Direct Normal Irradiance Research Articles

Analyzing Spatial Variations of Cloud Attenuation by a Network of All-Sky Imagers

All-sky imagers (ASIs) can be used to model clouds and detect spatial variations of cloud attenuation. Such cloud modeling can support ASI-based nowcasting, upscaling of photovoltaic production and numeric weather predictions. A novel procedure is developed which uses a network of ASIs to model clouds and determine cloud attenuation more accurately over every location in the observed area, at a resolution of 50 m × 50 m. The approach combines images from neighboring ASIs which monitor the cloud scene from different perspectives. Areas covered by optically thick/intermediate/thin clouds are detected in the images of twelve ASIs and are transformed into maps of attenuation index. In areas monitored by multiple ASIs, an accuracy-weighted average combines the maps of attenuation index. An ASI observation’s local weight is calculated from its expected accuracy. Based on radiometer measurements, a probabilistic procedure derives a map of cloud attenuation from the combined map of attenuation index. Using two additional radiometers located 3.8 km west and south of the first radiometer, the ASI network’s estimations of direct normal (DNI) and global horizontal irradiance (GHI) are validated and benchmarked against estimations from an ASI pair and homogeneous persistence which uses a radiometer alone. The validation works without forecasted data, this way excluding sources of error which would be present in forecasting. The ASI network reduces errors notably (RMSD for DNI 136 W/m2, GHI 98 W/m2) compared to the ASI pair (RMSD for DNI 173 W/m2, GHI 119 W/m2 and radiometer alone (RMSD for DNI 213 W/m2), GHI 140 W/m2). A notable reduction is found in all studied conditions, classified by irradiance variability. Thus, the ASI network detects spatial variations of cloud attenuation considerably more accurately than the state-of-the-art approaches in all atmospheric conditions.

Efficient waste heat recovery of a hybrid solar-biogas-fueled gas turbine cycle for poly-generation purpose: 4E analysis, parametric study, and multi-objective optimization

In the present theoretical study, a steam Rankine cycle (SRC) and a modified organic flash cycle (MOFC) are used as bottoming systems for a gas turbine cycle (GTC). Then, the waste energy of the compression stage of the GTC is recuperated by a hot water unit, and the waste energy of the SRC and MOFC is recovered in a single effect LiCl-H2O absorption chiller and a thermoelectric generator, correspondingly. Furthermore, the power produced in the SRC and MOFC is transmitted to a proton exchange membrane electrolyzer and a reverse osmosis desalination unit to produce hydrogen and freshwater. Thus, the system is converted into a ploy-generation layout. In the parametric study section, the effects of changes in the pressure ratio of the GTC, inlet temperature of the solar power tower, number of heliostat mirrors, methane content of biogas, inlet temperature of the gas turbine, and direct normal irradiance on the energy, exergy, exergy-economic, and environmental output parameters are investigated. The results show that solar power tower is the most influential component in the exergy destruction and cost rates. Furthermore, the exergy efficiency, total cost rate, the unit cost of products, and payback period are obtained as 24.34 %, 6390 $/h, 20.17 $/GJ, and 0.687 years in the base case. Considering exergy efficiency and total cost rate as the objective functions, these two parameters improved by 14.87 % and 11.01 % in the optimum case, respectively.

Parameterization of cloud transmittance for expeditious assessment and forecasting of all-sky DNI

Radiative transfer models require vast computing resources to solve cloud transmittance and reflectance from the radiative transfer equation. As a result, models offering precise simulation in operations often acquire individual cloud transmittance or reflectance from a lookup table precomputed for practicable scenarios. To further expedite the computation of global horizontal irradiance and to reduce the storage requirements, the Fast All-sky Radiation Model for Solar applications (FARMS) parameterized the lookup table using elementary functions with specified coefficients. This study extends FARMS direct normal irradiance (DNI) computation by utilizing hyperbolic tangent functions and various polynomial functions to parameterize the cloud transmittance for scattered solar radiation in the circumsolar region. The parameterization is implemented in FARMS with DNI (FARMS-DNI) and accounts for the circumsolar radiation when assessing or forecasting DNI. The evaluation, with long-term observations at the National Renewable Energy Laboratory's, Solar Radiation Research Laboratory, and the Atmospheric Radiation Measurement, Southern Great Plains, Central Facility, shows that the parameterized DNIs are virtually identical with those computed by coupling FARMS-DNI to a lookup table of cloud transmittance. This parameterization has diverse applications in radiative transfer models and numerical weather prediction models used to assess or forecast direct solar radiation.

