Capacity Configuration for "PEDF" System Driven by Safe and Stable Operation

PEDF (photovoltaic, energy storage, direct current, and flexibility) is an important support for the new power system to achieve zero carbon electricity in buildings. To mitigate the high initial investment costs of crucial equipment in the early stage of system design, and to enhance power supply reliability, an improved energy valley optimization (EVO) algorithm for designing the capacity allocation of crucial equipment in PEDF systems for civil buildings is proposed, from the comprehensive perspectives of system economics, low carbon operation, and safety control. Simulation results are compared with those obtained from the Grey Wolf and traditional EVO algorithms. The results demonstrate that the improved EVO algorithm yields superior configuration results and faster convergence when applied to optimizing equipment capacity allocation in PEDF systems. These findings validate the effectiveness and feasibility of the proposed method, offering valuable insights for selecting crucial equipment capacities in PEDF systems for civil buildings.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-11-01
DOI
https://doi.org/10.11930/j.issn.1004-9649.202405013
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
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article

Capacity Configuration for "PEDF" System Driven by Safe and Stable Operation

SHILAP Revista de lepidopterología
Optimal Power Flow Distribution
article

Capacity Configuration for "PEDF" System Driven by Safe and Stable Operation

article en

Abstract

PEDF (photovoltaic, energy storage, direct current, and flexibility) is an important support for the new power system to achieve zero carbon electricity in buildings. To mitigate the high initial investment costs of crucial equipment in the early stage of system design, and to enhance power supply reliability, an improved energy valley optimization (EVO) algorithm for designing the capacity allocation of crucial equipment in PEDF systems for civil buildings is proposed, from the comprehensive perspectives of system economics, low carbon operation, and safety control. Simulation results are compared with those obtained from the Grey Wolf and traditional EVO algorithms. The results demonstrate that the improved EVO algorithm yields superior configuration results and faster convergence when applied to optimizing equipment capacity allocation in PEDF systems. These findings validate the effectiveness and feasibility of the proposed method, offering valuable insights for selecting crucial equipment capacities in PEDF systems for civil buildings.

SHILAP Revista de lepidopterología
State Grid Corporation of China (China) (CN), Fujian Electric Power Survey & Design Institute (CN), Shanghai Electric (China) (CN)
Openalex Percentile: Top 71%
Optimal Power Flow Distribution
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