Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model
The increased share of new energy sources in Northeast China’s power mix has strained grid stability. Energy storage technologies are essential for maintaining grid stability by addressing peak shaving and frequency regulation challenges. However, a clear quantitative assessment of the region’s ener...
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2025-01-01
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| Online Access: | https://www.mdpi.com/1996-1073/18/2/226 |
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| author | Yiwen Yao Yu Shi Jing Wang Zifang Zhang Xin Xu Xinhong Wang Dingheng Wang Zilai Ou Zhe Ma |
| author_facet | Yiwen Yao Yu Shi Jing Wang Zifang Zhang Xin Xu Xinhong Wang Dingheng Wang Zilai Ou Zhe Ma |
| author_sort | Yiwen Yao |
| collection | DOAJ |
| description | The increased share of new energy sources in Northeast China’s power mix has strained grid stability. Energy storage technologies are essential for maintaining grid stability by addressing peak shaving and frequency regulation challenges. However, a clear quantitative assessment of the region’s energy storage needs is lacking, leading to weak grid stability and limited growth potential. This paper analyzes power supply data from Northeast China and models the stochastic characteristics of new energy generation. A joint optimization model for energy storage and thermal power is developed to optimize power allocation for peak shaving and frequency regulation at minimal cost. The empirical distribution method quantifies the relationship between storage power, capacity, and confidence levels, providing insights into the region’s future energy storage demands. The study finds that under 10 typical scenarios, the demand for peaking power at a 15 min scale is ≤500 MW, and the demand for frequency regulation at a 1 min scale is ≤1000 MW. At the 90% confidence level, the required capacity for new energy storage for peak shaving and frequency regulation is 424.13 MWh and 197.65 MWh, respectively. The required power for peak shaving and frequency regulation is 247.88 MW and 527.33 MW, respectively. The durations of peak shaving and frequency regulation are 1.71 h and 0.38 h. It also forecasts the energy storage capacity in the northeast region from 2025 to 2030 under the 5% annual incremental new energy penetration scenario. These findings provide theoretical support for energy storage policies in Northeast China during the 14th Five-Year Plan and practical guidance for accelerating energy storage industrialization. |
| format | Article |
| id | doaj-art-979a4113220044019d618ee1780e28bc |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-979a4113220044019d618ee1780e28bc2025-01-24T13:30:42ZengMDPI AGEnergies1996-10732025-01-0118222610.3390/en18020226Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering ModelYiwen Yao0Yu Shi1Jing Wang2Zifang Zhang3Xin Xu4Xinhong Wang5Dingheng Wang6Zilai Ou7Zhe Ma8Power Economic Research Institute of Jilin Electric Power Co., Ltd., Changchun 130021, ChinaPower Economic Research Institute of Jilin Electric Power Co., Ltd., Changchun 130021, ChinaPower Economic Research Institute of Jilin Electric Power Co., Ltd., Changchun 130021, ChinaDeepwater Engineering Research Center, Dalian University of Technology, Dalian 116024, ChinaPower Economic Research Institute of Jilin Electric Power Co., Ltd., Changchun 130021, ChinaPower Economic Research Institute of Jilin Electric Power Co., Ltd., Changchun 130021, ChinaPower Economic Research Institute of Jilin Electric Power Co., Ltd., Changchun 130021, ChinaDeepwater Engineering Research Center, Dalian University of Technology, Dalian 116024, ChinaDeepwater Engineering Research Center, Dalian University of Technology, Dalian 116024, ChinaThe increased share of new energy sources in Northeast China’s power mix has strained grid stability. Energy storage technologies are essential for maintaining grid stability by addressing peak shaving and frequency regulation challenges. However, a clear quantitative assessment of the region’s energy storage needs is lacking, leading to weak grid stability and limited growth potential. This paper analyzes power supply data from Northeast China and models the stochastic characteristics of new energy generation. A joint optimization model for energy storage and thermal power is developed to optimize power allocation for peak shaving and frequency regulation at minimal cost. The empirical distribution method quantifies the relationship between storage power, capacity, and confidence levels, providing insights into the region’s future energy storage demands. The study finds that under 10 typical scenarios, the demand for peaking power at a 15 min scale is ≤500 MW, and the demand for frequency regulation at a 1 min scale is ≤1000 MW. At the 90% confidence level, the required capacity for new energy storage for peak shaving and frequency regulation is 424.13 MWh and 197.65 MWh, respectively. The required power for peak shaving and frequency regulation is 247.88 MW and 527.33 MW, respectively. The durations of peak shaving and frequency regulation are 1.71 h and 0.38 h. It also forecasts the energy storage capacity in the northeast region from 2025 to 2030 under the 5% annual incremental new energy penetration scenario. These findings provide theoretical support for energy storage policies in Northeast China during the 14th Five-Year Plan and practical guidance for accelerating energy storage industrialization.https://www.mdpi.com/1996-1073/18/2/226energy storagedemand capacityrenewable energypower systems |
| spellingShingle | Yiwen Yao Yu Shi Jing Wang Zifang Zhang Xin Xu Xinhong Wang Dingheng Wang Zilai Ou Zhe Ma Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model Energies energy storage demand capacity renewable energy power systems |
| title | Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model |
| title_full | Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model |
| title_fullStr | Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model |
| title_full_unstemmed | Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model |
| title_short | Quantitative Analysis of Energy Storage Demand in Northeast China Using Gaussian Mixture Clustering Model |
| title_sort | quantitative analysis of energy storage demand in northeast china using gaussian mixture clustering model |
| topic | energy storage demand capacity renewable energy power systems |
| url | https://www.mdpi.com/1996-1073/18/2/226 |
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