Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model
Demand response (DR) is usually regarded as a valuable balancing and reserve resource that contributes to maintaining power balance and integrating renewable energies. However, the price elasticity curve of the DR resources is influenced by consumers' behavioral uncertainty and therefore...
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| Format: | Article |
| Language: | English |
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China electric power research institute
2025-01-01
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| Series: | CSEE Journal of Power and Energy Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10026207/ |
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| author | Bo Hu Yue Sun Wei Huang Changzheng Shao Tao Niu Xin Cheng Kaigui Xie |
| author_facet | Bo Hu Yue Sun Wei Huang Changzheng Shao Tao Niu Xin Cheng Kaigui Xie |
| author_sort | Bo Hu |
| collection | DOAJ |
| description | Demand response (DR) is usually regarded as a valuable balancing and reserve resource that contributes to maintaining power balance and integrating renewable energies. However, the price elasticity curve of the DR resources is influenced by consumers' behavioral uncertainty and therefore is difficult to predict. Consequently, additional risk may be introduced to composite power system reliability. Considering that, this paper investigates a reliability assessment of composite power system considering both the merits and potential uncertainty involved in the DR. First, the psychological behavior and consumption behavior of consumers are characterized in the DR modeling. A novel DR uncertainty index (denoted as <tex>$I^{U}$</tex>) measures uncertainty of consumer's behavior when electricity price changes. Then, an advanced Sigmoid cloud model is proposed to depict the comprehensive uncertain mapping relationships between price and <tex>$I^{U}$</tex>. Moreover, an improved demand elasticity matrix is proposed, in which price-quantity elastic coefficients are modified by the <tex>$I^{U}$</tex> index. Finally, a reliability assessment framework for a composite power system is developed considering the uncertain price-based DR model and a k-means algorithm is used to accelerate the assessment process. Accuracy and effectiveness of the proposed method are investigated through the case study on RBTS, RTS79 and RTS96 reliability test systems. |
| format | Article |
| id | doaj-art-d1f3fe6de701493e8351c7e9e6fb7486 |
| institution | DOAJ |
| issn | 2096-0042 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | China electric power research institute |
| record_format | Article |
| series | CSEE Journal of Power and Energy Systems |
| spelling | doaj-art-d1f3fe6de701493e8351c7e9e6fb74862025-08-20T03:11:17ZengChina electric power research instituteCSEE Journal of Power and Energy Systems2096-00422025-01-011131347135710.17775/CSEEJPES.2021.0150010026207Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud ModelBo Hu0Yue Sun1Wei Huang2Changzheng Shao3Tao Niu4Xin Cheng5Kaigui Xie6Chongqing University,State Key Laboratory of Power Transmission Equipment & System Security and new technology,Chongqing,China,400044China Yangtze Power Co., Ltd,Yichang,China,443000Chongqing University,State Key Laboratory of Power Transmission Equipment & System Security and new technology,Chongqing,China,400044Chongqing University,State Key Laboratory of Power Transmission Equipment & System Security and new technology,Chongqing,China,400044Chongqing University,State Key Laboratory of Power Transmission Equipment & System Security and new technology,Chongqing,China,400044Chongqing University,State Key Laboratory of Power Transmission Equipment & System Security and new technology,Chongqing,China,400044Chongqing University,State Key Laboratory of Power Transmission Equipment & System Security and new technology,Chongqing,China,400044Demand response (DR) is usually regarded as a valuable balancing and reserve resource that contributes to maintaining power balance and integrating renewable energies. However, the price elasticity curve of the DR resources is influenced by consumers' behavioral uncertainty and therefore is difficult to predict. Consequently, additional risk may be introduced to composite power system reliability. Considering that, this paper investigates a reliability assessment of composite power system considering both the merits and potential uncertainty involved in the DR. First, the psychological behavior and consumption behavior of consumers are characterized in the DR modeling. A novel DR uncertainty index (denoted as <tex>$I^{U}$</tex>) measures uncertainty of consumer's behavior when electricity price changes. Then, an advanced Sigmoid cloud model is proposed to depict the comprehensive uncertain mapping relationships between price and <tex>$I^{U}$</tex>. Moreover, an improved demand elasticity matrix is proposed, in which price-quantity elastic coefficients are modified by the <tex>$I^{U}$</tex> index. Finally, a reliability assessment framework for a composite power system is developed considering the uncertain price-based DR model and a k-means algorithm is used to accelerate the assessment process. Accuracy and effectiveness of the proposed method are investigated through the case study on RBTS, RTS79 and RTS96 reliability test systems.https://ieeexplore.ieee.org/document/10026207/Advanced Sigmoid cloud modeldemand response uncertaintypower system reliabilityprice elasticity of demand |
| spellingShingle | Bo Hu Yue Sun Wei Huang Changzheng Shao Tao Niu Xin Cheng Kaigui Xie Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model CSEE Journal of Power and Energy Systems Advanced Sigmoid cloud model demand response uncertainty power system reliability price elasticity of demand |
| title | Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model |
| title_full | Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model |
| title_fullStr | Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model |
| title_full_unstemmed | Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model |
| title_short | Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model |
| title_sort | power system reliability assessment with quantification of demand response uncertainty based on advanced sigmoid cloud model |
| topic | Advanced Sigmoid cloud model demand response uncertainty power system reliability price elasticity of demand |
| url | https://ieeexplore.ieee.org/document/10026207/ |
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