Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.

Comprehensive Benefit Evaluation of SZ Distributed Photovoltaic Power Generation Project Based on AHP-Matter-Element Extension Model

With the introduction of the“dual carbon goals,”there has been a robust development of distributed photovoltaic power generation projects in the promotion of their construction.As part of this initiative,a comprehensive and systematic analysis has been conducted to study the overall benefits of photovoltaic power generation projects.The evaluation process encompasses economic,technical,environmental,and social aspects,providing corresponding analysis methods and data references.Furthermore,targeted countermeasures and suggestions are proposed,signifying the research’s importance for the construction and development of subsequent distributed photovoltaic power generation projects.

Effect of Photovoltaic Power Generation on Carbon Dioxide Emission Reduction under Double Carbon Background

Increasing the efficiency and proportion of photovoltaic power generation installations is one of the best ways to reduce both CO_(2) emissions and reliance on fossil-fuel-based power supplies.Solar energy is a clean and renewable power source with excellent potential for further development and utilization.In 2021,the global solar installed capacity was about 749.7 GW.Establishing correlations between solar power generation,standard coal equivalent,carbon sinks,and green sinks is crucial.However,there have been few reports about correlations between the efficiency of tracking solar photovoltaic panels and the above parameters.This paper calculates the increased power generation achievable through the use of tracking photovoltaic panels compared with traditional fixed panels and establishes relationships between power generation,standard coal equivalent,and carbon sinks,providing a basis for attempts to reduce reliance on carbon-based fuels.The calculations show that power generation efficiency can be improved by about 26.12%by enabling solar panels to track the sun's rays during the day and from season to season.Through the use of this improved technology,global CO_(2) emissions can be reduced by 183.63 Mt,and the standard coal equivalent can be reduced by 73.67 Mt yearly.Carbon capture is worth approximately EUR 15.48 billion,and carbon accounting analysis plays a vital role in carbon trading.

Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete randomness.With the development of new energy economy,the proportion of photovoltaic energy increased accordingly.In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation,this paper proposes the short-termprediction of photovoltaic power generation based on the improvedmulti-scale permutation entropy,localmean decomposition and singular spectrum analysis algorithm.Firstly,taking the power output per unit day as the research object,the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions,and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy,sunny,abrupt,cloudy.Then,local mean decomposition(LMD)is used to decompose the output sequence,so as to extract more detail components of the reconstructed output sequence.Finally,combined with the weather forecast of the Meteorological Bureau for the next day,the singular spectrumanalysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather.Through the verification and analysis of examples,the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared.The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator,and has the advantages of simple structure and high prediction accuracy.

Solar Shutters based on Photovoltaic Power Generation

This paper introduces a set of electrical energy-saving system for commercial office buildings,aiming at making better use of solar energy and photovoltaic power generation.Solar energy is a renewable energy source,which is inexhaustible clean energy and has great commercial application value.Based on this fact,we plan to design a unique and novel solar shutter in combination with the daily observation and the shape of solar panels.The shutter blades are equipped with an automatic light tracking system,and the angle of the blades can be adjusted in time through photoresistor induction,that is,as much solar energy as possible can be converted into electric energy for load use,and at the same time,comfortable light can be provided for the house.In essence,the system is a small photovoltaic power generation system,which runs all day with high-efficiency based on automatic sun tracking.Among them,the basic operation route includes:solar position detection,computer data processing,photovoltaic and electric volt energy conversion,circuit connection,etc.From the current debugging results,the shutter has the characteristics of humanization,high efficiency,cleanliness and so on.Through this energy-saving system,we hope to maximize the use of solar energy in the premise of low cost,so as to achieve the purpose of energy saving.

