| 1. |
- Liu, L., et al.
(författare)
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Forecasting Power Output of Photovoltaic System Using A BP Network Method
- 2017
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Ingår i: Energy Procedia. - : Elsevier Ltd. - 1876-6102. ; 142, s. 780-786
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Tidskriftsartikel (refereegranskat)abstract
- The characteristics of intermittent and stochastic of solar energy has brought great challenges to power grid system in terms of operation and regulation. Power forecasting is an important factor for optimal schedule of power grid system and assessing the working performance of PV systems. In order to forecast the power output of a PV system located in Ashland at 24-hour-ahead for higher efficiency, a back propagation (BP) neural network model is proposed. Before designing the model, correlation analysis is done to investigate the relationship between power output and solar irradiance and ambient temperature, which are key parameters affecting the power output of PV systems. Based on a correlation analysis, the model admitted the following input parameters: hourly solar radiation intensity, the highest, the lowest daily and the average daily temperature, and hourly power output of the PV system. The output of the model is the forecasted PV power output 24 hours ahead. Based on the datasets, the neural network is trained to improve its accuracy. The best performance is obtained with the BP neural network structure of 28-20-11. The analysis of the error indicator MAPE shows that the proposed model has great accuracy and efficiency for forecasting the power output of photovoltaic systems.
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| 2. |
- Gao, Y., et al.
(författare)
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Cooling pitch cabinets in wind turbines using a pulsating heat pipe : A case study
- 2023
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Ingår i: Case Studies in Thermal Engineering. - : Elsevier Ltd. - 2214-157X. ; 50
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Tidskriftsartikel (refereegranskat)abstract
- As the electric capacity of wind turbine increases, heat dissipation in pitch cabinets becomes challenging owing to the limited space and rotating conditions. To cool down the pitch cabinet more effectively and allow heat dissipation, we designed and implemented a pulsating heat pipe (PHP) in this study. We designed PHP parameters and conducted performance tests to compare the cooling performance of the fabricated PHP with that of an air-based cooling system in a 1.5 MW wind turbine. The results demonstrated steady PHP operation under rotating conditions (17.3 rpm). At a heat load of 1000 W, the evaporator outlet temperature was only 76.1 °C. However, increasing the ambient temperature adversely affected PHP operation, resulting in higher temperature and thermal resistance. The heat-pipe-based cooling system lowered the insulated gate bipolar transistor (IGBT) temperature by about 20.4 °C in relation to the air-based cooling system, while being suitable under varied conditions. Additionally, the system could successfully operate when the heat load of IGBT was 2350 W, corresponding to a 7 MW electric capacity of the wind turbine. Reducing the manufacturing cost of the heat pipe would further enhance the applicability of this system for pitch cabinet IGBT cooling, such as decreasing payback period.
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| 3. |
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| 4. |
- Liu, L., et al.
(författare)
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Evaluating the benefits of Integrating Floating Photovoltaic and Pumped Storage Power System
- 2019
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Ingår i: Energy Conversion and Management. - : Elsevier Ltd. - 0196-8904 .- 1879-2227. ; 194, s. 173-185
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Tidskriftsartikel (refereegranskat)abstract
- Floating Photovoltaic systems have developed very fast in recent years. Compared to individual Floating Photovoltaic systems, further advantages, such as grid connectivity and energy storage, can be obtained when Floating Photovoltaic operates collaboratively with Pumped Storage Power Systems. This paper proposed an Integrated Floating Photovoltaic-Pumped Storage Power System and quantitatively assessed the potential of the integrated system in electricity generation and conservation of water and land resource. The study developed a coordinated operation model for the Integrated Floating Photovoltaic-Pumped Storage Power System, which employed a dual-objective optimization, namely to maximize the benefits of electricity generation and to minimize the energy imbalance at the same time. The dual-objective optimization was solved using the genetic algorithm method. Other benefits of the Integrated Floating Photovoltaic-Pumped Storage Power System, namely conservation of water and land resource, were also assessed. The proposed methodology was applied to a 2 GW Floating Photovoltaic farm and a 1 GW Pumped Storage Power System. Results indicated that the Integrated Floating Photovoltaic-Pumped Storage Power System has a great potential for gaining the benefits of electricity generation (9112.74 MWh in a typical sunny day averagely) and reducing energy imbalance (23.06 MW aggregately in one day). The coordinated operation provides the possibility to achieve a higher generation benefits without affecting the reliability of the grid, while the optimization method plays a key role of efficient coordination. In addition, the system would help to save 20.16 km 2 land and 19.06 million m 3 water a year due to the reduction in evaporation loss. The synthetic benefits greatly improve the economic and environmental feasibility of photovoltaic systems in reality.
