Multi-timescale power self-balancing optimization and regulation of remote rural microgrids based on stochastic monte carlo method Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1088/1742-6596/2960/1/012014
Conventional microgrid power self-balancing optimization and regulation methods are mainly based on real-time regulation mechanisms, but there is the problem of local optimum, which affects the regulation effect. Therefore, a stochastic Monte Carlo method is designed to optimize the power self-balancing regulation of remote rural microgrids in multiple time scales. The multi-time scale power imbalance characteristics of remote rural microgrids are extracted, and the load differentiation characteristics of remote rural areas are judged according to the regional economic development and resource endowment. Based on stochastic Monte Carlo, a microgrid multi-timescale power self-balancing optimization and regulation model is constructed to quantify the self-balancing capability of the microgrid, taking into account the temporal difference between wind power and remote rural load demand. Taking into account the inter-seasonal characteristics of remote rural loads and the dynamic balancing demand of sources and loads, the multi-timescale adjustable power of remote rural microgrids is optimally allocated to further balance the complexity of the regulation model and the solution time. Comparative experiments are conducted to verify that the self-balancing optimization effect is better and can be applied in real life.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2960/1/012014
- OA Status
- diamond
- References
- 5
- Related Works
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- OpenAlex ID
- https://openalex.org/W4407640990
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407640990Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1742-6596/2960/1/012014Digital Object Identifier
- Title
-
Multi-timescale power self-balancing optimization and regulation of remote rural microgrids based on stochastic monte carlo methodWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-02-01Full publication date if available
- Authors
-
Fei Liu, Mengke Liao, Pengchao Wang, Changling Li, Xuehua ZhaoList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/2960/1/012014Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1088/1742-6596/2960/1/012014Direct OA link when available
- Concepts
-
Monte Carlo method, Computer science, Power (physics), Stochastic optimization, Mathematical optimization, Statistical physics, Physics, Mathematics, Statistics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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5Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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