Nowcasting solar irradiance for effective solar power plants operation and smart grid management

Paulescu, Marius; Paulescu, Eugenia; Bădescu, Viorel

doi:10.1016/b978-0-12-817772-3.00009-4

Cited by 14 publications

(10 citation statements)

References 24 publications

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“…For the northern and southern parts of the Lubuskie Voivodeship, the average radiation values are 2.78 kWh/m 2 and 2.76 kWh/m 2 , respectively. The clearness index, expressing the relation of global solar radiation intensity measured at ground level to its equivalent estimated at the top of the atmosphere [63], in both cases, was very similar, and its fluctuations over the year are small. The greatest potential for generating energy from the Sun occurs in the summer (Figure 7).…”

Section: Methodsmentioning

confidence: 76%

Economic Profitability of a Hybrid Approach to Powering Residual Households from Natural Sources in Two Wind Zones of the Lubuskie Voivodeship in Poland

Kułyk

Augustowski

2021

Energies

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The research was a response to the search for alternative energy sources and the assessment of their profitability and legitimacy of use. The assessment used combined energy sources in the form of wind, solar, and natural gas energy. The research was carried out in various locations with varying degrees of sunlight and in various wind zones, which was motivated by the adopted strategy of increasing the importance of non-conventional energy sources and reducing greenhouse gas emissions. The evaluation was performed using the Homer Grid software. The studies showed the justification for the use of hybrid energy sources, combining renewable and non-renewable sources, at the current stage of development. In the conditions of the Lubuskie Voivodeship, the level of insolation was more important than the more favourable wind zone in such a model. Higher economic efficiency of the hybrid model was obtained in the southern location, with slightly less favourable conditions for wind installations. At the same time, the investments were economically profitable and allowed for their return in the perspective of at least eleven years, even at current prices.

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Section: Methodsmentioning

confidence: 76%

Economic Profitability of a Hybrid Approach to Powering Residual Households from Natural Sources in Two Wind Zones of the Lubuskie Voivodeship in Poland

Kułyk

Augustowski

2021

Energies

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“…This model utilizes the previous time step ( t − 1 ) values to predict the one‐step‐ahead ( t + 1 ) values 60 . As the forecast time horizon increases, the accuracy of the model decreases 61 . By Equation (16), a simple persistence model can be defined.…”

Section: Results Analysismentioning

confidence: 99%

“…60 As the forecast time horizon increases, the accuracy of the model decreases. 61 By Equation ( 16), a simple persistence model can be defined. It shows that the value of battery capacity ( b C) for future cycle, that is, at 1 step ahead cycle (t + 1) is equal to the capacity (C) observed at the present cycle (t).…”

Section: Persistence Vs Proposed 3 Models For Charging Profilementioning

confidence: 99%

Machinelearning‐basedapproach for useful capacity prediction ofsecond‐lifebatteries employing appropriate input selection

Bhatt

Ongsakul²,

Madhu

et al. 2021

Intl J of Energy Research

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Electric vehicle-discarded second-life batteries still contain 80% of usable capacity and can serve as a low-cost alternative for microgrid storage applications where the battery storage capacity is flexible against transport applications. By accurately predicting the remaining useful capacity or state of health of these batteries, using the data from their first life operation, their costeffectiveness for microgrid energy management can be analyzed. For this purpose, three machine learning models are proposed here. The input parameters for the models are selected from the charging and discharging profiles of batteries, considering both the aging and regeneration phenomenon. Eight different input cases with and without K-fold (K = 10) cross-validation are used for training the proposed models. Based on the comparative analysis it is found that all the models trained with K-fold cross-validation, show minimum error as compared to without K-fold. The forecasting results from multiple approaches showed that the long short term memory model trained with battery discharging profile outperformed other models, quantified by multiple error indices, including root mean square error (0.009147), mean absolute error (0.005841), and R 2 (0.9713). The robustness of the model is validated with multiple battery datasets. Further, the study illustrates the importance of activation functions, in machine learning models used for forecasting.

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“…Furthermore, when comparison against a reference baseline method is required, there may not be an overall agreement on the details of the implementation of such method and there is still debate regarding this topic, to which works such as [22] attempt to set the details for a standardized method. Additionally, as solar power forecasting has transitioned from the naïve persistence (irradiance I remains constant through forecast window, Equation (2), [23][24][25]) towards the smart persistence as the reference method (clear sky index K t cs remains constant through forecast window, Equation (3), [25,26]), the readers must be aware of which reference was used, making analysis and result comparison more difficult.Î…”

Section: Current State Of the Art In Solar Power Forecasting Performance Assessmentmentioning

confidence: 99%

“…To reduce forecast uncertainty due to the clear sky model, especially in cases of marked changes in Linke turbidity during nonclear conditions (as demonstrated in [35]), K t will be used instead of K tcs . As stated in Section 1, persistence forecasting as consensus baseline method has transitioned from naïve persistence (i.e., irradiance remains constant, Equation ( 2)) [23][24][25] towards smart persistence (i.e., clear sky index remains constant, Equation ( 3)) [25,26]. However, the estimation of the clear sky irradiance is subject to astronomical uncertainties (solar geometry modeling, Earth-Sun distance modeling and solar constant estimation uncertainty), atmospheric properties uncertainty (such as aerosol optical depth and integrated water vapor column estimation, among others, with specific effects depending on the clear sky model being used) and the intrinsic clear sky modeling error (which is model dependent).…”

Section: Dn I = (Ghi − Dh I) Sin α (9)mentioning

confidence: 99%

Short-Term Deterministic Solar Irradiance Forecasting Considering a Heuristics-Based, Operational Approach

2021

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Solar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are needed for better grid integration. This work presents a novel deterministic forecast method considering: irradiance pattern classification, Markov chains, fuzzy logic and an operational approach. The method developed was applied in a rolling manner for six years to a target location with no prior data to assess performance and its changes as new local data becomes available. Clearness index, diffuse fraction and irradiance hourly forecasts are analyzed on a yearly basis but also for 20 day types, and compared against smart persistence. Results show the proposed method outperforms smart persistence by ~10% for clearness index and diffuse fraction on the base case, but there are significant differences across the 20 day types analyzed, reaching up to +60% for clear days. Forecast lead time has the greatest impact in forecasting performance, which is important for any practical implementation. Seasonality in data gaps or rejected data can have a definite effect in performance assessment. A novel, comprehensive and detailed analysis framework was shown to present a better assessment of forecasters’ performance.

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Nowcasting solar irradiance for effective solar power plants operation and smart grid management

Cited by 14 publications

References 24 publications

Economic Profitability of a Hybrid Approach to Powering Residual Households from Natural Sources in Two Wind Zones of the Lubuskie Voivodeship in Poland

Economic Profitability of a Hybrid Approach to Powering Residual Households from Natural Sources in Two Wind Zones of the Lubuskie Voivodeship in Poland

Machinelearning‐basedapproach for useful capacity prediction ofsecond‐lifebatteries employing appropriate input selection

Short-Term Deterministic Solar Irradiance Forecasting Considering a Heuristics-Based, Operational Approach

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