Analysis and Modeling of Time Output Characteristics for Distributed Photovoltaic and Energy Storage

Due to the unpredictable output characteristics of distributed photovoltaics,their integration into the grid can lead to voltage fluctuations within the regional power grid.Therefore,the development of spatial-temporal coordination and optimization control methods for distributed photovoltaics and energy storage systems is of utmost importance in various scenarios.This paper approaches the issue from the perspective of spatiotemporal forecasting of distributed photovoltaic(PV)generation and proposes a Temporal Convolutional-Long Short-Term Memory prediction model that combines Temporal Convolutional Networks(TCN)and Long Short-Term Memory(LSTM).To begin with,an analysis of the spatiotemporal distribution patterns of PV generation is conducted,and outlier data is handled using the 3σ rule.Subsequently,a novel approach that combines temporal convolution and LSTM networks is introduced,with TCN extracting spatial features and LSTM capturing temporal features.Finally,a real spatiotemporal dataset from Gansu,China,is established to compare the performance of the proposed network against other models.The results demonstrate that the model presented in this paper exhibits the highest predictive accuracy,with a single-step Mean Absolute Error(MAE)of 1.782 and an average Root Mean Square Error(RMSE)of 3.72 for multi-step predictions.

Maximum power point tracking of photovoltaic power generation based on improved fuzzy control and conductance increment method

The National Development and Reform Commission of China announced in 2022 that it would promote the development of carbon peaking and carbon-neutrality.Therefore,gradual improvement in photovoltaic(PV)development technology would gradually show its advantages.Additionally,the development of the PV power generation industry is promoted significantly by the year-on-year increase in PV power generation.This study combines the traditional fuzzy control and incremental conductance methods by comparing the current maximum power point(MPP)intelligence with the traditional control algorithm.Furthermore,it proposes an optimization algorithm to improve the tracking speed of the MPP by using the partition variable step size.An incomplete partial differential equation is added to the judgment condition of the small step size to solve the problem of oscillation near the MPP caused by the ideal differential equation.A simulation model is established in MATLAB®/Simulink®and the method is simulated under specific conditions.The time to reach the first maximum output point is shortened by 0.21 and 0.14 s by analysing the oscillation process data of three simulation cycles of the incremental conductance,fuzzy control and fuzzy conductance methods,respectively.Additionally,the vibration loss caused by environmental mutation is reduced by 6.5%and 3.1%,respectively.The improved incremental conductance method utilizes the simulation results to optimize the problem of steady-state oscillation and improve the efficiency of the PV power generation.The feasibility and effectiveness of the improved incremental conductance method are verified by comparing the traditional control algorithm with the improved incremental conductance method.

Effect of photovoltaic panel electric field on the wind speed required for dust removal from the panels

Methods to remove dust deposits by high-speed airflow have significant potential applications,with optimal design of flow velocity being the core technology.In this paper,we discuss the wind speed required for particle removal from photovoltaic(PV)panels by compressed air by analyzing the force exerted on the dust deposited on inclined photovoltaic panels,which also included different electrification mechanisms of dust while it is in contact with the PV panel.The results show that the effect of the particle charging mechanism in the electric field generated by the PV panel is greatly smaller than the effect of the Van der Waals force and gravity,but the effect of the particle charged by the contact electrification mechanism in the electrostatic field is very pronounced.The wind speed required for dust removal from the PV panel increases linearly with the PV panel electric field,so we suggest that the nighttime,when the PV electric field is relatively small,would be more appropriate time for dust removal.The above results are of great scientific importance for accurately grasping the dust distribution law and for achieving scientific removal of dust on PV panels.

Analysis of Current Research and Future Development Trends of Applying Solar Energy in Street Lighting

In the context of promoting green energy transition and addressing climate change globally,solar energy,as a clean and renewable energy source,has gradually become a hot topic for research.Solar streetlight systems realize energy self-sufficiency and environment-friendly lighting by integrating photovoltaic power generation technology and efficient LED lighting technology.By comprehensively analyzing the current status of the application of solar streetlights at home and abroad,this paper discusses its technical advantages,market penetration,and challenges in its development.In terms of technical characteristics,this paper focuses on analyzing the key technologies such as energy conversion efficiency and intelligent control systems of solar streetlights.

