Big Data Analytics in Maharashtra’s State Sector Thermal Power Generation: A Case Study Using Pivot Tables

• Published in: INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT Vol. 9; no. 8; pp. 1 - 9
• Main Authors: SB, Dalvi, Karmarkar, Sumedh P, Kolhe, Prakash, Jadhav, Vishnu, Yadav, Rutik P
• Format: Journal Article
• Language: English
• Published: 14.08.2025
• ISSN: 2582-3930; 2582-3930
• DOI: 10.55041/IJSREM51815

Abstract          The rapid expansion of digital data in the energy sector has created new opportunities for performance monitoring and strategic planning using Big Data Analytics. This case study investigates sector-wise power generation performance in Maharashtra from April to December 2023, with a focus on applying Microsoft Excel Pivot Tables as a first-level analytical tool. The study uses a cleaned dataset of 83 entries to compare actual vs. programmed generation across major power sectors—coal, hydro, nuclear, gas, thermal, and state-operated plants. Pivot tables were used to calculate sector-wise achievement rates, Plant Load Factors (PLF), and year-on-year (YoY) performance indicators. Total actual generation was 554,039.8 MU against a target of 552,350 MU, achieving 100.31% of the planned output. Hydro and nuclear sectors exceeded their targets, while thermal and gas-based units showed minor shortfalls. Notable underperformance was observed in specific private and gas units, highlighting operational or data-reporting gaps. This study demonstrates how simple spreadsheet-based tools can yield valuable insights from large energy datasets. It also advocates for future integration of real-time, IoT-enabled systems and predictive analytics to support data-driven decision-making in power sector planning