Document Type : Research Article
Authors
1 Sustainable and Renewable Energy Development Authority (SREDA), Dhaka-1000, Bangladesh.
2 Institute of Appropriate Technology, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh.
3 Department of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology, Chittagong-4349, Bangladesh.
Abstract
The output power of a Solar Photovoltaic (SPV) plant depends mainly on the solar irradiance on the photovoltaic (PV) modules. Therefore, short-term variations in solar irradiance cause variations in the output power of solar power plants, making solar photovoltaic grid integration unstable. Solar irradiance variations mainly occur due to the weather conditions of a given location, especially the movement of clouds and seasonal effects. Consequently, assessing the variability of solar irradiance over the course of a year is essential to identify the extent of these variations. Geographical dispersion and cloud enhancement are two important factors affecting output power variations in a PV plant. Geographical dispersion reduces such variations, while cloud enhancement increases them. This study utilizes two ground station-based solar Global Horizontal Irradiance (GHI) datasets to assess the viability of solar irradiance in the Chittagong division of Bangladesh. The analysis reveals a significant number of days with high short-term solar irradiance variation. In addition to solar irradiance, the frequency and voltage at the interconnection point are important for safe grid integration. It was observed that the grid frequency exceeded the range specified by the International Electrotechnical Commission (IEC), but remained within the grid code range of Bangladesh. Grid voltage variation at the interconnection substation was found to be within the standard range during the daytime, but low voltage was observed at the grid level during the rest period. Therefore, it is crucial to implement necessary preventive measures to reduce short-term variations for the safe grid integration of large-scale variable SPV plants.
Keywords
- Assessment of Solar Irradiance
- Short-term variation of Solar Irradiance
- Integration Challenges of Variable Renewable Energy
- Voltage-frequency aspects of Solar Photovoltaic grid integration
Main Subjects
- Blanc P, Espinar B, Geuder N, Gueymard C, Meyer R, Pitz-Paal R, et al. Direct normal irradiance related definitions and applications: The circumsolar issue. Solar Energy. 2014 Dec;110:561–77. (https://doi.org/10.1016/j.solener.2014.10.001).
- Keeratimahat K, Bruce A, MacGill I. Partial curtailment to firm photovoltaic generation dispatch. In: 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE; 2019. p. 1–5. (https://doi.org/10.1109/APPEEC45492.2019.8994464).
- Järvelä M, Lappalainen K, Valkealahti S. Characteristics of the cloud enhancement phenomenon and PV power plants. Solar Energy. 2020 Jan;196:137–45. (https://doi.org/10.1016/j.solener.2019.11.090).
- Jazayeri M, Jazayeri K, Uysal S. Generation of spatially dispersed irradiance time-series based on real cloud patterns. Solar Energy. 2017 Dec;158:977–94. (https://doi.org/10.1016/j.solener.2017.10.026).
- Ahmed R, Sreeram V, Mishra Y, Arif MD. A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization. Renewable and Sustainable Energy Reviews. 2020 May;124:109792. (https://doi.org/10.1016/j.rser.2020.109792).
- Tahir ZR, Asim M. Surface measured solar radiation data and solar energy resource assessment of Pakistan: A review. Renewable and Sustainable Energy Reviews. 2018 Jan;81:2839–61. (https://doi.org/10.1016/j.rser.2017.06.090).
- Kainat EngrMGS, Alam EngrMdR, Masud EngrMdT. Towards a Sustainable Energy Future. Grid Integration of Solar Energy: A case study on 20 MW Solar Power Plant of Teknaf Solar Energy Ltd. [Internet]. Vol. 1, Towards Sustainable Energy Future. Dhaka: SREDA, Bangladesh; 2021 Nov [cited 2023 Mar 30]. Available from: http://www.sreda.gov.bd
- Van Haaren R, Morjaria M, Fthenakis V. Empirical assessment of short-term variability from utility-scale solar PV plants. Progress in Photovoltaics: Research and Applications. 2014 May;22(5):548–59. (https://doi.org/10.1002/pip.2302).
