A low-carbon operation optimization method of ETG-RIES based on adaptive optimization spiking neural P systems
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This work is partially supported by the National Natural Science Foundation of China (No. 61703345) and the Chunhui Project Foundation of the Education Department of China (No. Z201980).

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    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.

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Tao Wang, Zhu Huang, Ruixuan Ying, Luis Valencia-Cabrera. A low-carbon operation optimization method of ETG-RIES based on adaptive optimization spiking neural P systems[J]. Protection and Control of Modern Power Systems,2024,V9(5):162-177.[Tao Wang, Zhu Huang, Ruixuan Ying, Luis Valencia-Cabrera. A low-carbon operation optimization method of ETG-RIES based on adaptive optimization spiking neural P systems[J]. Power System Protection and Control,2024,V9(5):162-177]

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  • Online: August 28,2024
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