| 1. |
- Rong, X., et al.
(author)
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Experimental study on a multi-evaporator mutual defrosting system for air source heat pumps
- 2023
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In: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 332
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Journal article (peer-reviewed)abstract
- Air source heat pumps (ASHPs) are prone to frost when heating in a low-temperature and high-humidity environment, which deteriorates the heating performance of the unit. In this study, a new multi-evaporator mutual defrosting (MEMD) system was proposed to overcome the disadvantages of traditional defrosting methods: intermittent heating and inefficient defrosting. To validate the performance of the proposed defrosting technology, comparative tests were conducted in various outdoor environmental conditions. The experimental results showed that the MEMD system could continuously heat water during the defrosting period. In five experimental conditions, the MEMD system exhibited a lower water temperature drop range (2.1–2.8 °C) than that of a traditional reverse-cycle defrosting (RCD) system (6.0–7.3 °C). Due to the effective utilization of heat production during the heating period, the effective heat power (qe) of the unit increased by 0.7–1.4 kW, and the heat loss coefficient (HLC) of frosting and defrosting increased by an average of 6 % in the five experimental conditions, effectively reducing the heating capacity loss of the unit caused by defrosting. While defrosting, the MEMD system was able to utilize the remaining evaporators to absorb heat from the air and then deliver it to the defrosting evaporator. The equivalent defrosting energy efficiency (COPd) of the MEMD system was 17.5 % greater than that of the RCD system on average. During the heating and defrosting cycle, the energy saved when defrosting could increase the cycle coefficient of performance (CCOP) of heating by 3.7 %.
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| 2. |
- Liu, L., et al.
(author)
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Forecasting Power Output of Photovoltaic System Using A BP Network Method
- 2017
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In: Energy Procedia. - : Elsevier Ltd. - 1876-6102. ; 142, s. 780-786
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Journal article (peer-reviewed)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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| 3. |
- Fatima, R., et al.
(author)
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Sharing information online rationally : An observation of user privacy concerns and awareness using serious game
- 2019
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In: Journal of Information Security and Applications. - : Elsevier Ltd. - 2214-2134 .- 2214-2126. ; 48
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Journal article (peer-reviewed)abstract
- Recent studies have shown that excessive online information disclosure is a major reason of privacy breach. It makes it easy for social engineers to gather information about their targets. The objective of this study is to gather user privacy concerns reported in the literature and categorize them into themes, then design a serious game covering the categorized privacy concerns and evaluate the educational effect of the game regarding dangers associated with excessive online information disclosure. We have conducted a literature review and extracted user privacy concerns reported in 109+ publications. Then we designed a serious game and empirically evaluated the game players awareness of dangers associated with excessive online information disclosure. We find that privacy awareness has a positive long-term impact on users online behavior in terms of controlled information sharing. However, social networking needs drive users to share information online, even knowing the potential risks. The proposed serious game shows positive effect in improving the privacy awareness of participants.
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| 4. |
- Liu, L., et al.
(author)
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Evaluating the benefits of Integrating Floating Photovoltaic and Pumped Storage Power System
- 2019
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In: Energy Conversion and Management. - : Elsevier Ltd. - 0196-8904 .- 1879-2227. ; 194, s. 173-185
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Journal article (peer-reviewed)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.
(author)
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Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model
- 2022
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In: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 247
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Journal article (peer-reviewed)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. |
- Wang, F., et al.
(author)
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Optimal design and operation of hybrid renewable energy system for drinking water treatment
- 2021
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In: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 219
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Journal article (peer-reviewed)abstract
- The industrial process of drinking water treatment requires intensive energy, leading to high enterprise costs and abundant carbon emissions. To ensure cost-effective and low polluting power supply for the above process, this paper proposes to deploy the grid-connected hybrid renewable system. A multi-objective nonlinear dynamic model mixed with integer variables is established for the decision makers, in which both system configurations and operations as well as benefits trade-offs from four dimensions are simultaneously considered. The ε-constraint method and system planner attitude parameters are introduced to transform the proposed model into its equivalent single objective form, which is further been solved by the LINGO software. A case study in China is given to assess the viability of the proposed model, in which optimal system configuration, economically feasible self-sufficiency ratio and optimal energy balance are obtained. Influences of electricity pricing strategies and natural resource changes on the systems are also analyzed and compared. It is found that the deployment of grid-connected hybrid wind/PV/storage system can help power users to cope with the future electricity price variation risks, with the feasible self-sufficiency ratio reaching 95%.
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