The enhanced power quality provided by multilevel inverters(MLIs)has made them more appropriate for medium-and high-power applications,including photovoltaic systems.Nevertheless,a prevalent limitation involves the ne...The enhanced power quality provided by multilevel inverters(MLIs)has made them more appropriate for medium-and high-power applications,including photovoltaic systems.Nevertheless,a prevalent limitation involves the necessity for numerous switches and increased voltage stress across these switches,consequently increasing the overall system cost.To address these challenges,a new 17-level asymmetrical MLI with fewer components and low voltage stress is proposed for the photovoltaic system.This innovative MLI configuration has four direct current(DC)sources and 10 switches.Based on the trinary sequence,the proposed topology uses photovoltaics with boost converters and fuzzy logic controllers as its DC sources.Mathematical equations are used to calculate cru-cial parameters for this proposed design,including total standing voltage per unit(TSVPU),cost function per level(CF/L),component count per level(CC/L)and voltage stress across the switches.The comparison is conducted by considering switches,DC sources,TSVPU,CF/L,gate driver circuits and CC/L with other existing MLI topologies.The analysis is carried out under various conditions,encompassing different levels of irradiance,variable loads and modulation indices.To reduce the total harmonic distortion of the suggested topology,the phase opposition disposition approach has been incorporated.The suggested framework is simulated in MATLAB®/Simulink®.The results indicate that the proposed topology achieves a well-distributed stress profile across the switches and has CC/L of 1.23,TSVPU of 5 and CF/L of 4.58 and 5.76 with weight coefficients of 0.5 and 1.5,respectively.These values are not-ably superior to those of existing MLI topologies.Simulation results demonstrate that the proposed topology maintains a consistent output at varying irradiance levels with FLCs and exhibits robust performance under variable loads and diverse modulation indices.Furthermore,the total harmonic distortion achieved with phase opposition disposition is 7.78%,outperforming alternative pulse width modulation techniques.In summary,it provides enhanced performance.Considering this,it is suitable for the photovoltaic system.展开更多
Accurate photovoltaic(PV)power prediction can effectively help the power sector to make rational energy planning and dispatching decisions,promote PV consumption,make full use of renewable energy and alleviate energy ...Accurate photovoltaic(PV)power prediction can effectively help the power sector to make rational energy planning and dispatching decisions,promote PV consumption,make full use of renewable energy and alleviate energy problems.To address this research objective,this paper proposes a prediction model based on kernel principal component analysis(KPCA),modified cuckoo search algorithm(MCS)and deep convolutional neural networks(DCNN).Firstly,KPCA is utilized to reduce the dimension of the feature,which aims to reduce the redundant input vectors.Then using MCS to optimize the parameters of DCNN.Finally,the photovoltaic power forecasting method of KPCA-MCS-DCNN is established.In order to verify the prediction performance of the proposed model,this paper selects a photovoltaic power station in China for example analysis.The results show that the new hybrid KPCA-MCS-DCNN model has higher prediction accuracy and better robustness.展开更多
文摘The enhanced power quality provided by multilevel inverters(MLIs)has made them more appropriate for medium-and high-power applications,including photovoltaic systems.Nevertheless,a prevalent limitation involves the necessity for numerous switches and increased voltage stress across these switches,consequently increasing the overall system cost.To address these challenges,a new 17-level asymmetrical MLI with fewer components and low voltage stress is proposed for the photovoltaic system.This innovative MLI configuration has four direct current(DC)sources and 10 switches.Based on the trinary sequence,the proposed topology uses photovoltaics with boost converters and fuzzy logic controllers as its DC sources.Mathematical equations are used to calculate cru-cial parameters for this proposed design,including total standing voltage per unit(TSVPU),cost function per level(CF/L),component count per level(CC/L)and voltage stress across the switches.The comparison is conducted by considering switches,DC sources,TSVPU,CF/L,gate driver circuits and CC/L with other existing MLI topologies.The analysis is carried out under various conditions,encompassing different levels of irradiance,variable loads and modulation indices.To reduce the total harmonic distortion of the suggested topology,the phase opposition disposition approach has been incorporated.The suggested framework is simulated in MATLAB®/Simulink®.The results indicate that the proposed topology achieves a well-distributed stress profile across the switches and has CC/L of 1.23,TSVPU of 5 and CF/L of 4.58 and 5.76 with weight coefficients of 0.5 and 1.5,respectively.These values are not-ably superior to those of existing MLI topologies.Simulation results demonstrate that the proposed topology maintains a consistent output at varying irradiance levels with FLCs and exhibits robust performance under variable loads and diverse modulation indices.Furthermore,the total harmonic distortion achieved with phase opposition disposition is 7.78%,outperforming alternative pulse width modulation techniques.In summary,it provides enhanced performance.Considering this,it is suitable for the photovoltaic system.
文摘Accurate photovoltaic(PV)power prediction can effectively help the power sector to make rational energy planning and dispatching decisions,promote PV consumption,make full use of renewable energy and alleviate energy problems.To address this research objective,this paper proposes a prediction model based on kernel principal component analysis(KPCA),modified cuckoo search algorithm(MCS)and deep convolutional neural networks(DCNN).Firstly,KPCA is utilized to reduce the dimension of the feature,which aims to reduce the redundant input vectors.Then using MCS to optimize the parameters of DCNN.Finally,the photovoltaic power forecasting method of KPCA-MCS-DCNN is established.In order to verify the prediction performance of the proposed model,this paper selects a photovoltaic power station in China for example analysis.The results show that the new hybrid KPCA-MCS-DCNN model has higher prediction accuracy and better robustness.
文摘[目的]随着光伏、储能、新型建材及装配式建筑产业的发展,将光伏组件与屋面、墙体、遮阳等构件进行一体化设计与制造的光伏建筑一体化(Building Integrated Photovoltaic,BIPV)技术开始延伸为光伏储能建筑一体化(Building Integrated Photovoltaic and Energy Storge,BIPVES)技术。[方法]文章提出世界首个可充电水泥电池,将建筑墙体与光伏发电装置、储放电装置相融合;对设备和材料进行跨界创新,在玻璃表面打印高清晰度、高透光率花纹图案,制造高效光伏建材;研发预制式储能墙体,与各类钢结构装配式建筑体系进行结合,实现订制式生产、装配式施工,形成建筑构件与光伏、储能一体化的变革趋势。[结果]水泥基电池实现了建筑墙体具有光伏发电、储电以及供电等多种功能;新一代光伏建材可节省建筑外立面装饰材料的成本,降低建筑物碳排放;光伏和储能等可再生能源技术在建筑中的一体化集成,可取得最大化收益。[结论]新型光伏建材技术和水泥电池等新型储能技术具有发展前景,将可充电电池构件、光伏外墙板与装配式建筑墙体及预埋件进行组合集成并推广应用具有可行性。