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| 5. |
- Liu, L., et al.
(författare)
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Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model
- 2022
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Ingår i: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 247
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Tidskriftsartikel (refereegranskat)abstract
- Extreme electricity prices occur with a higher frequency and a larger magnitude in recent years. Accurate forecasting of the occurrence of extreme prices is of great concern to market operators and participants. This paper aims to forecast the occurrence probability of day-ahead extremely low and high electricity prices and investigate the relative importance of different influencing variables. The data obtained from the Australian National Electricity Market (NEM) were employed, including historical prices (one day before and one week before), reserve capacity, load demand, variable renewable energy (VRE) proportion and interconnector flow. A Multivariate Logistic Regression (MLgR) model was proposed, which showed good forecasting capability in terms of model fitness and classification accuracy with different thresholds of extreme prices. In addition, the performance of the MLgR model was verified by comparing with two other models, i.e., Multi-Layer Perceptron (MLP) and Radical Basis Function (RBF) neural network. Relative importance analysis was performed to quantify of the contribution of the variables. The proposed method enriches the theories of electricity price forecast and advances the understanding of the dynamics of extreme prices. By applying the model in practice, it will contribute to promoting the management of operation and establishment of a robust energy market.
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| 6. |
- Wei, P., et al.
(författare)
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Numerical study on thermal energy storage tube filled by metal foam with gradient porosities
- 2019
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Ingår i: IOP Conference Series. - : Institute of Physics Publishing.
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Konferensbidrag (refereegranskat)abstract
- Thermal energy storage has attracted more and more attentions due mainly to its ability of peak load shifting. Shell-and-tube configuration is a typical heat exchanger for thermal energy storage. To enhance phase change heat transfer, open-cell metal foam has been involved in various kinds of shell-and-tube heat exchangers. To further improve the overall thermal performance of a shell-and-tube heat exchanger, metal foams with gradient porosities were inserted into the shell side. Positive and negative gradients in porosity were studied for comparison. Numerical model was developed based on the finite volume method and three sets of numerical simulations were performed. Transient melting front and melting fraction were illustrated for comparison. Results demonstrated that the positive gradient in porosity outperformed the other two kinds of configurations, resulting in a 17.5% reduction in full melting time.
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| 7. |
- Zhao, R., et al.
(författare)
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Thermodynamic research of adsorbent materials on energy efficiency of vacuum-pressure swing adsorption cycle for CO2 capture
- 2018
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Ingår i: Applied Thermal Engineering. - : Elsevier Ltd. - 1359-4311 .- 1873-5606. ; 128, s. 818-829
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a comprehensive thermodynamic research on energy efficiency of vacuum-pressure swing adsorption (VPSA). The study examined the influence from four types of typical adsorbent materials on the energy efficiency of VPSA by cycle parameters. The selected adsorbent materials are activated carbons, zeolite 5A, zeolite 13X, silica gels, and metal-organic frameworks (MOFs). The study also analyzes the effects of separation temperature, adsorption pressure, desorption pressure, CO2 concentration and percent of unused bed on the energy-efficiency of VPSA cycle. The examined performance parameters are CO2 working capacity, proportionality factor, energy consumption and second-law efficiency. The results show that the energy consumption is approximately 2.0–4.5 MJ/kg and the second-law efficiencies are 4–7% for VPSA cycles using the five adsorbent materials. The effect of adsorbent materials on the energy efficiency mainly depends on the proportionality factor of CO2 working capacity (β) of VPSA cycle, which is important to screen materials at the fixed cyclic boundary conditions and preliminary calculation of second-law efficiency for VPSA cycles. For existing adsorbent materials which are Type I commonly, the lower values of β would lead to the higher second-law efficiencies. The development of new adsorbents of Type III would be extremely urgent in near future.
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