Study on Short-Term Electricity Load Forecasting Based on the Modified Simplex Approach Sparrow Search Algorithm Mixed with a Bidirectional Long- and Short-Term Memory Network Article Swipe
Chenjun Zhang
,
F. Zhang
,
Fuyang Gou
,
Wensi Cao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/pr12091796
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/pr12091796
In order to balance power supply and demand, which is crucial for the safe and effective functioning of power systems, short-term power load forecasting is a crucial component of power system planning and operation. This paper aims to address the issue of low prediction accuracy resulting from power load volatility and nonlinearity. It suggests optimizing the number of hidden layer nodes, number of iterations, and learning rate of bi-directional long- and short-term memory networks using the improved sparrow search algorithm, and predicting the actual load data using the load prediction model. Using actual power load data from Wuxi, Jiangsu Province, China, as a dataset, the model makes predictions. The results indicate that the model is effective because the enhanced sparrow algorithm optimizes the bi-directional long- and short-term memory network model for predicting the power load data with a relative error of only 2%, which is higher than the prediction accuracy of the other models proposed in the paper.
Related Topics
Concepts
Term (time)
Sparrow
Long short term memory
Computer science
Short-term memory
Simplex
Algorithm
Mathematical optimization
Mathematics
Artificial intelligence
Artificial neural network
Cognition
Combinatorics
Working memory
Physics
Biology
Quantum mechanics
Recurrent neural network
Ecology
Neuroscience
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/pr12091796
- https://www.mdpi.com/2227-9717/12/9/1796/pdf?version=1724422783
- OA Status
- gold
- Cited By
- 7
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401807425
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401807425Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/pr12091796Digital Object Identifier
- Title
-
Study on Short-Term Electricity Load Forecasting Based on the Modified Simplex Approach Sparrow Search Algorithm Mixed with a Bidirectional Long- and Short-Term Memory NetworkWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-08-23Full publication date if available
- Authors
-
Chenjun Zhang, F. Zhang, Fuyang Gou, Wensi CaoList of authors in order
- Landing page
-
https://doi.org/10.3390/pr12091796Publisher landing page
- PDF URL
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https://www.mdpi.com/2227-9717/12/9/1796/pdf?version=1724422783Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2227-9717/12/9/1796/pdf?version=1724422783Direct OA link when available
- Concepts
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Term (time), Sparrow, Long short term memory, Computer science, Short-term memory, Simplex, Algorithm, Mathematical optimization, Mathematics, Artificial intelligence, Artificial neural network, Cognition, Combinatorics, Working memory, Physics, Biology, Quantum mechanics, Recurrent neural network, Ecology, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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21Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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