Hourly predictions of direct normal irradiation using an innovative hybrid LSTM model for concentrating solar power projects in hyper-arid regions

Although solar energy harnessing capacity varies considerably based on the employed solar energy technology and the meteorological conditions, accurate direct normal irradiation (DNI) prediction remains crucial for better planning and management of concentrating solar power systems. This work develops hybrid Long Short-Term Memory (LSTM) models for assessing hourly DNI using meteorological datasets that include relative humidity, air temperature, and global solar irradiation. The study proposes a unique hybrid model, combining a balance-dynamic sine–cosine (BDSCA) algorithm with an LSTM predictor. Combining optimizers and predictors, such hybrid models are rarely developed to estimate DNI, especially in smaller prediction intervals. Therefore, various commonly adopted algorithms in relevant studies have been considered references for evaluating the new hybrid algorithm. The results show that the relative errors of the proposed models do not exceed 2.07%, with a minimum correlation coefficient of 0.99. In addition, the dimensionality of inputs was reduced from four variables to the two most cost-effective variables in DNI prediction. Therefore, these suggested models are reliable for estimating DNI in the arid desert areas of Algeria and other locations with similar climatic features.

Shortwave Radiation on Horizontal and Incline Surfaces—One Year of Solar Radiation Measurements at Athalassa, an Inland Location in Cyprus

Athalassa is the main actinometric station of Cyprus and is located in the center of the island at a height of about 160 m. The station is equipped with shortwave and longwave radiation instruments. The time step of the measurements is 10 min, and hourly and daily values were derived for the period of June 2020–May 2021. The solar data underwent an extensive quality control process based mainly on the suggested tests of Baseline Surface Radiation Network (BSRN) for both the hourly and daily datasets. More than 98% of the data were within the limits recommended by the BSRN and other radiation networks. A statistical analysis of the shortwave solar radiation components was then performed. Linear and quadratic relationships were established between various radiation components, and their diurnal and monthly variability was assessed. The annual average daily global radiation amount was approximately 19 MJ/m2, whereas the amounts of horizontal beam and diffuse radiation were 12.9 MJ/m2 and 4.7 MJ/m2, respectively. Regarding the modeling of diffuse irradiance, the BRL diffuse fraction model (Boland-Ridley-Lauret) was applied. The results showed that the BRL model can satisfactorily estimate both the diffuse solar irradiance as well as the direct normal irradiance. Furthermore, the levels of the shortwave components were estimated based on the classification of four categories of the clearness index. The annual average of the direct normal beam radiation on clear days was 27.3 MJ/m2, and the direct horizontal radiation was 17.7 MJ/m2. Finally, the total energy received by an inclined surface was estimated based on measurements on the horizontal surfaces. In practice, photovoltaics were installed with an annual permanent slope of 26° with respect to the horizontal surface, and in a southern direction.

Comparative Analysis of Photosynthetically Active Radiation Models Based on Radiometric Attributes in Mainland Spain

The aims of this work are to present an analysis of quality solar radiation data and develop several hourly models of photosynthetically active radiation (PAR) using combinations of radiometric variables such as global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI), and direct normal irradiance (DNI) from their dimensionless indices atmospheric clearness index (kt), horizontal diffuse fraction (kd), and normal direct fraction (kb) together with solar elevation angle (α). GHI, DHI, and DNI data with 1-minute frequencies in the period from 2016 to 2021 from CEDER-CIEMAT, in a northern plateau, and PSA-CIEMAT in the southeast of the Iberian Peninsula, were used to compare two locations with very different climates according to the Köppen—Geiger classification. A total of 15 multilinear models were fitted and validated (with independent training and validation data) using first the whole dataset and then by kt intervals. In most cases, models including the clearness index showed better performance, and among them, models that also use the solar elevation angle as a variable obtained remarkable results. Additionally, according to the statistical validation, these models presented good results when they were compared with models in the bibliography. Finally, the model validation statistics indicate a better performance of the interval models than the complete models.

