On the Improvement of representative demand curves via a hierarchical agglomerative clustering for power transmission network investment
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DOI: 10.1016/j.energy.2021.119989
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Cited by:
- Zifa Liu & Xinyi Li & Haiyan Zhao, 2023. "Short-Term Wind Power Forecasting Based on Feature Analysis and Error Correction," Energies, MDPI, vol. 16(10), pages 1-24, May.
- Wang, Yanmin & Li, Zhiwei & Liu, Junjie & Lu, Xuan & Zhao, Laifu & Zhao, Yan & Feng, Yongtao, 2024. "Analyzing daily change patterns of indoor temperature in district heating systems: A clustering and regression approach," Applied Energy, Elsevier, vol. 358(C).
- Ertugrul Ayyildiz & Mirac Murat & Gul Imamoglu & Yildiz Kose, 2023. "A novel hybrid MCDM approach to evaluate universities based on student perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 55-86, January.
- Palaniappan, Somasundaram & Karuppannan, Sundararaju & Velusamy, Durgadevi, 2024. "Categorization of Indian residential consumers electrical energy consumption pattern using clustering and classification techniques," Energy, Elsevier, vol. 289(C).
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Keywords
Transmission expansion planning; Hierarchical agglomerative clustering; Elbow rule; Linkage criterion; High-dimensionality data; K-means;All these keywords.
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