Preparation and Characterization of Andalusite Ceramic Used for Solar Thermal Power Generation

High-temperature thermal storage material is one of the critical materials of solar thermal power generation system. Andalusite, kaolin, talc, γ-Al2O3 and partially stabilized zireonia were used as the raw materials, and in-situ synthesis of cordierite was adopted to fabricate thermal storage material for solar thermal power generation via pressureless sintering. The phase compositions, microstructures and thermal shock resistances of the sintered samples were analyzed by XRD, SEM and EDS, and the corresponding mechanical properties were measured. The results show that the major phases of the samples are mullite and zirconium silicate, and the pores distribute uniformly. After being sintered at 1 460℃C, A4 sample exhibits a better mechanical performance and thermal shock resistance, its loss rate of bending strength after 30 cycles thermal shock is 3.04%, the bulk density and bending strength are 2.86 g.cm^-3 and 139.66 MPa, respectively. The better thermal shock resistance of the sample is closely related to the effect of zirconium silicate, such as its uniform distribution, nested growth with mullite, low thermal expansion coefficient, high thermal conductivity, etc. This ceramic can be widely used as one of potential thermal storage materials of solar thermal power generation system.

Application of Model Predictive Control Based on Kalman Filter in Solar Collector Field of Solar Thermal Power Generation

There are two prominent features in the process of temperature control in solar collector field.Firstly,the dynamic model of solar collector field is nonlinear and complex,which needs to be simplified.Secondly,there are a lot of random and uncontrollable,measurable and unmeasurable disturbances in solar collector field.This paper uses Taylor formula and difference approximation method to design a dynamic matrix predictive control(DMC)by linearizing and discretizing the dynamic model of the solar collector field.In addition,the purpose of controlling the stability of the outlet solar field salt temperature is achieved by adjusting the mass flow of molten salt.In order to further improve the ability of the system to suppress unmeasured disturbances,a steady-state Kalman filter is designed to estimate state variables,so that the system has better stability and robustness.The simulation verification results show that the DMC control system based on Kamlan filtering has better control effect than the traditional DMC control system.In the case of large fluctuations in solar radiation intensity and consideration of undetectable interference,the overshoot of the system is reduced by 4%and the rise time remains unchanged.

Effect of Impeller Solidity on the Generating Performance for Solar Power Generation

According to current solar power research,both the generating unit’s minimum start-up speed and power generation system’s minimum flow rate for operation decrease with the increase in the impeller solidity.Ideally,a high solidity should be achieved,as this translates more power for a solar power system in the start-up and shut-down cycles.However,increasing the number of blades does not increase the impeller solidity;therefore,there is an optimal number of blades needed to achieve the preferred solidity.This paper begins by selecting the blade airfoil and then performs a theoretical analysis based on the relationship between the blade number and chord length.Experiments are conducted to measure the starting and stopping wind speeds and power characteristics for different numbers of blades.The results show that a maximum impeller solidity of 0.2862 is achieved,as well as the minimum flow speed at the start-up,and the maintenance of the solar chimney power generation system is optimized when there are four blades.

A Case Study: Performance Comparison of Solar Power Generation between GridLAB-D and SAM in Dili Timor Leste

