Load forecasting techniques for power system: Research challenges and survey
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …
think tank of power sectors should forecast the future need of electricity with large accuracy …
A comprehensive review of the load forecasting techniques using single and hybrid predictive models
A Al Mamun, M Sohel, N Mohammad… - IEEE …, 2020 - ieeexplore.ieee.org
Load forecasting is a pivotal part of the power utility companies. To provide load-shedding
free and uninterrupted power to the consumer, decision-makers in the utility sector must …
free and uninterrupted power to the consumer, decision-makers in the utility sector must …
Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm
It is hard to predict wind power with high-precision due to its non-stationary and stochastic
nature. The wind power has developed rapidly around the world as a promising renewable …
nature. The wind power has developed rapidly around the world as a promising renewable …
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …
operations due to its strong randomness and volatility. These issues can be resolved via …
Random following ant colony optimization: Continuous and binary variants for global optimization and feature selection
X Zhou, W Gui, AA Heidari, Z Cai, G Liang… - Applied Soft Computing, 2023 - Elsevier
Continuous ant colony optimization was a population-based heuristic search algorithm
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …
Effective long short-term memory with differential evolution algorithm for electricity price prediction
Electric power, as an efficient and clean energy, has considerable importance in industries
and human lives. Electricity price is becoming increasingly crucial for balancing electricity …
and human lives. Electricity price is becoming increasingly crucial for balancing electricity …
Conventional models and artificial intelligence-based models for energy consumption forecasting: A review
Conventional models and artificial intelligence (AI)-based models have been widely applied
for energy consumption forecasting over the past decades. This paper reviews conventional …
for energy consumption forecasting over the past decades. This paper reviews conventional …
Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions
Energy management systems are designed to monitor, optimize, and control the smart grid
energy market. Demand-side management, considered as an essential part of the energy …
energy market. Demand-side management, considered as an essential part of the energy …
Dynamic Gaussian bare-bones fruit fly optimizers with abandonment mechanism: method and analysis
Abstract The Fruit Fly Optimization Algorithm (FOA) is a recent algorithm inspired by the
foraging behavior of fruit fly populations. However, the original FOA easily falls into the local …
foraging behavior of fruit fly populations. However, the original FOA easily falls into the local …
A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India
M Barman, NBD Choudhury, S Sutradhar - Energy, 2018 - Elsevier
In today's restructuring electricity market, short-term load forecasting (STLF) is an essential
tool for the electricity utilities to predict future scenario and act towards a profitable policy …
tool for the electricity utilities to predict future scenario and act towards a profitable policy …