Development of a Simple Methodology Using Meteorological Data to Evaluate Concentrating Solar Power Production Capacity

Evaluation of the Concentrating Solar Power capacity factor is critical to support decision making on possible regional energy investments. For such evaluations, the System Advisor Model is used to perform capacity factor assessments. Among the required data, information concerning direct normal irradiance is fundamental. In this context, the Engerer model is used to estimate direct normal irradiance hourly values out of global horizontal irradiance ground measurements and other observed meteorological variables. Model parameters were calibrated for direct normal irradiance measurements in Évora (Southern Portugal), being then applied to a network of 90 stations, part of the Portuguese Meteorological Service. From the modelled direct normal irradiance, and for stations that comprise 20 years of data, typical meteorological years were determined. Finally, to identify locations of interest for possible installations of Concentrating Solar Power systems, annual direct normal irradiance availabilities and the respective capacity factor, for a predefined power plant using the System Advisor Model, were produced. Results show annual direct normal irradiance availabilities and capacity factors of up to ~2310 kWh/m2 and ~36.2% in Castro Marim and in Faro, respectively. Moreover, this study supports energy policies that would promote Concentrating Solar Power investments in Southern Portugal (Alentejo and Algarve regions) and eastern centre Portugal (Beira Interior region), which have capacity factors above 30%.

Innovative hybrid waste to energy–parabolic trough plant for power generation and water desalination in the Middle East North Africa region: Jordan as a case study

This research proposes a hybrid system consisting of a parabolic trough solar field coupled with a waste incineration facility to produce power and desalinated water in Jordan. To predict the performance of the proposed system, EBSILON Professional (13.02) was used to simulate the entire system and for a more realistic simulation process, a prime sample of 100 tons of municipal waste from Jordan was obtained, processed, and homogenised, after which 4 kg was brought to Germany for laboratory analysis. The laboratory results were inserted into EBSILON. Solar radiation data were adapted from meteonorms and input to EBSILON. Heat transfer between the receiver wall and the heat transfer fluid was analysed to calculate the time required to increase the temperature of the Heat Transfer Fluid from the influent temperature to the desired effluent temperature. The results show that this system can produce 34 MWe of power and 13,824 m3/d of distilled water. On the 1st January, the temperature of the heat transfer fluid in the solar field was increased by 6 °C for 20 min in an open cycle. After 5h, it reached 390 °C in a closed cycle, assuming a fixed direct normal irradiance. Economically, five scenarios were analysed to assess the impact of the cost of heat harvested to produce this amount of water on the annual cost of handling each ton of garbage which was approximately 57 US$ in the first year of operation and 19.5 US$ in the 15th year of plant operation (for the scenario in which the tariff of power sales was considered to evaluate the cost of heat for water desalination).

Dispatch optimization of a concentrating solar power system under uncertain solar irradiance and energy prices

The integration of thermal energy storage into a concentrating solar power system allows for mitigating some of the risk associated with uncertain solar irradiance and uncertain energy prices. We solve a 48 h dispatch optimization model with continually updated conditional point forecasts of both direct normal irradiance (DNI) and electricity prices with a rolling-horizon scheme at hourly resolution over the course of a year. Joint, conditional forecasts for DNI and prices are formed using an autoregressive moving-average time series model with exogenous weather predictors. We guide dispatch using a mixed-integer programming model, but in order to evaluate performance we use the System Advisor Model (SAM) of the National Renewable Energy Laboratory. SAM is a techno-economic simulation model that accounts for plant thermodynamics with higher fidelity. Our conditional DNI forecasts improve annual revenue by 4%–12% over using historical forecasts based on data from previous years. Conditional price forecasts improve annual revenue by 6%–19% in the real-time market over analogous historical forecasts. Updating these forecasts every six hours, rather than every 24 h, further improves annual revenue by 5%–6%. We also investigate a method that values terminal inventory in our dispatch optimization model, again when used in a rolling-horizon scheme.

