Impact assessment of short-term variability of solar radiation in Rajasthan using SRRA data

Trıpathy, Sujit Kumar; Mitra, Indradip; Heinemann, Detlev; Giridhar, G.; Gomathinayagam, S.

doi:10.1016/j.rser.2017.05.014

Cited by 14 publications

(7 citation statements)

References 14 publications

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“…For multiple-site analysis, similar procedures are repeated with averaged forecasted NWP model GHI values from all point locations under study. The forecasted GHI series, obtained by employing these two techniques, are validated against acquired GHI datasets from the SRRA stations in Rajasthan [75,122].…”

Section: Evaluation Of Irradiance Forecast For Rajasthan From Nwp Mod...mentioning

confidence: 99%

Short-term PV power forecasting in India: recent developments and policy analysis

Mitra¹,

Heinemann

Ramanan³

et al. 2022

Int J Energy Environ Eng

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With ambitious renewable energy capacity addition targets, there is an ongoing transformation in the Indian power system. This paper discusses the various applications of variable generation forecast, state-of-the-art solar PV generation forecasting methods, latest developments in generation forecasting regulations and infrastructure, and the new challenges introduced by VRE generation. Day-ahead NWP-based GHI forecasting are validated against ground measurements from single and multiple sites in India. Recommendations for improving overall the forecasting infrastructure in India are presented.

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Section: Evaluation Of Irradiance Forecast For Rajasthan From Nwp Mod...mentioning

confidence: 99%

Short-term PV power forecasting in India: recent developments and policy analysis

Mitra¹,

Heinemann

Ramanan³

et al. 2022

Int J Energy Environ Eng

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“…Meanwhile, it was found that solar PV did not show as much geographic smoothing as was seen for aggregated wind plants 25 , demonstrating consistency with a previous study 24 . The effect of spatial smoothing and its role in decreasing solar variability (step change) was investigated based on a clear sky index 26 , which showed that a minimum 60% of power variability was suppressed in Rajasthan for time intervals of 1–15 min.…”

Section: Introductionmentioning

confidence: 99%

“…Among existing studies, different metrics are used to characterize the smoothing effects. For example, extreme values are used in 19 , variance of step changes 21 , standard deviation (STD) of the step change/ramping rate 14 , 16 – 18 , 22 , 26 , STD of the production 23 , and Fourier transform estimates of the power spectral density (PSD) 15 , 24 , 25 . Timescales (durations) considered are mainly minutes 16 , 19 – 21 , hours 14 , 17 , 18 , 26 , months 23 and years 15 , 24 , 25 .…”

Section: Introductionmentioning

confidence: 99%

“…For example, extreme values are used in 19 , variance of step changes 21 , standard deviation (STD) of the step change/ramping rate 14 , 16 – 18 , 22 , 26 , STD of the production 23 , and Fourier transform estimates of the power spectral density (PSD) 15 , 24 , 25 . Timescales (durations) considered are mainly minutes 16 , 19 – 21 , hours 14 , 17 , 18 , 26 , months 23 and years 15 , 24 , 25 . Furthermore, the geographical scale for solar power aggregation varies with plant/site 16 , 19 – 21 , 27 , to state 15 , 18 , 23 , 24 , 26 and to sub-region 14 , 25 but with a limited number of PV sites/stations.…”

Section: Introductionmentioning

confidence: 99%

“…Timescales (durations) considered are mainly minutes 16 , 19 – 21 , hours 14 , 17 , 18 , 26 , months 23 and years 15 , 24 , 25 . Furthermore, the geographical scale for solar power aggregation varies with plant/site 16 , 19 – 21 , 27 , to state 15 , 18 , 23 , 24 , 26 and to sub-region 14 , 25 but with a limited number of PV sites/stations. Most existing studies have been focused on the impact of solar power aggregation on short and mid-term power variations in terms of fluctuations rather than long term variations in terms of intermittency.…”

Section: Introductionmentioning

confidence: 99%

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Solar power generation intermittency and aggregation

Zhang

Sterling

2022

Sci Rep

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The inherent intermittency of solar power due to diurnal and seasonal cycles has usually resulted in the need for alternative generation sources thereby increasing system operation costs. However, when solar power is spread over a large geographical area with significant time differences, the intermittency can be significantly reduced and also the electricity market balancing cost. The aim of this article is to address the fundamental scientific question on how the intermittency of solar power generation is affected by aggregation, which is of great interest in the wider power and energy community and would have profound impacts on the solar energy integration into the energy supply and Net-Zero Implementation. This article goes beyond the typical regional analysis by investigating solar power intermittency at 5 aggregation levels from a global perspective based on global 7 year hourly meteorological re-analysis data with a fine spatial resolution of $${0.25}^{\circ }\times {0.25}^{\circ } (\sim 28 \; \mathrm{km} \times 28 \; \mathrm{km})$$ 0.25 ∘ × 0.25 ∘ ( ∼ 28 km × 28 km ) . In the proposed assessment framework, a coefficient of variation (CV) is used to quantify solar power intermittency and hence characterize the potential benefits of wide area solar power aggregation. A duration curve is used to characterize the intermittency in terms of power availability and a probability density function is further employed to investigate the dispersion and scaling behavior of CV at different aggregation levels. The findings indicate that the CV of solar power generation of ‘Inner Mongolia’ in China drops from 129.65 to 105.65% in the level of ‘Asia’ (by 24% decrease), to 56.11% in ‘Asia-North_America’ (by 73.54% decrease) and to the smallest 43.50% in ‘Global’ (by 86.15% decrease), nearly 3.5 times of that in ‘Asia’; (b) the availability of solar power generation increases from 52.17% in Germany, to 73.30% in ‘Europe_EU_plus’, to 77.82% in ‘Europe’, to 98.59% in ‘Europe-North_America’ (80.60% in ‘Europe-Africa’, 96.90% in ‘Europe-Asia’), to 100% in ‘Global’. Finally, conclusions and recommendations are provided to support a Net-Zero strategy.

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Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions

2023

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Impact assessment of short-term variability of solar radiation in Rajasthan using SRRA data

Cited by 14 publications

References 14 publications

Short-term PV power forecasting in India: recent developments and policy analysis

Short-term PV power forecasting in India: recent developments and policy analysis

Solar power generation intermittency and aggregation

Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions

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