Study of comparison of solar power generation between the GridLAB-D tool and System Advisor Model (SAM) in Dili, Timor Leste is presented in this paper. Weather Research and Forecasting (WRF) model is used to simulate solar radiation for one calendar year from January to December 2014 using six-hourly interval 1° × 1° NCEP FNL analysis data. The one calendar year results from the WRF model will be used as input data for GridLAB-D and SAM to estimate the solar power generation. GridLAB-D is an open-source and analysis tool designed to operate the distribution power systems with a high-performance algorithm. System Advisor Model version SAM 2017.9.5 is used to estimate solar power performance with Photovoltaics (PVWatts)- Commercial Distributed model. This model is designed to analyze the performance and the financing of renewable energy for electricity generation. The results show the lowest solar radiation is 512 W/m2 obtained in June with an average monthly power of 20.6 kW and 30.55 kW generated from the SAM model and the GridLAB-D simulator, respectively. Meanwhile, the highest solar radiation is 1100 W/m2, 1112 W/m2, 1046 W/m2, and 1077 W/m2 obtained in October, November, December, and January with an average monthly power of 55.72 kW, 62.44 kW, 56.65 kW, and 56.97 kW from the SAM model, in the other hand, 48.89 kW, 51.31 kW, 55.51 kW, and 57.18 kW generated by the GridLAB-D. Finally, the results show that the performance of the GridLAB-D and the SAM model was quite good because both model precisely presented values are almost closest to each other. This study proposes that the results of solar output power from both methods, GridLAB-D and SAM can be used to design grid-connected or stand-alone electric power projects to increase the quality of electricity generation in Dili, Timor Leste.

POWER GENERATION POTENTIAL OF BIPV APPLICATION IN CHINA

This paper discusses the potential and prospect of building-integrated photovoltaics (BIPV) for solar electrical power generation in China.The BIPV technology has been identified as the most economical renewable energy resource to contribute to world electrical energy demand for protecting environment from reduced fossil fuel consumption.The available solar energy resource of 14 cities and the potential power generation from PV claddings in buildings in China were estimated.The economical analysis of BIPV application is discussed.It is found that the potential is significant and the government should play an important role in its development.

In-Situ Preparation and Thermal Shock Resistance of Mullite-Cordierite Heat Tube Material for Solar Thermal Power

In order to improve the thermal shock resistance of solar thermal heat transfer tube material, the mullite-cordierite composite ceramic as solar thermal heat transfer tube material were fabricated by pressureless sintering using a-Al203, Suzhou kaolin, talc, and feldspar as starting materials. The important parameter for solar thermal transfer tube such as water absorption （W）, bulk density （Db）, and the mechanical properties were investigated. The phase composition and microstructure of the composite ceramics were analyzed by XRD and SEM. The experimental results show that the B3 sintered at 1 300 ℃ and holding for 3 h has an optimum thermal shock resistance. The bending strength loss rate of B3 is only 2% at 1 100℃ by air quenching-strength test and the sample can endure 30 times thermal shock cycling, and the water absorption, the bulk density and the bending strength are 0.32%, 2.58 g·cm-3, and 125.59 MPa respectively. The XRD analysis indicated that the phase compositions of the sample were mullite, cordierite, corundum, and spinel. The SEM images illustrate that the cordierite is prismatic grain and the mullite is nano rod, showing a good thermal shock resistance for composite ceramics as potential solar thermal power material.

Optimization of solar thermal power station LCOE based on NSGA-Ⅱ algorithm

In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied to optimize the levelling cost of energy(LCOE)of the solar thermal power generation system in this paper.Firstly,the capacity and generation cost of the solar thermal power generation system are modeled according to the data of several sets of solar thermal power stations which have been put into production abroad.Secondly,the NSGA-II genetic algorithm and particle swarm algorithm are applied to the optimization of the solar thermal power station LCOE respectively.Finally,for the linear Fresnel solar thermal power system,the simulation experiments are conducted to analyze the effects of different solar energy generation capacities,different heat transfer mediums and loan interest rates on the generation price.The results show that due to the existence of scale effect,the greater the capacity of the power station,the lower the cost of leveling and electricity,and the influence of the types of heat storage medium and the loan on the cost of leveling electricity are relatively high.

