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Robotic Expert System for Energy Management in Distributed Grid Ecosystem

Author

Listed:
  • Ononiwu Gordon Chiagozie

    (Federal University of Technology Owerri, Owerri, Nigeria)

  • Kennedy Chinedu Okafor

    (Federal University of Technology, Owerri, Nigeria)

  • Nwaokolo F I

    (Federal University of Technology Owerri, Owerri, Nigeria)

Abstract

A robotic expert system (RES) for energy management (EM) in community-based micro-grids is developed using a fuzzy computational scheme. Within the micro-grid multi-dimensional space, embedded algorithms for residential homes, sectors and central controller units are introduced to perform EM in a collaborative manner. Demand response and load shedding are carried out within the community micro-grid to ascertain the behavioral responses based on changes in power demand levels. Various tests are carried out with an observable low error margin. It was observed that the system reduced the total power demand on the micro-grid by 20% of the total distributed power. Micro-grid RES, neuro-fuzzy control (NFC), and support vector regression (SVR) evaluations are compared considering the home units at 40kW of the generated capacity. The results gave a 35.79%, 31.58% and 32.63% energy demand, respectively. Consequently, RES provides a grid look-ahead prediction, annotated-self healing, and stability restoration.

Suggested Citation

  • Ononiwu Gordon Chiagozie & Kennedy Chinedu Okafor & Nwaokolo F I, 2020. "Robotic Expert System for Energy Management in Distributed Grid Ecosystem," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 9(1), pages 1-26, January.
    • Handle: RePEc:igg:jeoe00:v:9:y:2020:i:1:p:1-26
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