Research on Intelligent Energy System and Power Metering Optimization Based on Multi-objective Optimization Decision Algorithm

Authors

  • Kang Liyan State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, Shenyang, 110000, Liaoning, China
  • Shang Ying State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, Shenyang, 110000, Liaoning, China
  • Zhang Muxin State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, Shenyang, 110000, Liaoning, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.3946

Keywords:

Smart energy systems, multi-objective optimization decision algorithm, power metering optimization, energy efficiency

Abstract

In this paper, the intricate problem of optimizing power metering within an intelligent energy system, utilizing a multi-objective optimization decision-making algorithm, is thoroughly explored. Given the current energy landscape, achieving efficient energy utilization and environmental sustainability has become a focal point of research. As a pivotal aspect of future energy management, the precision and optimization of power metering in intelligent energy systems directly influence the effectiveness and cost of energy consumption. To begin, this paper delves into the fundamental principles and application backdrop of intelligent energy systems, highlighting the significance of power metering in such systems. Subsequently, addressing the multi-objective optimization challenges in power metering, a novel optimization method based on a multi-objective optimization decision algorithm is introduced. This algorithm achieves comprehensive optimization of power metering, encompassing multiple objectives such as power cost reduction, enhanced energy efficiency, and environmental protection. The experimental results underscore the remarkable performance of this algorithm, which not only elevates the precision of power metering but also achieves substantial savings in energy costs and significantly boosts energy efficiency. Furthermore, the algorithm exhibits robust adaptability, making it capable of addressing power metering optimization challenges across diverse scenarios. Finally, this paper discusses the practical application prospects of the optimization algorithm in intelligent energy systems, and points out the direction of future research. The research in this paper provides new ideas and methods for the optimization of power metering in intelligent energy systems, and has important theoretical and practical significance for promoting the intelligence and refinement of energy management.

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Author Biographies

Kang Liyan, State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, Shenyang, 110000, Liaoning, China

Kang Liyan was born in Shenyang, Liaoning, China in 1975. She obtained a Master’s degree in Engineering from Northeast Electric Power University. She works at the Marketing Service Center of State Grid Liaoning Electric Power Co., Ltd. Her research interests include electricity metering, construction of electricity consumption information collection systems, information security, and big data analysis.

Shang Ying, State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, Shenyang, 110000, Liaoning, China

Shang Ying was born in 1988 in Liaoyang, Liaoning, China. She obtained a Master’s degree in Engineering from North China Electric Power University. She works at the Marketing Service Center of State Grid Liaoning Electric Power Co., Ltd. Her research interests include electricity metering, electricity inspection and anti theft, and big data application analysis. Encryption and information security.

Zhang Muxin, State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, Shenyang, 110000, Liaoning, China

Zhang Muxin was born in Huludao, Liaoning, China in 1992. He obtained a Bachelor’s degree in Computer Science from Northeastern University. He works at the Marketing Service Center of State Grid Liaoning Electric Power Co., Ltd. His research interests include electricity metering, electricity information collecting, and line loss analyzing.

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Published

2024-10-28

How to Cite

Liyan, K. ., Ying, S. ., & Muxin, Z. . (2024). Research on Intelligent Energy System and Power Metering Optimization Based on Multi-objective Optimization Decision Algorithm. Distributed Generation &Amp; Alternative Energy Journal, 39(04), 807–830. https://doi.org/10.13052/dgaej2156-3306.3946

Issue

Section

Renewable Power & Energy Systems