A combination of supervised dimensionality reduction and learning methods to forecast solar radiation

Machine learning is routinely used to forecast solar radiation from inputs, which are forecasts of meteorological variables provided by numerical weather prediction (NWP) models, on a spatially distributed grid. However, the number of features resulting from these grids is usually large, especially if several vertical levels are included. Principal Components Analysis (PCA) is one of the simplest and most widely-used methods to extract features and reduce dimensionality in renewable energy forecasting, although this method has some limitations. First, it performs a global linear analysis, and second it is an unsupervised method. Locality Preserving Projection (LPP) overcomes the locality problem, and recently the Linear Optimal Low-Rank (LOL) method has extended Linear Discriminant Analysis (LDA) to be applicable when the number of features is larger than the number of samples. Supervised Nonnegative Matrix Factorization (SNMF) also achieves this goal extending the Nonnegative Matrix Factorization (NMF) framework to integrate the logistic regression loss function. In this article we try to overcome all these issues together by proposing a Supervised Local Maximum Variance Preserving (SLMVP) method, a supervised non-linear method for feature extraction and dimensionality reduction. PCA, LPP, LOL, SNMF and SLMVP have been compared on Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) radiation data at two different Iberian locations: Seville and Lisbon. Results show that for both kinds of radiation (GHI and DNI) and the two locations, SLMVP produces smaller MAE errors than PCA, LPP, LOL, and SNMF, around 4.92% better for Seville and 3.12% for Lisbon. It has also been shown that, although SLMVP, PCA, and LPP benefit from using a non-linear regression method (Gradient Boosting in this work), this benefit is larger for PCA and LPP because SMLVP is able to perform non-linear transformations of inputs.

Dynamic behavior of solar thermochemical reactors for fuel generation: Modeling and control strategies

Solar thermochemical water splitting provides an efficient route for converting solar energy into renewable fuels. The operation of solar thermochemical reactor under real on-sun condition requires in-depth understanding of its dynamic behaivor under fluctuating direct normal irradiation (DNI). In this work, we developed a 2D axial-symmetric multi-physical model to assess the reactor’s dynamic behavior with three oxygen removing technologies electrochemical oxygen pump (EOP), sweep gas (SG), and vacuum pump (VP), under varying solar irradiations. To alleviate the negative effect of decreased DNI, two control strategies (CS) including varying operational conditions for oxygen removing technologies (CS1) and replacing the reduction step with the oxidation step (CS2) were conducted. We found that CS1 was only effective when DNI reduction was larger than 75 % over the whole reduction step (case 2). In general, CS2 can be implemented to alleviate the efficiency decrease for all DNI variations expect for the case 2 in this study. Especially, CS2 significantly increased the solar-to-fuel efficiency compared to the case without control strategy for the reduced DNI from 1000 W/m2 to 500 W/m2 during the whole reduction step. The reactor dynamic behavior in response to the daily DNI variations is also reported which shows that the efficiency profiles are highly in line with the DNI profile. This modeling work as well as proposed control strategies can be used to guide the design and control of solar thermochemical reactors under realistic conditions and hence for better assessing the performance of the reactor in practice.

Study on dynamic model and dynamic characteristics of Delingha 50 MW trough solar field

China General Nuclear Power Group (CGNPC) Delingha 50 MW parabolic trough solar thermal power plant is the first commercial trough solar plant in China, and its solar field consists of 190 parallel heat collecting loops. For large-scale trough solar plant, balancing the flow rate of heat absorbing medium in each loop and stabilizing the outlet temperature are the key technologies and difficult problems. Regarding the Delingha 50 MW solar field as the research object, this paper mainly focusing on the dynamic characteristics of flow and heat transfer in the solar field. The hydrodynamic calculation model and the heat transfer dynamic model are established on the real-time dynamic simulation platform STAR-90. With the actual operation data, the built solar field model is validated by comparing the simulation results. On this basis, the disturbance simulations of direct normal irradiance (DNI), heat transfer oil’s mass flow and heat transfer oil’s inlet temperature are carried out. The dynamic response curves of disturbance and the thermal inertia time constant of the loops are obtained. The conclusions lay a theoretical foundation for the formulation of outlet medium’s temperature control strategy in the solar field of large-scale trough solar thermal power generation system.

