Browsing by Author "Han, Yifeng"

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Energy, environmental-based cost, and solar share comparisons of a solar driven cooling and heating system with different types of building
(2022-07-05) Chen, Yuzhu; Hua, Huilian; Xu, Jinzhao; Wang, Jun; Lund, Peter D.; Han, Yifeng; Cheng, Tanghua
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
To reduce fossil fuel consumption and carbon emissions from building energy systems, a solar-based cooling and heating system is proposed here employing solar concentrating collectors, photovoltaics, double-effect absorption heat pump and thermal storage. The system is applied to five building types in a region with cold winter and hot summer. The system configuration is optimized using energy, environmental cost, and solar fraction as criteria. The results demonstrate that the solar system could produce at least 31.1% of the cooling/heating loads resulting in 73.3% and 64.2% energy and cost savings in a hospital. The coefficient of performance of the hybrid system ranges from 5.87 to 7.56 in cooling mode, and 1.22 to 1.65 for heating. The cost of devices is the most sensitive factor, and followed by the price of grid electricity. Increasing the renewable energy penetration rate could improve the energy performance, but decrease the cost saving ratio due to the lower carbon emissions.
Multi-objective optimization of an integrated energy system against energy, supply-demand matching and exergo-environmental cost over the whole life-cycle
(2022-02-15) Chen, Yuzhu; Xu, Zhicheng; Wang, Jun; Lund, Peter D.; Han, Yifeng; Cheng, Tanghua
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
An integrated energy system (IES) can yield several benefits in energy, environmental impacts, cost, and flexibility over a separate system, although the initial cost may be higher. An IES using gas turbine, solar photovoltaics (PV), heat pumps, electrical cooling, and energy storage units is proposed here to satisfy the electricity, cooling, and heating demands of a residential building. A multi-objective optimization approach is used to find the best solutions considering energy, supply-demand matching and exergo-environmental economic indices with life cycle assessment (LCA) in following electric mode. The maximum benefit from the IES studied is reached with a system yielding 53.08% for energy savings, 99.88% matching, and 43.50% cost savings. The ideal scheme selected by the TOPSIS method has a higher annual total cost than the cost with conventional method, but has a better cost saving ratio, 41.81%. A sensitivity analysis shows that a higher PV use would decrease the fuel consumption, but it would reduce the matching and economic performance. Similar to the effect of natural gas price, the off-grid electricity price has higher impact on the cost saving ratio, but lower influence on the specific exergo-environmental cost.
Parameter identification and generality analysis of photovoltaic module dual-diode model based on artificial hummingbird algorithm
(2023-12-01) Li, Zhen; Hu, Jianke; Han, Yifeng; Li, Hefeng; Wang, Jun; Lund, Peter
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The aim of this study is to propose a photovoltaic (PV) module simulation model with high accuracy under practical working conditions and strong applicability in the engineering field to meet various PV system simulation needs. Unlike previous model-building methods, this study combines the advantages of analytical and metaheuristic algorithms. First, the applicability of various metaheuristic algorithms is comprehensively compared and the seven parameters of the PV cell under standard test conditions are extracted using the double diode model, which verifies that the artificial hummingbird algorithm has higher accuracy than other algorithms. Then, the seven parameters under different conditions are corrected using the analytical method. In terms of the correction method, the ideal factor correction is added on the basis of previous methods to solve the deviation between simulated data and measured data in the non-linear section. Finally, the root mean squared error between the simulated current data and the measured current data of the proposed model under three different temperatures and irradiance is 0.0697, 0.0570 and 0.0289 A, respectively.