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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 deep learning framework for building energy consumption forecast
Increasing global building energy demand, with the related economic and environmental
impact, upsurges the need for the design of reliable energy demand forecast models. This …
impact, upsurges the need for the design of reliable energy demand forecast models. This …
Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads
Z Zhang, WC Hong - Knowledge-Based Systems, 2021 - Elsevier
Accurate electric load forecasting is critical in guaranteeing the efficiency of the load
dispatch and supply by a power system, which prevents the wasting of electricity and …
dispatch and supply by a power system, which prevents the wasting of electricity and …
A comprehensive review of the load forecasting techniques using single and hybrid predictive models
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 …
Recent advances in neuro-fuzzy system: A survey
Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
Optimization strategies for Microgrid energy management systems by Genetic Algorithms
Abstract Grid-connected Microgrids (MGs) have a key role for bottom-up modernization of
the electric distribution network forward next generation Smart Grids, allowing the …
the electric distribution network forward next generation Smart Grids, allowing the …
Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by firefly algorithm
D Wang, H Luo, O Grunder, Y Lin, H Guo - Applied Energy, 2017 - Elsevier
In the deregulated competitive electricity market, the price which reflects the relationship
between electricity supply and demand is one of the most important elements, making it …
between electricity supply and demand is one of the most important elements, making it …
[HTML][HTML] An adaptive deep-learning load forecasting framework by integrating transformer and domain knowledge
Electrical energy is essential in today's society. Accurate electrical load forecasting is
beneficial for better scheduling of electricity generation and saving electrical energy. In this …
beneficial for better scheduling of electricity generation and saving electrical energy. In this …
Short-term load forecasting method based on feature preference strategy and LightGBM-XGboost
X Yao, X Fu, C Zong - IEEE Access, 2022 - ieeexplore.ieee.org
Short term load forecasting is one of the important problems in power system. Accurate
forecasting results can improve the flexibility of power market and resource utilization …
forecasting results can improve the flexibility of power market and resource utilization …
Comparative analysis of noise robustness of type 2 fuzzy logic controllers
Nowadays Fuzzy logic in control applications is a well-recognized alternative, and this is
thanks to its inherent advantages as its robustness. However, the Type-2 Fuzzy Logic …
thanks to its inherent advantages as its robustness. However, the Type-2 Fuzzy Logic …