Analysis of silicon-based integrated photovoltaic–electrochemical hydrogen generation system under varying temperature and illumination

Last decade witnessed tremendous research and development in the area of photo-electrolytic hydrogen generation using chemically stable nanostructured photo-cathode/anode materials. Due to intimately coupled charge separation and photo-catalytic processes, it is very difficult to optimize individual components of such system leading to a very low demonstrated solar-to-fuel efficiency (SFE) of less than 1%. Recently there has been growing interest in an integrated photovoltaic–electrochemical (PV–EC) system based on GaAs solar cells with the demonstrated SFE of 24.5% under concentrated illumination condition. But a high cost of GaAs based solar cells and recent price drop of poly-crystalline silicon (pc-Si) solar cells motivated researchers to explore silicon based integrated PV–EC system. In this paper a theoretical framework is introduced to model silicon-based integrated PV–EC device. The theoretical framework is used to analyze the coupling and kinetic losses of a silicon solar cell based integrated PV–EC water splitting system under varying temperature and illumination. The kinetic loss occurs in the range of 19.1%–27.9% and coupling loss takes place in the range of 5.45%–6.74% with respect to varying illumination in the range of 20–100 mW/cm2. Similarly, the effect of varying temperature has severe impact on the performance of the system, wherein the coupling loss occurs in the range of 0.84%–21.51% for the temperature variation from 25 to 50 °C. © 2016 Science Press

Operation Strategy Analysis and Configuration Optimization of Solar CCHP System

This paper proposed a new type of combined cooling heating and power(CCHP)system,including the parabolic trough solar thermal(PTST)power generation and gas turbine power generation.The thermal energy storage subsystem in the PTST unit provides both thermal energy and electrical energy.Based on the life cycle method,the configuration optimization under eight operation strategies is studied with the economy,energy,and environment indicators.The eight operation strategies include FEL,FEL-EC,FEL-TES,FEL-TES&EC,FTL,FTL-EC,FTL-TES,and FTL-TES&EC.The feasibility of each strategy is verified by taking a residential building cluster as an example.The indicators under the optimal configuration of each strategy are compared with that of the separate production(SP)system.The results showed that the PTST-CCHP system improves the environment and energy performance by changing the ratio of thermal energy and electric energy.The environment and energy indicators of FEL-TES&EC are superior to those of FTL-TES&EC in summer,and the results are just the opposite in winter.The initial annual investment of the PTST-CCHP system is higher than that of the SP system,but its economic performance is better than that of the SP system with the increase of life-cycle.

Simulation Analysis for Massive Deployment of Variable Renewables Employing an Optimal Power Generation Mix Model

This paper develops a high time-resolution optimal power generation mix model in its time resolution of 10 minutes on 365 days by linear programming technique. The model allows us to analyse the massive deployment of photovoltaic system and wind power generation in power system explicitly considering those short-term output variation. PV （photovoltaic） and wind output are estimated, employing meteorological database. Simulation results reveal that variable fluctuation derived from a high penetration level of those renewables is controlled by quick load following operation of natural gas combined cycle power plant, pumped-storage hydro power, stationary NAS （sodium and sulfur） battery and the output suppression control of PV and wind. It additionally turns out that the operational configuration of those technologies for the renewable variability differs significantly depending on those renewable output variations in each season and solving the seasonal electricity imbalance as well as the daily imbalance is important if variable renewables are massively deployed.

Distributed Solar PV System for Industrial Application

The paper presents the design and field test of a distributed solar PV system for industrial application （DGPVi）. DGPVi utilizes HyPV （hybrid PV） system which generates solar power for self-consumption in lighting and air conditioning in a production line of a factory when solar energy is available. It does not feed the excess PV power to the grid. HyPV will be switched to grid power supply when solar energy is not available. A 3 kWp DGPVi is installed in a factory for field demonstration. The test results show that the solar PV power generated can be utilized immediately. The solar energy generation efficiency （kWh/day per kWp PV installation） of DGPVi is close to that of grid-tied PV system without self-consumption and battery storage. The yearly return on investment of DGPVi is 2.0% at the present installation cost or 3.3% at further cost-down cost. The payback time will be 14.3 years at the present installation cost or 12.1 years at cost-down cost. The present study verifies the economic feasibility of DGPVi.

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.

