A Low-Carbon Operation Optimization Method of ETG-RIES Based on Adaptive Optimization Spiking Neural P Systems

To enhance multi-energy complementarity and foster a low carbon economy of energy resources, this paper proposes an innovative low-carbon operation optimization method for electric-thermal-gas regional integrated energy systems. To bolster the low-carbon operation capabilities of such systems, a coordinated operation framework is presented that integrates carbon capture devices, power to gas equipment, combined heat and power units, and a multi-energy storage system. To address the challenge of high-dimensional constraint imbalance in the optimization process, a novel low-carbon operation optimization method is then proposed. The new method is based on an adaptive single-objective continuous optimization spiking neural P system, specifically designed for this purpose. Furthermore, simulation models of four typical schemes are established and employed to test and analyze the economy and carbon environmental pollution degree of the proposed system model, as well as the performance of the operation optimization method. Finally, simulation results show that the proposed method not only considers the economic viability of the target integrated energy system, but also significantly improves the wind power utilization and carbon reduction capabilities.

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Publication Details

Journal
Protection and Control of Modern Power Systems
Published
2024-08-26
DOI
https://doi.org/10.23919/pcmp.2023.000208
Citations
10
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
2.34

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article

A Low-Carbon Operation Optimization Method of ETG-RIES Based on Adaptive Optimization Spiking Neural P Systems

Tao Wang, Luis Valencia–Cabrera, Ruixuan Ying, Zhu Huang
10 citations
Protection and Control of Modern Power Systems
DNA and Biological Computing
2.34
article

A Low-Carbon Operation Optimization Method of ETG-RIES Based on Adaptive Optimization Spiking Neural P Systems

Tao Wang, Luis Valencia–Cabrera, Ruixuan Ying, Zhu Huang
article en
10 citations

Abstract

To enhance multi-energy complementarity and foster a low carbon economy of energy resources, this paper proposes an innovative low-carbon operation optimization method for electric-thermal-gas regional integrated energy systems. To bolster the low-carbon operation capabilities of such systems, a coordinated operation framework is presented that integrates carbon capture devices, power to gas equipment, combined heat and power units, and a multi-energy storage system. To address the challenge of high-dimensional constraint imbalance in the optimization process, a novel low-carbon operation optimization method is then proposed. The new method is based on an adaptive single-objective continuous optimization spiking neural P system, specifically designed for this purpose. Furthermore, simulation models of four typical schemes are established and employed to test and analyze the economy and carbon environmental pollution degree of the proposed system model, as well as the performance of the operation optimization method. Finally, simulation results show that the proposed method not only considers the economic viability of the target integrated energy system, but also significantly improves the wind power utilization and carbon reduction capabilities.

Protection and Control of Modern Power SystemsVol. 9(5)
Xihua University (CN), Universidad de Sevilla (ES)
National Natural Science Foundation of China
Openalex Percentile: Top 11%
DNA and Biological Computing
2.34
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A Low-Carbon Operation Optimization Method of ETG-RIES Based on Adaptive Optimization Spiking Neural P Systems — Tao Wang, Luis Valencia–Cabrera, et al. · Protection and Control of Modern Power Systems (2024) | TGRS Research Map | TGRS