Electricity load forecasting by an improved forecast engine for building level consumers

Y Liu, W Wang, N Ghadimi - Energy, 2017 - Elsevier
For optimal power system operation, electrical generation must follow electrical load
demand. So, short term load forecast (STLF) has been proposed by researchers to tackle the …

Small-scale building load forecast based on hybrid forecast engine

M Mohammadi, F Talebpour, E Safaee… - Neural Processing …, 2018 - Springer
Electricity load forecasting plays an important role for optimal power system operation.
Accordingly, short term load forecast (STLF) is also becoming an important task by …

Electricity demand prediction using data driven forecasting scheme: ARIMA and SARIMA for real-time load data of Assam

K Goswami, AB Kandali - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Aim of forecasting electrical load focuses in predicting satisfactorily and accurately the
demand that might increase or decrease in the future. A large number of engineering …

[HTML][HTML] Achieving grid resilience through energy storage and model reference adaptive control for effective active power voltage regulation

A Jarosz - Energy Conversion and Management: X, 2024 - Elsevier
This article presents a comprehensive examination of the utilization of energy storage units
for voltage regulation in grids. Specifically, the focus is on the practical implementation of …

Optimal fractional order PID controller for automatic generation control of two‐area power systems

C Ismayil, RS Kumar, TK Sindhu - International Transactions on …, 2015 - Wiley Online Library
This paper proposes a fractional order PID (FOPID) controller for the supplementary
automatic generation control (AGC) of two area thermal power systems. To establish the …

Computational awareness for smart grid: a review

CW Tsai, A Pelov, MC Chiang, CS Yang… - International journal of …, 2014 - Springer
Smart grid has been an active research area in recent years because almost all the
technologies required to build smart grid are mature enough. It is expected that not only can …

Machine learning-based approach for early diagnosis of breast cancer using biomarkers and gene expression profiles

A Sahu, S Qazi, K Raza, A Singh, S Verma - Computational intelligence in …, 2022 - Springer
Breast cancer is a heterogeneous disease and the most frequent malignancy in women
globally each year. Emerging applications of gene expression profiles are important to …

Evaluation of renewable energy technology based on reliability attributes using hybrid fuzzy dynamic decision-making model

DO Aikhuele, DE Ighravwe, D Akinyele - Technology and Economics of …, 2019 - Springer
Socio-technical and economic attributes consideration are very important during a
renewable energy technology selection for a community. When decision-makers considered …

Yajna and mantra science bringing health and comfort to Indo-Asian public: a healthcare 4.0 approach and computational study

R Rastogi, M Saxena, M Maheshwari, P Garg… - Machine Learning with …, 2020 - Springer
Improving comfort, stress and pollution levels among the fascinating achievements of
modern science and technology has become a major challenge for our well-being. The …

A comparison of several maximum power point tracking algorithms for a photovoltaic power system

A Aifan G. Alsulami, AA Alhussainy… - Frontiers in Energy …, 2024 - frontiersin.org
This paper presents a comparative study between traditional and intelligent Maximum
Power Point Tracking (MPPT) algorithms for Photovoltaic (PV) powered DC Shunt Motors …