Short-Term Prediction of Photovoltaic Power Based on Fusion Device Feature-Transfer

To attain the goal of carbon peaking and carbon neutralization,the inevitable choice is the open sharing of power data and connection to the grid of high-permeability renewable energy.However,this approach is hindered by the lack of training data for predicting new grid-connected PV power stations.To overcome this problem,this work uses open and shared power data as input for a short-term PV-power-prediction model based on feature transfer learning to facilitate the generalization of the PV-power-prediction model to multiple PV-power stations.The proposed model integrates a structure model,heat-dissipation conditions,and the loss coefficients of PV modules.Clear-Sky entropy,characterizes seasonal and weather data features,describes the main meteorological characteristics at the PV power station.Taking gate recurrent unit neural networks as the framework,the open and shared PV-power data as the source-domain training label,and a small quantity of power data from a new grid-connected PV power station as the target-domain training label,the neural network hidden layer is shared between the target domain and the source domain.The fully connected layer is established in the target domain,and the regularization constraint is introduced to fine-tune and suppress the overfitting in feature transfer.The prediction of PV power is completed by using the actual power data of PV power stations.The average measures of the normalized root mean square error(NRMSE),the normalized mean absolute percentage error(NMAPE),and the normalized maximum absolute percentage error(NLAE)for the model decrease by 15%,12%,and 35%,respectively,which reflects a much greater adaptability than is possible with other methods.These results show that the proposed method is highly generalizable to different types of PV devices and operating environments that offer insufficient training data.

Analysis of heat flow diagram of small-scale power generation system:Innovative approaches for improving techno-economic and ecological indices

In this paper,the heat flow diagram of steam turbine model K-6-35 has been analyzed for innovative approaches towards improving the techno-economic and ecological indices of the small-scale power generation system.The numerical analysis is performed using IPSEpro process simulation software based on heat balance method under four different cases.It was found that the study of Solar Assisted Power Generation(SAPG)system has important practical significance in power generation with minimum pollutants and maximum efficiency.Both fuel-saving(FS)and power-boosting(PB)operation modes of the SAPG system are considered.Various types of stand-alone solar thermal power plants exhibited very low overall efficiency with many ecological advantages compared to the conventional thermal power plant based on fossil fuels.Besides,SAPG system with FS mode presented higher techno-economic indices and operation performance.An important reduction in fuel consumption and pollutant emissions could be obtained with SAPG system.Considering the hourly,daily,monthly,and yearly amount of saved fuel and reduced pollutants in the whole power plant,the SAPG system with FS mode can largely contribute to high ecological indices power generation.A thermal efficiency increased by 1.31%with specific equivalent fuel consumption decreased by 22.54 g/kWh was obtained with SAPG system.The coal consumption was reduced by 4.75%when SAPG system operates in FS mode.

Solar aided power generation:A review

Solar Aided Power Generation(SAPG)is the most efficient and economic ways to hybridise solar thermal energy and a fossil fuel fired regenerative Rankine cycle(RRC)power plant for power generation purpose.In such an SAPG plant,the solar thermal energy is used to displace the extraction steam by preheating the feedwater to the boiler.The displaced/saved extraction steam can,therefore,expand further in the steam turbine to generate power.The research and development of the SAPG technology started in the 1990s.This paper is trying to reviews and summarises the progress of research and development of the SAPG plant technology in last almost 30 or so years,including the technical and economic advantages of SAPG over other solar thermal power generation tech-nologies(e.g.solar alone power generation),various modelling techniques used to simulate SAPG perforamnce,impacts of SAPG plant’s configuration,size of solar field and strategies to adjust mass flow rate of extraction steam on the plant perforamnce,exergy analysis of SAPG plant and operation strategies to maximise plant’s economic returns etc.In addition,the directions for future R&D about SAPG technology have been pointed/proposed in this paper.