- Sengupta M, Xie Y, Lopez A, Habte A, Maclaurin G, Shelby J. The National Solar Radiation Data Base (NSRDB). Renewable and Sustainable Energy Reviews. 2018 Jun;89:51–60. (https://doi.org/10.1016/j.rser.2018.03.003).
- Sivaneasan B, Yu CY, Goh KP. Solar Forecasting using ANN with Fuzzy Logic Pre-processing. Energy Procedia. 2017 Dec;143:727–32. (https://doi.org/10.1016/j.egypro.2017.12.753).
- Shuvho MdBA, Chowdhury MA, Ahmed S, Kashem MA. Prediction of solar irradiation and performance evaluation of grid connected solar 80KWp PV plant in Bangladesh. Energy Reports. 2019 Nov;5:714–22. (https://doi.org/10.1016/j.egyr.2019.06.011).
- Boopathi K, Ramaswamy S, Kirubakaran V, Uma K, Saravanan G, Thyagaraj S, et al. Economic investigation of repowering of the existing wind farms with hybrid wind and solar power plants: a case study. International Journal of Energy and Environmental Engineering. 2021 Dec 17;12(4):855–71. (https://doi.org/10.1007/s40095-021-00391-3).
- Karthikeyan V, Janarthanan S. Yield factor of grid connected solar photovoltaic system-a case study. Journal of Advanced Research in Dynamical and Control Systems. 2017 Jan 1;9:206–13. (https://www.academia.edu/42707694/Yield_Factor_of_Grid_Connected_Solar_Photovoltaic_System_A_Case_Study).
- Denholm P, Margolis RM. Evaluating the limits of solar photovoltaics (PV) in electric power systems utilizing energy storage and other enabling technologies. Energy Policy. 2007 Sep;35(9):4424–33. (https://doi.org/10.1016/j.enpol.2007.03.004).
- Zhang J, Zhao L, Deng S, Xu W, Zhang Y. A critical review of the models used to estimate solar radiation. Renewable and Sustainable Energy Reviews. 2017 Apr;70:314–29. (https://doi.org/10.1016/j.rser.2016.11.124).
- Choi Y, Suh J, Kim SM. GIS-Based Solar Radiation Mapping, Site Evaluation, and Potential Assessment: A Review. Applied Sciences. 2019 May 13;9(9):1960. (https://doi.org/10.3390/app9091960).
- Wei CC. Predictions of Surface Solar Radiation on Tilted Solar Panels using Machine Learning Models: A Case Study of Tainan City, Taiwan. Energies (Basel). 2017 Oct 20;10(10):1660. (https://doi.org/10.3390/en10101660).
- Carmona F, Orte PF, Rivas R, Wolfram E, Kruse E. Development and Analysis of a New Solar Radiation Atlas for Argentina from Ground-Based Measurements and CERES_SYN1deg data. The Egyptian Journal of Remote Sensing and Space Science. 2018 Dec;21(3):211–7. (https://doi.org/10.1016/j.ejrs.2017.11.003).
- Jamil B, Akhtar N. Estimation of diffuse solar radiation in humid-subtropical climatic region of India: Comparison of diffuse fraction and diffusion coefficient models. Energy. 2017 Jul;131:149–64. (https://doi.org/10.1016/j.energy.2017.05.018).
- Annual Report 2019-2020 of SREDA [Internet]. Dhaka; 2020. Available from: http://www.sreda.gov.bd
- Customized Bangladesh Map - Google My Maps [Internet]. [cited 2023 Mar 26]. Available from: https://www.google.com/maps/d/u/0/edit?hl=en&mid=1eKcsqjkBzI3jgVfOkJ6xpVPVU1guOtg&ll=23.608281830845563%2C92.00898324794439&z=7
- Global Solar Atlas [Internet]. [cited 2023 Mar 27]. Available from: https://globalsolaratlas.info/download/bangladesh
- IEC 61727:2004 | IEC Webstore | invertor, smart city, LVDC [Internet]. [cited 2023 Mar 27]. Available from: https://webstore.iec.ch/publication/5736
- Bangladesh Energy Regulatory Commission (Electricity Grid Code) Regulations, 2019 [Internet]. Dhaka; 2020 [cited 2023 Mar 30]. Available from: http://www.berc.org.bd
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