Marjerie Suresh

Marjerie Suresh

Graduate Student at UC Davis

Intelligent Interconnection of Operating Micro-Grid and Irrigation System in Dharnai - A Rural Indian Scenario

Done at 2019 IEEE Global Humanitarian Technology Conference (GHTC), 2019

Hari Vignesh Baskar, Marjerie Suresh, Abishek Coimbatore Sridhar, Sai Shankar Muthukrishnan, Vineeth Vijayaraghavan

Overview

  • Designed a dynamic load profile for agricultural demand in rural India with crop yield and weather data.
  • Developed the Smart Energy Transfer Algorithm (SETA) on Python to promote interconnection of systems and efficient energy transfer and utilization between the two systems.
  • Improves the system efficiency by 10.5 percent and agricultural efficiency by 13 percent.
  • Published in the 2019 IEEE Global Humanitarian Technology Conference proceedings. (here)

The code for the work is found here.

Citation

H. V. Baskar, S. Marjerie, A. C. Sridhar, S. S. Muthukrishnan and V. Vijayaraghavan, “Intelligent Interconnection of Operating Micro-grid and Irrigation System in Dharnai - A Rural Indian Scenario,” 2019 IEEE Global Humanitarian Technology Conference (GHTC), Seattle, WA, USA, 2019, pp. 1-7, doi: 10.1109/GHTC46095.2019.9033013.

Abstract

This paper presents a flexible energy transfer algorithm for the pre-existing Indian rural micro-grid and the irrigation system. Dharnai, a small village in Jehanabad district, Bihar (25.0125N, 84.9792E) uses the Dharnai Microgrid system (DMG) for community electrification and its agricultural load is serviced by Dharnai Irrigation System (DIS). The irrigation load demand for the project lifetime of 20 years is modeled using climatic variations like evapotranspiration, rainfall and crop pattern. Since the DIS and DMG systems are not integrated the excess energy generated is rendered unused. The efficient utilization of excess energy is achieved by interconnecting the two systems as they are less than 2 km apart. In this paper, a smart energy transfer algorithm that can be implemented on pre-existing systems is developed to predict and transfer energy. The algorithm is made flexible and dynamic so that the efficiency of a preferred system can be boosted based on village community requirements. A relative efficiency increase in the overall system of 10.57% is obtained using the algorithm and on implementing preferential energy transfer, a relative efficiency increase of 7.8% and 13.05% is achieved in DIS and DMG respectively.

Extended the algorithm for a cluster of microgrids in the paper, “Smart Energy Routing For Rural Islanded Microgrid Clusters”.