Optimal Planning of Interconnected Integrated Energy System at User Side Based on Chance Constrained Programming

2018 ◽  
Author(s):  
Muke Bai ◽  
Wanxing Sheng ◽  
Xiaokang Hu ◽  
Limei Zhang ◽  
Keyan Liu
Keyword(s):  
Energy System ◽  
Chance Constrained Programming ◽  
Optimal Planning ◽  
Integrated Energy System ◽  
Constrained Programming

Optimal Planning of Islanded Integrated Energy System With Solar-Biogas Energy Supply

2020 ◽  
Vol 11 (4) ◽  
pp. 2437-2448 ◽  
Author(s):  
Canbing Li ◽  
Hanyu Yang ◽  
Mohammad Shahidehpour ◽  
Zhenci Xu ◽  
Bin Zhou ◽  
...  
Keyword(s):  
Energy Supply ◽  
Energy System ◽  
Optimal Planning ◽  
Integrated Energy System ◽  
Biogas Energy

Optimal Planning for Electricity-Hydrogen Integrated Energy System Considering Power to Hydrogen and Heat and Seasonal Storage

2020 ◽  
Vol 11 (4) ◽  
pp. 2662-2676 ◽  
Author(s):  
Guangsheng Pan ◽  
Wei Gu ◽  
Yuping Lu ◽  
Haifeng Qiu ◽  
Shuai Lu ◽  
...  
Keyword(s):  
Energy System ◽  
Optimal Planning ◽  
Integrated Energy System

scholarly journals Study on Multiobjective Modeling and Optimization of Offshore Micro Integrated Energy System considering Uncertainty of Load and Wind Power

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jun Wu ◽  
Baolin Li ◽  
Jun Chen ◽  
Qinghui Lou ◽  
Xiangyu Xing ◽  
...  
Keyword(s):  
Wind Power ◽  
Oil And Gas ◽  
Operating Cost ◽  
Energy Systems ◽  
Energy System ◽  
Offshore Wind ◽  
Chance Constrained Programming ◽  
Penalty Cost ◽  
Integrated Energy Systems ◽  
Integrated Energy System

Offshore micro integrated energy systems (OMIESs) are the basis of offshore oil and gas engineering and play an important role in developing and utilizing marine resources. By introducing offshore wind power generation, the carbon emissions of offshore micro integrated energy systems can be effectively reduced; however, greater challenges have been posted to the reliable operation due to the uncertainty. To reduce the influence brought by the uncertainty, a multiobjective optimization model was proposed based on the chance-constrained programming (CCP); the operating cost and penalty cost of natural gas emission were selected as objectives. Then, the improved hybrid constraints handling strategy based on nondominated sorting genetic algorithm II (IHCHS-NSGAII) was introduced to solve the model efficiently. Finally, the numerical studies verified the efficiency of the proposed algorithm, as well as the validity and feasibility of the proposed model in improving the economy of OMIES under uncertainty.

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