Dust Deposition’s Effect on Solar Photovoltaic Module Performance:An Experimental Study in India’s Tropical Region

A solar PV panel works with maximum efficiency only when it is operated around its optimum operating point or maximum power point.Unfortunately,the performance of the solar cell is affected by several factors like sun direction,solar irradiance,dust accumulation,module temperature,as well as the load on the system.Dust deposition is one of the most prominent factors that influence the performance of solar panels.Because the solar panel is exposed to the atmosphere,dust will accumulate on its surface,reducing the quantity of sunlight reaching the solar cell and diminishing output.In the proposed work,a detailed investigation of the performance of solar PV modules is carried out under the tropical climatic condition of Chennai,India,where the presence of dust particles is very high.The data corresponding to four different dust samples of various densities at four solar irradiation levels of 220,525,702,and 905 W/m^(2)are collected,and performance analysis is carried out.Based on the analysis carried out,the maximum power loss is found to be 73.51%,66.29%,65.46%,and 61.42%,for coal,sand,brick powder,and chalk dust respectively.Hence,it can be said that coal dust contributes to the maximum power loss among all four dust samples.Due to heat dissipation produced by dust deposition,the performance of solar PV modules is degraded as the temperature rose.

Power Output Improvement of PV Module for Agricultural Use by Using Inexpensive Sunlight Concentrator

PV modules are used as stand alone power sources for agricultural equipments such as lifting pumps in farms, where the power infrastructure is not yet improved. In order to expand the agricultural use of PV module, the cost of PV generation should be reduced. In this paper, the power output performance of a commercial PV module was improved by using a sunlight concentrator that could be assembled inexpensively and a simple sun-tracking method.

Review of Photovoltaic Cell Technology Development

China has pledged to peak its carbon footprint by 2030 and become carbon neutral by 2060. According to the future energy demand and the requirement to achieve “carbon neutrality”, the new energy represented by photovoltaic power generation will become the main force to achieve “carbon neutrality”. It is great strategic significant to increase the proportion of non-carbon energy gradually and build a new energy supply system with multiple complementary energy. According to the current situation of domestic energy development in recent years and the development trend of new energy in China, the author reviewed the development of photovoltaic cells technology. As the head industry of photovoltaic industry, photovoltaic cells were applied in multy prospects, such as agriculture and public transportation. Two feasible solutions toward the disadvantage of photovoltaic cell were discussed, including the appropriate geographical location of photovoltaic cells and the superhydrophobic coating on the surface of the cell.

Short-term Photovoltaic Power Forecasting Using SOM-based Regional Modelling Methods

The inherent intermittency and uncertainty of photovoltaic(PV)power generation impede the development of grid-connected PV systems.Accurately forecasting PV output power is an effective way to address this problem.A hybrid forecasting model that combines the clustering of a trained self-organizing map(SOM)network and an optimized kernel extreme learning machine(KELM)method to improve the accuracy of short-term PV power generation forecasting are proposed.First,pure SOM is employed to complete the initial partitions of the training dataset;then the fuzzy c-means(FCM)algorithm is used to cluster the trained SOM network and the Davies-Bouldin index(DBI)is utilized to determine the optimal size of clusters,simultaneously.Finally,in each data partition,the clusters are combined with the KELM method optimized by differential evolution algorithm to establish a regional KELM model or combined with multiple linear regression(MR)using least squares to complete coefficient evaluation to establish a regional MR model.The proposed models are applied to one-hour-ahead PV power forecasting instances in three different solar power plants provided by GEFCom2014.Compared with other single global models,the root mean square errors(RMSEs)of the proposed regional KELM model are reduced by 52.06%in plant 1,54.56%in plant 2,and 51.43%in plant 3 on average.Such results demonstrate that the forecasting accuracy has been significantly improved using the proposed models.In addition,the comparisons between the proposed and existing state-of-the-art forecasting methods presented have demonstrated the superiority of the proposed methods.The forecasts of different methods in different seasons revealed the strong robustness of the proposed method.In four seasons,the MAEs and RMSEs of the proposed SF-KELM are generally the smallest.Moreover,the R2 value exceeds 0.9,which is the closest to 1.

Economic analysis of solar energy development in North Africa

The economic analysis of solar energy development is the basis of promoting the solar energy planning in north Africa and realizing the clean energy power transmission among continents. In this paper, the cost development trend of photovoltaic(PV) power and concentrating solar power(CSP) generation is analyzed, and the levelized cost of energy(LCOE) of solar power generation is forecasted. Then, taking the development of Tunisian solar energy as an example in the context of transcontinental transmission, PV power with energy storage and PV-CSP power generation are given as two kinds of development plan respectively. The installed capacity configurations of the two schemes are given with production simulation method, and comprehensive LCOE are calculated. The studies show that based on the LCOE forecast value, the LCOE of PV-CSP combined power generation will decrease when the annual utilization hours of transmission channel is increased. It can be chosen as one of important mode of the North Africa solar energy development.

