A Distributed Photovoltaics Ordering Grid-Connected Method for Analyzing Voltage Impact in Radial Distribution Networks

In recent years,distributed photovoltaics(DPV)has ushered in a good development situation due to the advantages of pollution-free power generation,full utilization of the ground or roof of the installation site,and balancing a large number of loads nearby.However,under the background of a large-scale DPV grid-connected to the county distribution network,an effective analysis method is needed to analyze its impact on the voltage of the distribution network in the early development stage of DPV.Therefore,a DPV orderly grid-connected method based on photovoltaics grid-connected order degree(PGOD)is proposed.This method aims to orderly analyze the change of voltage in the distribution network when large-scale DPV will be connected.Firstly,based on the voltagemagnitude sensitivity(VMS)index of the photovoltaics permitted grid-connected node and the acceptance of grid-connected node(AoGCN)index of other nodes in the network,thePGODindex is constructed to determine the photovoltaics permitted grid-connected node of the current photovoltaics grid-connected state network.Secondly,a photovoltaics orderly grid-connected model with a continuous updating state is constructed to obtain an orderly DPV grid-connected order.The simulation results illustrate that the photovoltaics grid-connected order determined by this method based on PGOD can effectively analyze the voltage impact of large-scale photovoltaics grid-connected,and explore the internal factors and characteristics of the impact.

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.

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

Discussion on the Soil and Water Conservation Model in Mountain Photovoltaic Power Generation Project

In the context of rising global energy demand and increasing awareness of environmental protection,photovoltaic power generation,as a clean and renewable form of energy,has become increasingly important and has received widespread attention and application worldwide.However,during the construction and operation of mountain photovoltaic power generation projects,water and soil erosion has become a major challenge,which not only restricts the sustainable development process of the project,but also has a significant negative impact on the local ecological environment.This article deeply analyzes the multiple causes,extensive impacts and effective prevention and control strategies of water and soil erosion in mountain photovoltaic power generation projects.The results show that rainfall intensity,terrain slope,soil type and vegetation coverage are the four key factors leading to soil erosion.Soil erosion not only causes a sharp decline in soil fertility,but also aggravates the problem of sediment deposition in rivers and reservoirs,and poses a direct threat to the stability and operating efficiency of photovoltaic equipment.In order to deal with the above problems,this paper innovatively puts forward a series of soil and water conservation technologies,covering multiple dimensions such as engineering measures,plant measures,farming measures and temporary measures,and deeply discusses the application models and management strategies of these measures in key stages such as planning and design,construction,operation and maintenance.Through specific case analysis,the successful practical experience of soil and water conservation is refined and summarized,and the key role of community cooperation,technical support and modern monitoring technology in preventing and controlling soil and water erosion is further emphasized.This article aims to achieve a win-win situation of ecological environment protection and energy development and utilization through scientific planning and effective governance,and contribute to the construction of a green,low-carbon,and sustainable energy system.

Research on the Application of New Energy Photovoltaic Power Generation Technology

With the rapid development of technology and economy,the demand for energy in society is increasing.People are gradually realizing that fossil energy is limited,and the development of new energy may also face situations where it cannot meet social needs.The problem of resource shortage is gradually exposed to people.Therefore,the development of usable new energy has become an urgent problem for society to solve.At present,electricity is the most widely used energy source worldwide and photovoltaic power generation technology is gradually becoming well-known.As an emerging industry,the development of photovoltaic power generation still requires continuous promotion by national and social policies to be extended to various industries and ensure the stability of its energy supply.This article mainly outlines the principles,characteristics,and advantages of photovoltaic power generation,and briefly explains the current technology types and application aspects of photovoltaic power generation to contribute to its promotion and better serve all aspects of social life with new energy.

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.

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.

Economic Evaluation Method of Photovoltaic Power Generation Installed in Ordinary Homes

This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following three points: 1) This method determines the profit and loss and payback period in order to evaluate the installation of photovoltaic power generation, taking into account the price of equipment, solar battery module conversion efficiency, subsidy, electricity purchase price, service life and rate for selling electricity. 2) The proposed evaluation method was applied to Kanagawa Prefecture in Japan, providing plural scenarios. Using a solar battery module conversion efficiency of more than 15%, it is possible to make the payback period shorter than the 20-year service life and anticipate a profit in almost the whole area. 3) The areas suitable for photovoltaic power generation are Kawasaki City and Ninomiya-machi. It is necessary to adopt measures to increase the subsidy and install photovoltaic power generating systems in specific places in areas where subsidies are not provided in enough amounts.

Preliminary Feasibility Study on Application of Very Large Scale-Photovoltaic Power Generation in China

Some energy experts believe that solar energy photovoltaic power generation is hopeful to be applied in a large amount and possesses a certain proportion in the structure of energy in the future. In this paper, based on the forecasting of electric load demand and energy structure of power generation in the middle of 21 century, the pictures of VLS-PV power genera- tion is composed, the operation characteristic of VLS-PV power generation and the adaptability of electric power grid for it is analyzed, the ways for transmitting large amount of PV power and the economic and technical bottlenecks for applying VLS-PV power generation are discussed. Finally, the steps and suggestions for developing VLS-PV power generation and its electric power system in China are proposed.

