Hourly Solar Data Research Articles

Development of New Models for the Estimation of Hourly Components of Solar Radiation: Tests, Comparisons, and Application for the Generation of a Solar Database in Morocco

All studies of solar systems need the hourly values of solar fluxes related to the different components of solar radiation. However, for most sites, measurements are not available. The goal of this paper is to establish an hourly solar radiation data bank for the entirety of Morocco. This data bank will contain the energetic components (global, diffuse, direct, and inclined solar radiation) and the spectral components (ultraviolet I UV , infrared I IR , and photosynthetically active radiation I PAR ). To create this database, in the beginning, we build up models for predicting the various components of the hourly solar radiation, from measurements provided by the different stations owned by the Laboratory of Solar Energy and Environment (LESE). Then, these equations will be verified by using statistical tests. Moreover, we compared our results with those obtained by similar studies. Finally, based on the daily database of global radiation provided by the Laboratory of Solar Energy and Environment, we created an hourly database that unites the various components of solar radiation over 10 years for the entirety of Morocco. Regarding the validity study, the statistical indicators showed that the used models have minimal errors that do not exceed, for the global radiation, -2.93% in Rabat, -3.9% in Tangier,-3.28% in Marrakech, and -0.85% in Fez, and for diffuse radiation, -1.09% in Rabat, -0.68% in Fez,-3.08% in Tangier, and -2.49% in Marrakech. These results show the good quality of the used estimation models. Thus, the data bank that we have realized will fill the gap of the hourly solar data and will meet the needs of engineers, installers of solar systems, and researchers who often need an extensive database.

Low Complexity Dimensioning of Sustainable Solar-Enabled Systems: A Case of Base Station

Solar-enabled systems are becoming popular for provisioning pollution-free and cost-effective energy solution. Dimensioning of a solar-enabled system requires estimation of appropriate size of photovoltaic (PV) panel as well as storage capacity while satisfying a given energy outage constraint. Dimensioning has strong impact on the user's quality of experience and network operator's interest in terms of energy outage and revenue. In this paper, dimensioning problem of solar-enabled communication nodes is analyzed in order to reduce the computation overhead, where stand-alone solar-enabled base station (SS-BS) is considered as a case study. For this purpose, hourly solar data of last 10 years has been taken into consideration for analysis. First, the power consumption model of BS is revised to save energy and increase revenue. Using the hourly solar data and power consumption profile, the lower bounds on panel size and storage capacity are obtained using the Gaussian mixture model, which provides a reduced search space for cost-optimal system dimensioning. Then, the cost function and energy outage probability are modeled as functions of panel size and number of battery units using curve fitting technique. The cost function is proven to be quasiconvex, whereas energy outage probability is proven to be convex function of panel size and number of battery units. These properties transform the cost-optimal dimensioning problem into a convex optimization framework, which ensures a global optimal solution. Finally, a Computationally-efficient Energy outage aware Cost-optimal Dimensioning Algorithm (CECoDA) is proposed to estimate the system dimension without requiring exhaustive search. The proposed framework is tested and validated on solar data of several cities; for illustration purpose, four cities, New Delhi, Itanagar, Las Vegas, and Kansas, located at diverse geographical regions, are considered. It is demonstrated that, the presented optimization framework determines the system dimension accurately, while reducing the computational overhead up to 94 percent and the associated energy requirement for computation with respect to the exhaustive search method used in the existing approaches. The proposed framework CECoDA takes advantage of the location-dependent unique solar profile, thereby achieving cost-efficient solar-enabled system design in significantly less time.

Tracking collector consideration of tilted collector solar updraft tower power plant under Malaysia climate conditions

SUPP (Solar Updraft Tower power plant) is a technology in the power generation sector. The power productivity and efficiency represent important performance characteristics of SUPP. In the present work a mathematical model was developed to estimate the performance of SUPP based on tracking solar collector consideration in Malaysia. The objective is to verify the suggested model and to optimize the slope angle of tilted tracking solar collector. Basically, the hourly solar data were analysed considering solar azimuth angle for tracking case calculation to determine the solar energy incident on the collector. Then, the useful energy gain was calculated based on heat transfer relations. The model was validated with experimental work and well agreement was achieved. Results revealed that the SUPP of slope collector angle of 10° can produce higher power generation over the whole the year. Also, the tracking solar consideration enhanced the performance characteristics especially the power productivity by around 3.5 kW over that of fixed collector. The maximum collector and SUPP efficiencies of 51% and 0.165% respectively were obtained.

Stand-alone seawater RO (reverse osmosis) desalination powered by PV (photovoltaic) and PRO (pressure retarded osmosis)

A novel RO seawater desalination plant powered by PV (Photovoltaic) and PRO (PVROPRO) is proposed and the feasibility of two stand-alone schemes, SSRO (salinity-solar powered RO) operation and SRO (salinity powered RO) operation, are investigated. First, the stand-alone feasibility of the plant is thermodynamically analysed. In doing so, on the basis of mathematical models describing RO, PRO and the PV array, the stand-alone feasibility is numerically investigated and the feasible operational windows for the two operation schemes, SSRO and SRO, are identified. In addition, the detrimental effects, CP (concentration polarization) and RSP (reverse salt permeation) in the mass transfer, on the operational windows are investigated. Finally, a case study of the proposed PVROPRO plant is developed based on the hourly solar data of Perth Australia in a year. The highest weekly production rate is found to be almost 20 times the rate in PVRO in the same week. Annual production is increased more than nine times compared to the stand-alone PVRO plant. Furthermore, it is found that, due to detrimental effects the weekly PW (product water) production rate is decreased in the range of 16–20% and the overall annual reduction is 18.07%.

Satellite approach based on cloud cover classification: Estimation of hourly global solar radiation from meteosat images

Hourly global solar irradiation data useful for the design of solar energy conversion systems is generated using a new satellite based model called SICIC (solar irradiation from cloud image classification). It is a model built by processing high resolution visible Meteosat images and ground measurements of solar radiation flux collected in various locations of France during the 1994/95 period. Taking into account the hourly variability of solar radiation flux, SICIC begins by sorting the sun elevation angles into representative classes. For each location and each class, the clearness index is then computed, and the grey levels of the pixels of the visible Meteosat images are converted into cloud cover indexes. Next, two adjustable thresholds are used to split the set of cloud cover indices into three subsets representing clear, partly covered and overcast skies, respectively. Finally, three regression equations linking the clearness and cloud cover indices are obtained for the three sky categories. In these equations, the SICIC parameters (the regression coefficients and both thresholds) vary against the solar elevation angle. SICIC then yields a good estimate of the hourly global solar irradiation flux for every site displayed in the Meteosat images. This model is compared to GISTEL, which is another model governed by the same hypotheses as SICIC but differing by the invariability of its parameters in time. SICIC is found to be more accurate than GISTEL. In particular, the hourly solar data are estimated with an error (RMSE) varying from 32% to 12% for SICIC and 44% to 14% for GISTEL when the sun altitude increases from 15° to 75°. At the daily scale, SICIC is also more efficient than GISTEL. It has been satisfactorily applied to other sites of France and Algeria. The tests made on Wefax and B2 Meteosat images show that this model can be easily extended to other satellite images.