为研究太阳能PV/T热电联供系统的性能和针对太阳能PV/T系统复杂的能量平衡方程,搭建了太阳能PV/T系统试验台,同时建立了基于改进灰狼优化的BP神经网络(back propagation neural network model based on improved grey wolf algorithm,IG...为研究太阳能PV/T热电联供系统的性能和针对太阳能PV/T系统复杂的能量平衡方程,搭建了太阳能PV/T系统试验台,同时建立了基于改进灰狼优化的BP神经网络(back propagation neural network model based on improved grey wolf algorithm,IGWO-BP)预测模型,在晴朗天气下进行试验,并采用该模型对系统电功率以及蓄热水箱内水温进行预测。结果显示,晴朗日系统的电效率8.7%~12.2%、热效率51.7%;预测结果与BP神经网络预测模型、基于粒子群优化的BP神经网络(back propagation neural network based on particle swarm optimization,PSO-BP)预测模型和卷积神经网络(convolutional neural network,CNN)预测模型预测结果进行比较,结果显示IGWO-BP预测模型电效率预测模型的绝对百分比误差(mean absolute percentage error,MAPE)、决定系数(determination coefficient,R^(2))、均方根误差(root mean square error,RMSE)、效率因子(efficient factor,EF)和Pearson相关系数(pearson related coefficient,r)分别为4.5E-05、0.99、0.24、0.99和1.00,在储热罐温度预测中,上述指标分别为8.90E-04、0.98、0.07、0.98、0.99,均优于其他预测模型,IGWO-BP神经网络预测模型具有更好的预测性能。研究结果可为太阳能PV/T热电联供系统性能预测与优化控制提供参考。展开更多
The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs ...The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.展开更多
The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although ...The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.展开更多
To analyze the additional cost caused by the performance attenuation of a proton exchange membrane electrolyzer(PEMEL)under the fluctuating input of renewable energy,this study proposes an optimization method for powe...To analyze the additional cost caused by the performance attenuation of a proton exchange membrane electrolyzer(PEMEL)under the fluctuating input of renewable energy,this study proposes an optimization method for power scheduling in hydrogen production systems under the scenario of photovoltaic(PV)electrolysis of water.First,voltage and performance attenuation models of the PEMEL are proposed,and the degradation cost of the electrolyzer under a fluctuating input is considered.Then,the calculation of the investment and operating costs of the hydrogen production system for a typical day is based on the life cycle cost.Finally,a layered power scheduling optimization method is proposed to reasonably distribute the power of the electrolyzer and energy storage system in a hydrogen production system.In the up-layer optimization,the PV power absorbed by the hydrogen production system was optimized using MALTAB+Gurobi.In low-layer optimization,the power allocation between the PEMEL and battery energy storage system(BESS)is optimized using a non-dominated sorting genetic algorithm(NSGA-Ⅱ)combined with the firefly algorithm(FA).A better optimization result,characterized by lower degradation and total costs,was obtained using the method proposed in this study.The improved algorithm can search for a better population and obtain optimization results in fewer iterations.As a calculation example,data from a PV power station in northwest China were used for optimization,and the effectiveness and rationality of the proposed optimization method were verified.展开更多
对于光伏阵列而言,阴影遮挡和阵列损坏会导致其输出功率降低。为了提升光伏阵列的输出功率,提出了一种优化的奇偶重构方法(Optimized Odd Even Configuration,OOEC),纠正了奇偶重构法(Odd Even Configuration,OEC)在局部阴影超过4列时,...对于光伏阵列而言,阴影遮挡和阵列损坏会导致其输出功率降低。为了提升光伏阵列的输出功率,提出了一种优化的奇偶重构方法(Optimized Odd Even Configuration,OOEC),纠正了奇偶重构法(Odd Even Configuration,OEC)在局部阴影超过4列时,重构效果差的缺点。所提出的方法将光伏阵列分为自由重构模块和固定重构模块,根据不同的阴影情况调整连接方式,确定最佳的连接关系,并与Arrow So Du ku,Zig-zag,OEC三种方法进行仿真实验对比,仿真结果表明,经过OOEC重构后的光伏阵列输出功率明显提高,光伏阵列的PU输出特性曲线更加趋向于单峰,并且从失配损耗,功率提升百分比,性能比,均衡指数上看来,OOEC有着更好的性能。展开更多
