Low-Carbon Economic Dispatch of Integrated Energy Systems in Multi-Form Energy-intensive Parks Based on the ICT-GRU Prediction Model

Authors

  • Liaoyi Ning Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China
  • Kai Liang Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China
  • Bo Zhang Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China
  • Yang Gao Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China
  • Zhilin Xu Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China

DOI:

https://doi.org/10.13052/spee1048-5236.4323

Keywords:

ICT-GRU prediction, multi-form energy-intensive park, integrated energy system, low-carbon economic dispatch

Abstract

This paper presents a solution to the issues of redundancy and ambiguity in predicting variables associated with renewable energy output while aligning with the objectives of the “dual-carbon” energy strategy. A low-carbon economic dispatch method for multi-form energy-intensive parks is proposed, employing the ICT-GRU prediction model. Leveraging historical generation data, the ICT-GRU model enables accurate forecasting of renewable energy output. Subsequently, a comprehensive energy system model is developed considering the carbon emission characteristics and control features of park entities. The model aims to minimize operational costs and facilitate low-carbon economic dispatch. The effectiveness of the proposed method is demonstrated through a case study conducted in a multi-form energy-intensive load park integrated into a power grid. The results validate its capability to achieve low-carbon economic operation and provide valuable insights for grid dispatch optimization.

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Author Biographies

Liaoyi Ning, Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China

Liaoyi Ning, Male, from Anshan City, Liaoning Province, Deputy General Manager of State Grid Liaoning Electric Power Co., Ltd., with a doctoral degree in Power Systems and Automation. His main research areas include optimization and scheduling of power systems, and the secure and stable operation of power systems.

Kai Liang, Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China

Kai Liang, Male, born in June 1975, from Anshan City, Liaoning Province. Currently employed at State Grid Liaoning Electric Power Co., Ltd., Anshan Power Supply Company. His main research areas are optimization and scheduling of power systems, and active support for the integration of renewable energy.

Bo Zhang, Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China

Bo Zhang, Male, born on January 23, 1994. Currently employed at State Grid Liaoning Electric Power Co., Ltd., Anshan Power Supply Company. Holds a master’s degree in Power Systems and Automation. His main research areas are flexible DC transmission and optimization and scheduling of power systems.

Yang Gao, Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China

Yang Gao, Male, born on September 21, 1982. Holds a master’s degree in Agricultural Electrification and Automation. Currently employed at State Grid Liaoning Electric Power Co., Ltd., Anshan Power Supply Company. His main research area is optimization and scheduling of power systems.

Zhilin Xu, Anshan Power Supply Company of State Grid Liaoning Electric Power Co., Ltd, Anshan 114000, China

Zhilin Xu, Male, born on June 20, 1990. Holds a master’s degree in Electrical Engineering. Currently employed at State Grid Liaoning Electric Power Co., Ltd., Anshan Power Supply Company. His main research area is the secure and stable operation of power systems.

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Published

2024-01-14

How to Cite

Ning, L. ., Liang, K. ., Zhang, B. ., Gao, Y. ., & Xu, Z. . (2024). Low-Carbon Economic Dispatch of Integrated Energy Systems in Multi-Form Energy-intensive Parks Based on the ICT-GRU Prediction Model. Strategic Planning for Energy and the Environment, 43(02), 251–280. https://doi.org/10.13052/spee1048-5236.4323

Issue

Section

New Technologies and Strategies for Sustainable Development