Design of a Stand-Alone PV System for Irrigation in Rural India Using SAM Software

Abstract

India's commitment to renewable energy has been reinforced through its ranking as the fourth-largest global solar power capacity holder, as reported in the Ministry of New and Renewable Energy's 2022 year-end review. Non-fossil fuel-based power generation has reached 42.26% of India's total installed capacity. In this context, solar pump installations for agricultural use, under the component – A, B, C, are in progress. This study proposes the deployment of stand-alone solar power plants using the System Advisor Model (SAM) in three distinct regions of Andhra Pradesh, India. Aimed at facilitating the adoption of green energy and income generation through surplus power sales in rural communities, this work is grounded in a comprehensive survey conducted across eight diverse locations: Ganayigudem, Manduru, Jogannapalem, Vegavaram, Veeravallipalem, Ainavillilanka, Seetharampuram, and Naguladevupadu. Real-time power requirement data was collected from 112 farmers across approximately 882 acres of land. These locations were divided into three sets, designated as set-A, set-B, and set-C, using a clustering approach. The energy requirements for agricultural purposes were derived from the survey data, enabling the near-practical construction of a solar plant via the SAM software, using actual weather data and load requirements. The Levelized cost of energy nominal (LOCE) was calculated to be 3.38 $/kWh and 2.7 $/kWh per cent of land area for set-A, 3.18 $/kWh and 2.54 $/kWh for set-B, and 3.33 $/kWh and 2.66 $/kWh for set-C. These figures encapsulate the cost of constructing and maintaining the solar plant over its lifespan. The lower LOCE for set-B compared to set-A is attributed to the larger plant size in set-A. The feasibility of solar plant construction is enhanced by government-provided tax benefits. However, it is noteworthy that changes in weather patterns may introduce slight discrepancies in practical implementation, as the current results are based on past weather data.