleem, AR Mohammed… - 2022 3rd International …, 2022‏ - ieeexplore.ieee.org
Predicting electrical loads is critical since it requires the preparation of work schedules for
main and minor transformer maintenance operations. This study aims to estimate the …