Development of the simplified predictive model for the estimation of annual PV energy production: A case study for Odisha

Tarai, Rakesh Kumar; Chandola, Vikash; Kale, Paresh

doi:10.1109/ciact.2017.7977337

Cited by 3 publications

(2 citation statements)

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“…2, use the PV production data obtained for 1195 locations in Odisha using PVGIS method [9], after normalized to per kWp, to predict the outcome of PV plant [8]. The regression analysis by a robust least square method using Matlab curve fitting tool provides the coefficients of the functions for the proposed models.…”

Section: Methodology To Develop the Modelmentioning

confidence: 99%

“…The first model, Simplified Model (SFM) takes only three input variables (annual global radiation, ambient temperature, and temperature coefficient) to predict the output response of the PV system. SFM is further simplified, called as Further Simplified model (FSFM), which requires only two input values (annual global radiation and ambient temperature) to estimate the expected output energy production [8]. The aim of the paper is to analyze the preciseness of both the model's forecast for Odisha by validating the response on the generation and weather data collected from SN Mohanty solar power plant which runs with c-Si modules.…”

Section: Introductionmentioning

confidence: 99%

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Validation of predictive models to estimate annual PV production: A case study of odisha

Tarai¹,

Kale²

2016

ijsgce

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The decision to install a PV plant depends on three major factors: the climatic and environment conditions of the location, the viability of commercial operations, and the government policies. Economic feasibility of a PV system in the energy market is largely driven by the cost of technology, the cost of installation, and the yield of the plant. Considering uncertain nature of geographical parameters (solar radiation, temperature, dust accumulation, etc.), development of a reliable model to predict the energy output of a plant-to-be installed becomes essential. The model ensures the long-term performance criteria of the PV system. The proposed model considers a case study of Odisha by taking only two meteorological variables collected from 1195 locations: total annual incident global radiation on the PV module and annual average air temperature. The developed model is independent of longitude and latitude, elevation, and other environment conditions. Model is validated using the data collected from SN Mohanty solar power plant situated at Cuttack. The paper focuses on simplification at every stage of the development while validating the preciseness of the model.

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Section: Methodology To Develop the Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%