NDLI: Stochastic PV model for power system planning applications

Content Provider	IET Digital Library
Author	Sumaiti, Ameena Saad Al Ahmed, Mohammed Hassan Rivera, Sergio Moursi, Mohammed Shawky El Salama, Mohamed M. A. Alsumaiti, Tareefa
Abstract	Planning photovoltaic (PV) power systems integration into the grid necessitates accurate modelling of renewable power generation. Global solar irradiance, weather temperature and PV power losses due to overheating specifically in hot regimes are major factors contributing to PV power generation uncertainty. This study targets demonstrating the effectiveness of deploying advanced five parameter probabilistic distribution ‘Wakeby’ for modelling PV uncertain power generation, measured as a function of such factors, in power system planning applications. The impact of different approaches for incorporating weather temperature on PV energy estimation is studied. Wakeby-Monte Carlo Simulation for PV power data training with an emphasis on MCS stopping criteria for such advanced distribution is presented. The model is tested and verified in 31-bus distribution system to demonstrate its effectiveness over other literature uncertainty modelling approaches when planning integration of PV systems' integration into the grid to minimise the grid losses cost. Real PV power measurements are utilised as benchmark verifying the accuracy and suitability of the presented uncertainty modelling approach. Simulation results demonstrate a small error of $4.7 in the expected annual cost of grid losses when deploying Wakeby model compared to the benchmark case and that error can vary significantly when deploying other PV models.
Starting Page	3168
Ending Page	3179
Page Count	12
ISSN	17521416
Volume Number	13
e-ISSN	17521424
Issue Number	Issue 16, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/13/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0345
Journal	IET Renewable Power Generation
Publisher Date	2019-09-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	31-bus Distribution System Advanced Five Parameter Probabilistic Distribution Wakeby Grid Loss Incorporating Weather Temperature Monte Carlo Method Optimisation Technique Photovoltaic Power System Power Grid Power System Planning Application Presented Uncertainty Modelling Approach Probability Theory PV Energy Estimation PV Model PV Power Data Training PV Power Generation Uncertainty PV Power Loss PV Power Measurement PV System PV Uncertain Power Generation Renewable Power Generation Solar Power Stations Statistics Stochastic Linearised SCUC Stochastic PV Model Wakeby Model Wakeby-Monte Carlo Simulation
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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