An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs
The global environmental concern has promoted the installed capacity of renewable energy to explode. The uncertainty of the growing renewable energy poses a risk of incorrect forecasting of clearing prices and misled strategies to participants in the deregulated power markets. However, the transmiss...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723013653 |
| _version_ | 1797374180952375296 |
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| author | Yuhan Huang Tao Ding Xinran He Chenggang Mu Kai Feng Xiao Liang |
| author_facet | Yuhan Huang Tao Ding Xinran He Chenggang Mu Kai Feng Xiao Liang |
| author_sort | Yuhan Huang |
| collection | DOAJ |
| description | The global environmental concern has promoted the installed capacity of renewable energy to explode. The uncertainty of the growing renewable energy poses a risk of incorrect forecasting of clearing prices and misled strategies to participants in the deregulated power markets. However, the transmission loss and the correlation among integrated wind power outputs are ignored in the existing research. To improve the forecasting accuracy, this paper presents a Markov Chain Monte Carlo method for stochastic LMP considering the correlation among wind power outputs and transmission loss. The expectation of an LMP with a given precision can be obtained from the proposed method. The case study verifies the validity of the proposed method, demonstrating that the squared Euclidean distance of the selected Archimedean Copula function is limited to 9.3143. Additionally, given the same convergence criteria, the sampling times are reduced by an order of magnitude compared to the Acceptance-Rejection sampling method. |
| first_indexed | 2024-03-08T19:02:07Z |
| format | Article |
| id | doaj.art-ba55d4105aab4605952a8dfcacb845bc |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-08T19:02:07Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-ba55d4105aab4605952a8dfcacb845bc2023-12-28T05:18:05ZengElsevierEnergy Reports2352-48472023-11-019149153An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputsYuhan Huang0Tao Ding1Xinran He2Chenggang Mu3Kai Feng4Xiao Liang5School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, ChinaSchool of Electrical Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, China; Corresponding author.School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, ChinaSchool of Electrical Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, ChinaChina Electric Power Research Institute Nanjing Section, Nanjing, Jiangsu, 211102, ChinaState Grid Anhui Electric Power Company, Hefei, Anhui, 230061, ChinaThe global environmental concern has promoted the installed capacity of renewable energy to explode. The uncertainty of the growing renewable energy poses a risk of incorrect forecasting of clearing prices and misled strategies to participants in the deregulated power markets. However, the transmission loss and the correlation among integrated wind power outputs are ignored in the existing research. To improve the forecasting accuracy, this paper presents a Markov Chain Monte Carlo method for stochastic LMP considering the correlation among wind power outputs and transmission loss. The expectation of an LMP with a given precision can be obtained from the proposed method. The case study verifies the validity of the proposed method, demonstrating that the squared Euclidean distance of the selected Archimedean Copula function is limited to 9.3143. Additionally, given the same convergence criteria, the sampling times are reduced by an order of magnitude compared to the Acceptance-Rejection sampling method.http://www.sciencedirect.com/science/article/pii/S2352484723013653Renewable energyElectricity price forecastLocational marginal priceTransmission lossOutput correlation |
| spellingShingle | Yuhan Huang Tao Ding Xinran He Chenggang Mu Kai Feng Xiao Liang An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs Energy Reports Renewable energy Electricity price forecast Locational marginal price Transmission loss Output correlation |
| title | An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs |
| title_full | An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs |
| title_fullStr | An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs |
| title_full_unstemmed | An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs |
| title_short | An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs |
| title_sort | lmp forecasting method considering the transmission loss and the correlation among stochastic wind power outputs |
| topic | Renewable energy Electricity price forecast Locational marginal price Transmission loss Output correlation |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723013653 |
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