文摘为研究太阳能PV/T热电联供系统的性能和针对太阳能PV/T系统复杂的能量平衡方程,搭建了太阳能PV/T系统试验台,同时建立了基于改进灰狼优化的BP神经网络(back propagation neural network model based on improved grey wolf algorithm,IGWO-BP)预测模型,在晴朗天气下进行试验,并采用该模型对系统电功率以及蓄热水箱内水温进行预测。结果显示,晴朗日系统的电效率8.7%~12.2%、热效率51.7%;预测结果与BP神经网络预测模型、基于粒子群优化的BP神经网络(back propagation neural network based on particle swarm optimization,PSO-BP)预测模型和卷积神经网络(convolutional neural network,CNN)预测模型预测结果进行比较,结果显示IGWO-BP预测模型电效率预测模型的绝对百分比误差(mean absolute percentage error,MAPE)、决定系数(determination coefficient,R^(2))、均方根误差(root mean square error,RMSE)、效率因子(efficient factor,EF)和Pearson相关系数(pearson related coefficient,r)分别为4.5E-05、0.99、0.24、0.99和1.00,在储热罐温度预测中,上述指标分别为8.90E-04、0.98、0.07、0.98、0.99,均优于其他预测模型,IGWO-BP神经网络预测模型具有更好的预测性能。研究结果可为太阳能PV/T热电联供系统性能预测与优化控制提供参考。
基金the financial support provided by Universiti Malaysia Pahang Al Sultan Abdullah(www.umpsa.edu.my,accessed 10 April 2024)through the Doctoral Research Scheme(DRS)toMr.Rittick Maity and the Postgraduate Research Scheme(PGRS220390).
文摘The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.
文摘The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.
基金supported by the National Key Research and Development Program of China(Materials and Process Basis of Electrolytic Hydrogen Production from Fluctuating Power Sources such as Photovoltaic/Wind Power,No.2021YFB4000100)。
文摘To analyze the additional cost caused by the performance attenuation of a proton exchange membrane electrolyzer(PEMEL)under the fluctuating input of renewable energy,this study proposes an optimization method for power scheduling in hydrogen production systems under the scenario of photovoltaic(PV)electrolysis of water.First,voltage and performance attenuation models of the PEMEL are proposed,and the degradation cost of the electrolyzer under a fluctuating input is considered.Then,the calculation of the investment and operating costs of the hydrogen production system for a typical day is based on the life cycle cost.Finally,a layered power scheduling optimization method is proposed to reasonably distribute the power of the electrolyzer and energy storage system in a hydrogen production system.In the up-layer optimization,the PV power absorbed by the hydrogen production system was optimized using MALTAB+Gurobi.In low-layer optimization,the power allocation between the PEMEL and battery energy storage system(BESS)is optimized using a non-dominated sorting genetic algorithm(NSGA-Ⅱ)combined with the firefly algorithm(FA).A better optimization result,characterized by lower degradation and total costs,was obtained using the method proposed in this study.The improved algorithm can search for a better population and obtain optimization results in fewer iterations.As a calculation example,data from a PV power station in northwest China were used for optimization,and the effectiveness and rationality of the proposed optimization method were verified.
文摘对于光伏阵列而言,阴影遮挡和阵列损坏会导致其输出功率降低。为了提升光伏阵列的输出功率,提出了一种优化的奇偶重构方法(Optimized Odd Even Configuration,OOEC),纠正了奇偶重构法(Odd Even Configuration,OEC)在局部阴影超过4列时,重构效果差的缺点。所提出的方法将光伏阵列分为自由重构模块和固定重构模块,根据不同的阴影情况调整连接方式,确定最佳的连接关系,并与Arrow So Du ku,Zig-zag,OEC三种方法进行仿真实验对比,仿真结果表明,经过OOEC重构后的光伏阵列输出功率明显提高,光伏阵列的PU输出特性曲线更加趋向于单峰,并且从失配损耗,功率提升百分比,性能比,均衡指数上看来,OOEC有着更好的性能。