A method for global potential assessment of roof integrated two-stage solar concentrators (TSSCs) at district scale

This paper proposes a core method for integrating two-stage solar concentrators (TSSCs) as roof-integrated energy supply systems at the district scale. However, the performance of these systems not only depends on good configurations but also on optimal building typologies. The design process of buildings-integrated TSSCs on a district scale reflects a complex multi-criteria problem, where several conflicting concerns from multiple stakeholders need to be addressed. Thus, the proposed method aims to support the multi-criteria decision-making process in the early-stage design of sustainable districts utilizing TSSC technology. The method contributes to the design of the TSSCs relative to district designs. Our method enables design generation according to a set of decision variables related to the district (roof type and slope, orientation, building height, width, and length), and TSSC (type, geometric ratio, separation distance between mirrors, modules number, and solar cell size). The method uses a parametric modeling approach combined with a multi-objective optimization algorithm (NSGA-II) that enables design optimization of the district and TSSCs in two consecutive steps. The two-step design optimization allows finding optimal district designs for maximizing cumulative direct normal irradiance (DNI) and minimizing the total energy demand, and TSSC designs for maximizing average monthly load match index (av.LMI) (a ratio of energy yield to demand) and minimizing the average covered roof area occupied by modules. We validated the proposed method in an illustrative case study of ‘Buckower Felder’, a district in the city of Berlin (Germany). The illustrative application shows that our method enables the performance-driven, generative design of both; district and building-integrated TSSCs and searches for the most appropriate solutions i.e., urban designs for maximum DNI and minimum demand, and TSSC designs for maximum av.LMI and minimum covered roof area. Results indicate that there is a trade-off between objectives, where district design with high DNI (>4500 kW/m2/h/month) reflects high energy demand (8.6e + 05 kWh/month). Similarly, TSSC designs ensuring high av.LMI (>1.0) require a large roof area (>47 %). Given these trade-offs, the method can meaningfully support the decision-making process. Thus, the method allows for large-scale integration of TSSCs with buildings at an urban scale and supports solar energy planning and energy transition policies for sustainable districts.

Modeling study and experimental investigation of SPSR and solid particles–sCO2 heat exchanger for concentrating solar power plant

Solid particle solar receiver (SPSR) and solid particles-supercritical carbon dioxide (sCO 2) heat exchanger (HX) are critical units for energy concentration and conversion in innovative concentrating solar power (CSP) plant, and their property will have great impact on the sCO 2-CSP integrated system. The SPSR is receiving increasing attention owing to the higher operation temperature potentially to lower the cost of the integrated. The significance of solid particles–sCO 2 HX cannot be underestimated, since the energy conversation assimilated from solid particles of the SPSR can be transferred to sCO 2 rapidly and efficiently to directly impact the whole efficiency of the integrated system. In this paper, mathematical models of quartz tube bundles SPSR and fluidized bed solid particles–sCO 2 HX were established. Furthermore, based on the first solar power tower plant in Asia, on-sun experiments were carried out, the total operation time exceeded 103 h. The experimental results show that when 59 heliostats are used, the direct normal irradiance is 865 W/m2, and the remaining time is 351 s, the maximum output temperature can reach 871.6 °C. In addition, by comparing the simulation results with the experimental values, it indicates the established models possess high degree of accuracy. The study extends to the dynamic simulation and control strategy, and puts forward suggestions for the system optimization and operation regulation of the sustainable power system on electrical engineering and green energy.

Mapping of Suitable Sites for Concentrated Solar Power Plants in the Philippines Using Geographic Information System and Analytic Hierarchy Process