《光伏发电系统接入配电网技术规定》标准解读和修订建议

In the context of clean and Low-carbon energy transformation and new power system,China^photovoltaic power generation will usher in great development.Its large-scale access impacts the safe and stable operation of the power grid with increasing significance.In order to strengthen the support and Leading roles of the standards,it is urgent to revise the national standard GB/T 29319-2012,Technical requirements for connecting photovoltaic power system to distribution network,based on the current development trend of photovoltaic power generation and power grid transformation needs.This paper firstly interprets the important technical provisions of the standard,then analyzes the problems in its implementation and finally proposes some revision suggestions in terms of grid adaptability,power control and fault crossing,to facilitate safe and orderly development of photovoltaic power generation in China.

A maximum power point tracking strategy applied to building integrated photovoltaics

To solve the problem of permanent-shadow shading of photovoltaic buildings,a maximum power point tracking(MPPT)strategy to determine the search range by pre-delimiting area is proposed to improve MPPT efficiency.The single correspondence between the solar-cell current-voltage(I-V)curve and the illumination conditions was proved by using the single-diode model of photovoltaic cells,thus proving that a change in the illumination conditions corresponds to a unique maximum power point(MPP)search area.According to the approximate relationship between MPP voltage,current and open-circuit voltage and short-circuit current of a photovoltaic module,the voltage region where the MPP is located is determined and the global maximum power point is determined using the power operating triangle strategy in this region.Simulation carried out in MATLAB proves the correctness and feasibility of the theoretical research.Simulation results show that the MPPT strategy proposed in this paper can improve the average efficiency by 1.125%when applied in series as building integrated photovoltaics.

A Simulation Research on the Grid-Connected Control Technology of Single-Phase Inverters Based on MATLAB

This paper primarily discusses the main circuit of single-phase inverter circuits.It begins by introducing the research context and the significance of the subject,then discusses the topology of grid-connected single-phase inverter circuits,continues by discussing the control strategy for grid-connected single-phase inverter circuits,realizes a sinusoidal pulse width modulation(SPWM)signal generation circuit and an inverse control algorithm program,and finally ensures good output waveform and fast dynamic response.In view of the hysteresis feature of the grid voltage’s synchronous signal sampling circuit,the acquisition function in digital signal processing(DSP)control chips is applied,and the reasons for the hysteresis phenomenon are thoroughly investigated.The reliability of the SPWM control algorithm is revealed through the results.

Research on Green Transformation of Campus Sponge and Energy Saving Facilities on Sloping Land

Based on the renovation of sponge and energy-saving facilities in a middle school in Nanning,this paper systematically studies the overall elevation of the campus,the composition of the drainage system and the layout of space functions,and formulates a characteristic scheme for the renovation of sponge and energy-saving facilities according to the characteristics of the sloping campus.In order to control the total amount of rainwater runoff,the sponge transformation mainly adopts the transformation methods of partition catchment,upper storage and lower use,multi-stage detection and classification treatment.For the purpose of solar energy and wind energy utilization,solar photovoltaic panels and small-scale wind power generation system are adopted.The application effects of sponge and energy-saving facilities are estimated and evaluated.

Design of multi-passband polymer multilayer film and its application in photovoltaic agriculture

To solve the issue of the contradiction between photovoltaic power generation and plant photosynthesis for sunlight demand, we propose a design method of multi-passband polymer multilayer optical structure. Using polycarbonate(PC) and polymethyl methacrylate(PMMA), two polymer materials with different refractive indices, the passband position and passband bandwidth are calculated and adjusted by the transmission matrix method and TFCalc software. A 450 nm,660 nm, and 730 nm three-passband filter was realized by superimposing stacks of different band positions. The feasibility of the photovoltaic agriculture was confirmed by the power generation efficiency and the actual plant growth.