Competitive evaluation and multi-stage planning of park integrated energy systems

被引:0
|
作者
Yongtao Guo [1 ]
Yue Xiang [1 ]
Zhukui Tan [2 ]
Hongcai Zhang [3 ]
Ji Li [4 ]
Zechun Hu [5 ]
Fang Liu [6 ]
Junyong Liu [1 ]
机构
[1] Sichuan University,College of Electrical Engineering
[2] China Southern Power Grid Guizhou Power Grid Co.,Electric Power Research Institute
[3] Ltd,State Key Laboratory of Internet of Things for Smart City, Department of Electrical and Computer Engineering
[4] University of Macau,Department of Electrical Engineering
[5] China Academy of Building Research,undefined
[6] Tsinghua University,undefined
[7] State Grid Sichuan Economic Research Institute,undefined
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D O I
10.1038/s41598-025-92431-9
中图分类号
学科分类号
摘要
Optimal planning for the park integrated energy system (PIES) is essential for energy efficiency improvement and carbon neutrality. A reasonable evaluation method is the key to guide PIES planning. However, indicators for the PIES planning schemes are various with high penetration of renewable energy, large carbon emissions and multiple energy forms coupling, which brings challenges to find out the benchmark planning scheme for PIES development. Herein, we extend a competitive evaluation method that considers the aspects of energy, economy, environment, reliability and greening development level for PIES with different energy planning trends. We formulate a multi-stage planning model for PIES dynamic development aiming at investment and operation cost minimization. We set a group of comparable PIESs with different energy planning trends to evaluate and determine the benchmark PIES to motivate the others. The competitiveness of our evaluation method is reflected in that the benchmark is determined by the competition of different PIESs and it may change through multi-stage planning. A practical PIES with eight functional areas is adopted for competitive evaluation in multi-criteria over multi-stage planning optimization, and their pros and cons are evaluated and compared. By comparing the evaluation efficiency, the benchmark of PIES planning can be dynamically adjusted.
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