Solar energy is a renewable source of energy harnessed from the sun. Concentrated solar power (CSP) plants harness this energy by focusing sunlight on a limited area to heat a working fluid, which is used to generate steam and power a thermodynamic cycle that produces electricity. There are currently no CSP plants in the Philippines, and this study aimed to locate the most suitable sites for this type of power plant. The first step was to mask out areas totally unsuitable as plant sites; we identified five exclusion factors for this: protected areas, slope, direct normal irradiance (DNI), water bodies, and land cover type. A scoring gradient was then applied to the remaining suitable areas according to seven ranking factors: DNI, slope, typhoon frequency, capacity of the nearest grid line, distance to the nearest grid line, distance to the nearest road, and distance to the nearest water body. Next, to reflect the actual degrees of influence of the factors to site suitability, we determined their relative numeric weights using analytic hierarchy process, with the weights derived from inputs from interviews with academic and industry experts. Finally, using ArcGIS Pro, we used a weighted sum of the ranking scores to produce a suitability map covering the entire Philippines. Suitable sites in the following provinces were found: Ilocos Sur, Pampanga, Mindoro, Masbate, and Maguindanao. These areas have a total area of 27.9 km2 and a projected total power output of 733 MW.

Numerical investigation of the thermal performance of multistage falling particle receivers at commercial scales

The thermal performance of commercial scale multistage falling particle receivers (MFPRs) was numerically investigated under various environmental conditions using advanced CFD models. This model accounted for spatially-varying solar radiation from the heliostats, particle dynamics, heat transfer, turbulent air flows, and the effect of wind. In this study, a 2-stage MFPR design has been explored for various trough heights and trough lengths. The final MFPR geometry provided ∼5%-points higher thermal efficiency compared to a similarly sized free-falling particle receiver (FFPR) at the same quiescent condition. The thermal performance of MFPRs was evaluated for three different commercial scales at various levels of incident solar power (Qin) to account for variation of incident solar power from changes in the direct normal irradiance (DNI) throughout a typical day. An upper bound for MFPR efficiency was obtained from scaling Qin by Ap1.2 where Ap is the open aperture area. The proposed scaling showed that the thermal efficiency asymptotes as a function of Qin/Ap1.2, and the thermal efficiency converges to ∼90% for Qin/Ap1.2 >0.75 regardless of the overall receiver scale. A parametric study was also performed to explore the effects of incident solar power, wind speed, and wind direction on the performance of MFPR at various scales. The study showed that the thermal efficiency of MFPRs is reduced with decreasing incident solar fluxes and with increasing wind speed. The degradation in thermal performance became significant for the present north-facing MFPR with the wind blowing from the northwest to west-northwest directions. It was found that for these wind directions, vortical structures existing ahead of the open aperture entrained cooler ambient air into the receiver cavity, increasing thermal convection between the ambient air and falling particles, and thus resulted in significant thermal performance degradation.

Measuring Concentrated Solar Radiation Flux in a Linear Fresnel-Type Solar Collector

Linear Fresnel solar collectors are a promising and emerging solution to contribute to renewable heat supply in industrial processes with thermal energy demand in the medium temperature range (<250 °C). An innovative linear Fresnel collector (LFC) prototype has been designed, patented, and built at the Plataforma Solar de Almería (PSA), Spain. This work presents the applied methodology, experimental device, and results obtained in the measurement of the flux density of concentrated solar radiation in the focal plane of the solar collector. The experimental results confirm that an average flux density of (9.8 ± 0.6) kW/m2 was obtained with a direct normal solar irradiance of (870 ± 10) W/m2 in tests performed in May 2002, which is a result similar to that obtained in optical simulations of the system.

Wavelet Analysis of the Interconnection between Atmospheric Aerosol Types and Direct Irradiation over Cameroon

The comparative analysis of the intra- and interannual dynamics between the Direct Normal Irradiation (DNI) under clear sky conditions and five aerosol types (Dust, Sea Salt, Black Carbon, Organic Carbon, and Sulfate) is the purpose of this study. To achieve this aim, we used fifteen-year DNI and aerosols data downloaded at 3-hour time intervals in nine defined zones throughout Cameroon. The wavelet transform is a powerful tool for studying local variability of amplitudes in a temporal dataset and constitutes our principal tool. The results show unequal distribution of aerosol types according to zones, but the Desert Dusts (DU) and Organic Carbon (OM) aerosols have been found as dominant particles in the studied region. The wavelet coherence analysis between DNI and each aerosol type reveals three bands of periodicity: ∼ 4-month band, 8–16-month band, and sometimes after-32-month band, with the most important frequency at 8–16-month band period. However, the intensity of coherence across bands varies with respect to aerosol type as well as each of the nine climate zones. A significant anticorrelation relationship was obtained between DNI and each type of aerosol, emphasizing that the presence of such atmospheric particles could dampen the renewable energy utilized by power systems. Also, the analysis shows that scattering aerosols such as Sulfate and Sea Salt (SU and SS, respectively) lead DNI in phase while absorbing aerosols such as Organic Carbon, Black Carbon, and Dust (OM, BC, and DU, respectively) give phase lag with DNI.

