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.

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.

Case-specificity and Its Implications in Distribution Network Analysis with Increasing Penetration of Photovoltaic Generation

Distribution system analysis(DSA)currently faces several challenges due to inclusion of distributed energy resources(DERs),which have many characteristics,such as inherent variability,uncertainty,possibility of flexible four quadrant converter operations with distributed generation(DG),and the need for efficient operations to improve reliability of the supply system.This article argues for a high degree of case-specificity and discusses its implications in distribution networks with increasing DG penetration.The research is based on the exhaustive yearly simulation analyses of 132 candidate scenarios and investigates the effects of feeder-specific factors,such as geo-electric size and feeder spread,load density,and phase unbalancing.Nineteen(19)feeder variants—with phase-domain detailed modeling of all feeder components,including DGs,are subjected to increasing penetration of photovoltaic generation without altering the type and location of DGs.The objective is to analyze the role of feederspecific factors on feeder response characteristics in terms of annualized operational parameters,such as energy losses,feeder voltage profile,average power factor,and peak demand at a substation node,as well as tap-changer operations of voltage regulating equipment and their interaction with shunt compensation.Recorded annual load profiles—industrial,commercial,and residential—as well as location specific weather data are used to simulate the candidate scenarios based on three IEEE test feeders and one actual spot network in India.Results signify the consideration of feeder-specific factors in the planning exercise of grouping“similar”feeders for formulating the strategies that can improve daily operations of distribution feeders.The demonstrated case-specificity also implies that optimization algorithms for improved operations with DGs will need to be based on an integrated approach that accounts for feeder-specific factors as well as cyclic variability of DERs.

Evaluation of High Step-up Power Conversion Systems for Large-capacity Photovoltaic Generation Integrated into Medium Voltage DC Grids

With the increase of dc based renewable energy generation and dc loads,the medium voltage dc(MVDC)distribution network is becoming a promising option for more efficient system integration.In particular,large-capacity photovoltaic(PV)-based power generation is growing rapidly,and a corresponding power conversion system is critical to integrate these large PV systems into MVDC power grid.Different from traditional ac grid-connected converters,the converter system for dc grid interfaced PV system requires large-capacity dc conversion over a wide range of ultra-high voltage step-up ratios.This is an important issue,yet received limited research so far.In this paper,a thorough study of dc-dc conversion system for a medium-voltage dc grid-connected PV system is conducted.The required structural features for such a conversion system are first discussed.Based on these features,the conversion system is classified into four categories by series-parallel connection scheme of power modules.Then two existing conversion system configurations as well as a proposed solution are compared in terms of input/output performance,conversion efficiency,modulation method,control complexity,power density,reliability,and hardware cost.In-depth analysis is carried out to select the most suitable conversion systems in various application scenarios.

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).

Energy Loss Analysis of Distributed Rooftop Photovoltaics in Industrial Parks

The analysis of the loss of distributed photovoltaic power generation systems involves the interests of energy users,energy-saving service companies,and power grid companies,so it has always been the focus of the industry and society in some manner or another.However,the related analysis for an actual case that considers different cooperative corporations’benefits is lacking in the presently available literature.This paper takes the distributed rooftop photovoltaic power generation project in an industrial park as the object,studies the analysis and calculation methods of line loss and transformer loss,analyzes the change of transformer loss under different temperatures and different load rates,and compares the data and trend of electricity consumption and power generation in industrial parks before and after the photovoltaic operation.This paper explores and practices the analysis method of the operating loss of distributed photovoltaic power generation and provides an essential reference for the benefit analysis and investment cost estimation of distributed photovoltaic power generation systems in industrial parks.The analyzed results reveal that the change loss is stable after the photovoltaic is connected,and there is no additional transformer loss.And before and after the photovoltaic system installation,there was no significant change in the total monthly data difference between the total meter and the sub-meter.

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 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.

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.

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.

