Yakai Lu

Day-Ahead Cooling Load Forecasting for District Cooling System Based on Baseline-Morphology Decomposition

Yue Liu, Huabiao Kong, Yakai Lu, Zhe Tian

Against the backdrop of global climate change and energy structure transition, district energy systems have garnered significant attention for their efficiency and sustainability. Accurate load forecasting is crucial for enhancing the operational efficiency of district cooling systems. However, as typical dynamic time-varying …

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Integrating data balancing and multi-task learning for operation state prediction in variable refrigerant flow air conditioning systems

Yakai Lu, Conghui Li, Yuying Ke, Jide Niu et autres

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Economic viability and capacity sizing of rural household PV systems under market-based feed-in tariffs: A case study in Tianjin, China

Xiaoyuan Li, Jide Niu, Zhe Wen Tian, Yakai Lu et autres

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Continual learning-enhanced data-driven modeling: A method for improving building load prediction model performance

Zhe Wen Tian, Mingwei Song, Yakai Lu, Wenjie Song et autres

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A rapid assessment method for the thermal mass energy storage capacity of building clusters

Zhe Tian, Ruiqi Liu, Yakai Lu, Jide Niu et autres

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A data informativeness evaluation method for grey-box modeling of building thermal dynamics

Xinyi Lin, Zhe Tian, Adrian Chong, Yakai Lu et autres

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Performance requirement evaluation of day-ahead load prediction in operation optimization of cold-storage air-conditioning systems

Yakai Lu, Conghui Li, Wenjing Liu, Jide Niu et autres

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A Short-Term Building Load Prediction Method Based on Modal Decomposition and Deep Learning

Shengze Lu, Dandan Yu, Yan Yu Ding, Wanyue Chen et autres

Accurate cooling load prediction is essential for energy-efficient HVAC system operation. However, the stochastic and nonlinear nature of load data challenges conventional neural networks, causing prediction delays and errors. To address this, a novel hybrid model is developed. The approach first applies …

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Optimal operation strategy for building users considering asynchronous information release in multi-type demand response markets to mitigate building-grid interaction risks

Cheng Zhen, Zhe Wen Tian, Jide Niu, Yakai Lu et autres

Co-quantification of building energy flexibility considering the synergistic effect of HVAC and lighting systems

Zhe Wen Tian, Junze Li, Yakai Lu, Jide Niu et autres

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Machine learning-enhanced lightweight rule-based control strategy for building energy demand response

Jie Zhu, Zhe Wen Tian, Jide Niu, Yakai Lu et autres

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Stochastic peak shaving scenario generation for grid-friendly building energy system design

Xiaoyuan Li, Zhe Tian, Wei Feng, Zhen Cheng et autres

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