High Efficiency PCS with Scan-Type MPPT Control for a Grid-Connected PV Power Generation System

For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection interval control that operates at specified intervals and monitors the maximum power point. The author has obtained satisfactory results using this new MPPT control method. This paper investigates the application of the new MPPT control method for a PCS （power conditioning system） in a grid-connected type PV power generation system. The experimental results clearly demonstrate that the developed PCS offers outstanding effectiveness in tracking the maximum power point in partially shaded environments.

Forecast of Power Generation for Grid-Connected Photo-voltaic System Based on Grey Theory and Verification Model

Being photovoltaic power generation affected by radiation strength, wind speed, clouds cover and environment temperature, the generating in each moment is fluctuating. The operational characteristics of grid-connected PV systems are coincided with gray theory application conditions. A gray theory model has been applied in short-term forecast of grid-connected photovoltaic system. The verification model of the probability of small error will help to check the accuracy of the gray forecast results. The calculated result shows that the ?model accuracy has been greatly enhanced.

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.

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.

PSO-BP-Based Optimal Allocation Model for Complementary Generation Capacity of the Photovoltaic Power Station

To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed.Particle Swarm Optimization and BP neural network are used to establish the forecasting model,the Markov chain model is used to correct the forecasting error of the model,and the weighted fitting method is used to forecast the annual load curve,to complete the optimal allocation of complementary generating capacity of photovoltaic power stations.The experimental results show that thismethod reduces the average loss of photovoltaic output prediction,improves the prediction accuracy and recall rate of photovoltaic output prediction,and ensures the effective operation of the power system.

Evaluation of the Performances of the First Grid-Connected Photovoltaic System in Sénégal

This document presents the evaluation and the monitoring of the performances of the first grid-connected photovoltaic system installed in the Center of Studies and Researches on the Renewable Energies (CERER) inaugurated on December 4th, 2012 by the governmental authorities of Senegal and Tenerife. This mini power plant of 3.15 kWc is a perfect example of the political will of the government which is to reduce the production cost of the electricity, with the diversification of the sources of production, and the greater use of the other sources such as the natural gas, the coal, the renewable energies. The evaluation of the performances of the installation is realized by using the indicators of efficiency and performance as the photovoltaic surface yield, the ratio of photovoltaic performance, the photovoltaic specific yield, and the losses of captures. The obtained results show that a big part of the energy shone during the period of observation was not able to be used further to circumstances such as the losses of conductivity, the heat losses or for example the defects on components. The analysis also shows that a large part of the produced energy is not injected because of the dilapidation of the network, the defects of landing but especially one disjunction sees frequently at the level of the point of injection.

Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods

With the increasing proportion of renewable energy in China’s energy structure,among which photovoltaic power generation is also developing rapidly.As the photovoltaic(PV)power output is highly unstable and subject to a variety of factors,it brings great challenges to the stable operation and dispatch of the power grid.Therefore,accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy.Currently,the short-term prediction of PV power has received extensive attention and research,but the accuracy and precision of the prediction have to be further improved.Therefore,this paper reviews the PV power prediction methods from five aspects:influencing factors,evaluation indexes,prediction status,difficulties and future trends.Then summarizes the current difficulties in prediction based on an in-depth analysis of the current research status of physical methods based on the classification ofmodel features,statistical methods,artificial intelligence methods,and combinedmethods of prediction.Finally,the development trend ofPVpower generation prediction technology and possible future research directions are envisioned.

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.

Coordinated control strategy for a PV-storage grid-connected system based on a virtual synchronous generator

Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage units.Most of the structures combined with energy storage are used as the DC side.At the same time,virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation.For the PV-storage grid-connected system based on virtual synchronous generators,the existing control strategy has unclear function allocation,fluctuations in photovoltaic inverter output power,and high requirements for coordinated control of PV arrays,energy storage units,and photovoltaic inverters,which make the control strategy more complicated.In order to solve the above problems,a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed.In this strategy,the energy storage unit implements maximum power point tracking,and the photovoltaic inverter implements a virtual synchronous generator algorithm,so that the functions implemented by each part of the system are clear,which reduces the requirements for coordinated control.At the same time,the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter.The simulation validates the effectiveness of the proposed method from three aspects:grid-connected operating conditions,frequency-modulated operating conditions,and illumination sudden-drop operating condition.Compared with the existing control strategies,the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.

Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).

Performance on Power,Hot and Cold Water Generation of a Hybrid Photovoltaic Thermal Module

This paper proposed a new function of photovoltaic thermal(PVT)module to produce nocturnal cool water not just only generating electrical power and hot water during daytime.Experimental tests were carried out under Chiang Mai tropical climate with a 200 Wp monocrystalline PVT module having dimensions of 1.601 m×0.828 m connected with two water tanks each of 60 L taken for hot and cool water storages.The module was facing south with 18o inclination.The electrical load was a 200 W halogen lamp.From experiments,by taking the module as a nocturnal radiative cooling surface,the cool water temperature in the cool storage tank could be reduced 2℃–3℃each night and the temperature could be reduced from 31.5℃to 22.1℃within 4 consecutive days.The cool water at approximately 23℃was also used to cool down the PVT module from noon when the PVT module temperature was rather high,and then the module temperature immediately dropped around 5℃and approximately 10%increase of electrical power could be achieved.A set of mathematical models was also developed to predict the PVT module temperature and the hot water temperature including the cool water temperature in the storage tanks during daytime and nighttime.The simulated results agreed well with the experimental data.