Optimized Controller Gains Using Grey Wolf Algorithm for Grid Tied Solar Power Generation with Improved Dynamics and Power Quality

This study proposes a control algorithm based on synchronous reference frame theory with unit templates instead of a phase locked loop for grid-connected photovoltaic(PV)solar system,comprising solar PV panels,DC-DC converter,controller for maximum power point tracking,resistance capacitance ripple filter,insulated-gate bipolar transistor based controller,interfacing inductor,linear and nonlinear loads.The dynamic performance of the grid connected solar system depends on the effect operation of the control algorithm,comprising two proportional-integral controllers.These controllers estimate the reference solar-grid currents,which in turn generate pulses for the three-leg voltage source converter.The grey wolf optimization algorithm is used to optimize the controller gains of the proportional-integral controllers,resulting in excellent performance compared to that of existing optimization algorithms.The compensation for neutral current is provided by a star-delta transformer(non-isolated),and the proposed solar PV grid system provides zero voltage regulation and eliminates harmonics,in addition to load balancing.Maximum power extraction from the solar panel is achieved using the incremental conductance algorithm for the DC-DC converter supplying solar power to the DC bus capacitor,which in turn supplies this power to the grid with improved dynamics and quality.The solar system along with the control algorithm and controller is modeled using Simulink in Matlab 2019.

A hybrid machine-learning model for solar irradiance forecasting

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power plants.These plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power output.As the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather conditions.This study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast horizons.Our proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression model.The proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable framework.We evaluated the performance of our model using data sets from both cloudy and sunny days in Seattle and Medford,USA and compared it against three forecasting models:persistence,modified 24-hour persistence and least squares.Based on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

An Overview about the Brazilian Photovoltaic Market Development

There are five main institutions that develop research and provide data regarding photovoltaic energy generation in Brazil, they are: Brazilian Electricity Regulatory Agency (ANEEL);Energy Research Office (EPE);International Renewable Energy Agency (IRENA);Institute for the Development of Alternative Energies in Latin America (IDEAL);and Greener (a research and consultancy company specialized in the photovoltaic solar energy sector). The reports provided by these institutions present a large volume of data and information, this factor makes hard task of understanding the Brazilian photovoltaic market. Therefore, this paper purposes to present an overview about the development of photovoltaic generation in Brazil, through of an unpublished compilation and analysis of the data provided by the institutions previously cited. For this, initially the factors that contributed to the implementation and expansion of this sector are presented. Following, it is presented the main resolutions for the implementation of distributed generation, as well as organizations responsible for the standardization, operation, testing and expected requirements for connection of renewable sources in the electrical system. Quantitative data about energy installed, number of installations approvals, distribution of installations by sector of society, number homologations by power range and cost distribution for the implementation of these systems are provided. Finally, the incentive policies, credit lines and future perspectives for the development of the photovoltaic sector in Brazil are presented.

Influence of thermal effect on multi-junction GaInP/GaAs/Ge concentrating photovoltaic system

The influence of thermal effect on the energy conversion efficiency of concentrating photovoltaic system for multi-junction GaInP/GaAs/Ge thin-film solar cell is analyzed experimentally.With the increment of operation temperature,the maximal energy conversion efficiency and optimal loaded resistor will be changed.Under the condition of operation temperature lower than 90℃.this influence of thermal effect is very small.However,when the operation temperature exceeds 90℃,the maximal conversion efficiency of the cells will decrease sharply,and contrarily the corresponding optimal loaded resistor will increase quickly.Then the system performance will degenerate badly and a thermal management will be necessary.

Comprehensive study of efficient dye-sensitized solar cells based on the binary ionic liquid electrolyte by modifying with additives and iodine

The photovoltaic performance of dye-sensitized solar cells （DSSCs） is enhanced by modifying the binary room tem- perature ionic liquid （RTIL） electrolyte with additives and iodine. The average photoelectric conversion efficiency （PCE） of 6.39% is achieved. Through electrochemical impedance spectroscopy （EIS）, cyclic voltammetry scans and incident photon-to-current conversion efficiency （1PCE） data, the working principles are analyzed. The enhancement is mainly attributed to the improvement of short circuit current which is caused by the reduction of overall internal resistance of the devices. Durability tests are measured at room temperature, and the long-term stability performance can be maintained.