Photovoltaic,thermoelectric and electromagnetic generation technologies applied in power systems for mobile unmanned systems

Unmanned systems are increasingly adopted in various fields,becoming an indispensable technology in daily life.Power systems are the lifeblood of unmanned systems,and affect the working time and task complexity.However,traditional power systems,such as batteries and fuels have a fixed capacity.Therefore,once the power supply is exhausted and cannot be replenished in time,the unmanned systems will stop working.Hence,researchers have increasingly begun paying attention to renewable energy generation technologies.The principles,advantages,and limitations of renewable energy generation technologies are different,and their application effects in different unmanned systems are also uneven.This paper presents a comprehensive study of the application and development status of photovoltaic,thermoelectric,and magnetoelectric generation technologies in four kinds of unmanned systems,including space,aviation,ground,and water,and then summarizes the adaptability and limitations of the three technologies to different systems.Moreover,future development directions are predicted to enhance the reliability of renewable energy generation technologies in unmanned systems.This is the first study to conduct a comprehensive and detailed study of renewable energy generation technologies applied in unmanned systems.The present work is critical for the development of renewable energy generation technologies and power systems for unmanned systems.

CT-NET: A Novel Convolutional Transformer-Based Network for Short-Term Solar Energy Forecasting Using Climatic Information

Photovoltaic(PV)systems are environmentally friendly,generate green energy,and receive support from policies and organizations.However,weather fluctuations make large-scale PV power integration and management challenging despite the economic benefits.Existing PV forecasting techniques(sequential and convolutional neural networks(CNN))are sensitive to environmental conditions,reducing energy distribution system performance.To handle these issues,this article proposes an efficient,weather-resilient convolutional-transformer-based network(CT-NET)for accurate and efficient PV power forecasting.The network consists of three main modules.First,the acquired PV generation data are forwarded to the pre-processing module for data refinement.Next,to carry out data encoding,a CNNbased multi-head attention(MHA)module is developed in which a single MHA is used to decode the encoded data.The encoder module is mainly composed of 1D convolutional and MHA layers,which extract local as well as contextual features,while the decoder part includes MHA and feedforward layers to generate the final prediction.Finally,the performance of the proposed network is evaluated using standard error metrics,including the mean squared error(MSE),root mean squared error(RMSE),and mean absolute percentage error(MAPE).An ablation study and comparative analysis with several competitive state-of-the-art approaches revealed a lower error rate in terms of MSE(0.0471),RMSE(0.2167),and MAPE(0.6135)over publicly available benchmark data.In addition,it is demonstrated that our proposed model is less complex,with the lowest number of parameters(0.0135 M),size(0.106 MB),and inference time(2 ms/step),suggesting that it is easy to integrate into the smart grid.

Design of Smart Home System Based on ZigBee Technology and R&D for Application

In this paper, a smart home system based on ZigBee technology is designed. The system includes home network, home server and mobile terminal. The program is highly scalable and cost-effective. This paper developed the home server-side application based on MFC technology and the mobile terminal application. The mobile client can remotely control home devices and query the running state, electric energy information and historical data of home devices. At the same time, the home server-side application can store electric energy information and electricity consumption of home devices. Combined with household distributed photovoltaic generation system, the system can be applied to home energy management system. Through running tests and application, the results show that the system has realized basic functions of smart home and achieved the desired design goals.

Multi-Agents for Microgrids

Microgrid systems are built to integrate a generation mix of solar and wind renewable energy resources that are generally intermittent in nature. This paper presents a novel decentralized multi-agent system to securely operate microgrids in real-time while maintaining generation, load balance. Agents provide a normal operation in a grid-connected mode and a contingency operation in an islanded mode for fault handling. Fault handling is especially critical in microgrid operation to simulate possible contingencies and microgrid outages in a real-world scenario. A robust agent design has been implemented using MATLAB-Simulink and Java Agent Development Framework technologies to simulate microgrids with load management and distributed generators control. The microgrid of the German Jordanian University has been used for simulation for Summer and Winter photovoltaic generation and load profiles. The results show agent capabilities to operate microgrid in real-time and its ability to coordinate and adjust generation and load. In a simulated fault incident, agents coordinate and adjust to a normal operation in 0.012 seconds, a negligible time for microgrid restoration. This clearly shows that the multi-agent system is a viable solution to operate MG in real-time.

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.

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.