Flexibility enhancement of solar-aided coal-fired power plant under different direct normal irradiance conditions

The integration of solar thermal energy into the coal-fired power plant is a cost-effective method to compensate for the solar energy intermittency. With the increasing penetration of renewable energy in the power grid, the solar-aided coal-fired power plant (SACFPP) should undertake peak-shaving tasks, which receives little attention in previous studies. This study examines the SACFPP flexibility and finds out that the reheat steam temperature easily exceeding the safety range limits the maximum load cycling rate during processes simultaneously accompanied with direct normal irradiance (DNI) disturbances. An improved control strategy is proposed accordingly to enhance the SACFPP flexibility. The feedforward control signal to regulate the flue gas damper is generated corresponding to the DNI and load cycling requirements. The effectiveness of the proposed control under sunny/cloud cover cases and actual conditions is verified. Results show that the maximum load cycling rate of a 660 MW SACFPP increases from 3.3 MW min−1to 13.2/13.2/9.9 MW min−1 under sunny/light cloud cover/strong cloud cover cases, respectively. The reheat steam temperature deviations are reduced from 9.7 °C to 4.0 °C and 18.6 °C to 4.0 °C, when DNI step decreases from 700 W m−2 to 400 W m−2 and 0 W m−2 in load up processes, respectively.

Collaborative optimization of thermal and economic performances of a tower solar aided coal-fired power generation system

• New operation strategy of solar aided coal-fired power generation unit is proposed. • The system annual performances in different solar irradiation levels are studied. • Collaborative optimization of the proposed system configurations is carried out. • Multi-time scale thermal performance analyses of the proposed system are conducted. • The sensitivity analyses of the economic parameters of solar field are explored. This paper studies a novel tower solar aided coal-fired power generation (TSACPG) system with thermal energy storage (TES) system to realize the high-grade solar energy cascade utilization and puts forward an improved annual operation strategy of the system. The variations of annual electricity output from solar, annual solar to electricity efficiency and solar field levelized cost of electricity (LCOE) of the proposed TSACPG system under different solar multiples and thermal energy storage hours are explored in different level direct normal irradiation (DNI) sites. Collaborative optimizations of the TSACPG system configurations are performed by the non-dominated sorting genetic algorithm-II. The results demonstrate that the annual electricity output from solar is positively correlated with yearly DNI level and ascends with the increases of both TES hour and solar multiple. The annual solar to electricity efficiency descends with an increasing solar multiple and ascends with an increasing TES hour. The solar field LCOE will initially descend with the increase of solar multiple to the minimum and then ascend, and it will also ascend with an increasing TES hour. The improved operation strategy proposed is superior to the simple operation strategy in terms of both thermodynamic and economic performances. The pareto fronts in different level DNI sites are obtained with the simultaneous optimization of the annual electricity output from solar and the solar field LCOE. The best compromise solutions are obtained. The optimal TES hours and solar multiple values in high, medium and low level DNI sites are 14.14 h/2.64, 14.22 h/2.61 and 12.15 h/2.52, respectively. The multi-time scale analyses of the TSACPG system in different level DNI sites are conducted. The results suggest that the electricity output from solar is relatively high and the solar to electricity efficiency is comparatively low in high level DNI sites. The daily performance result implies that the system has a better performance in high level DNI site, which provides an important reference for the actual design of the system. Economic analysis reveals that the tower solar system investment payback time shows the superiority in high level DNI site and the investment payback time exhibits a trend towards shortening with an increasing coal price. Meanwhile, the sensitivity results of economic performance indexes show that the TSACPG system economic performance is closely related to the price of system components, which exhibits the impact of market changes on economic benefits for decision makers.