Multi-Objective Energy Management System for Isolated Solar Microgrids using Pareto Q learning

Ayodele Benjamin Esan, Hussain Shareef, Nasir Saeed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Microgrids play a crucial role in the development of smart energy grids in developed countries and in addressing energy poverty in developing countries. However, accurately modeling the uncertainties associated with renewable distributed generation technologies (RDGs) proves challenging due to their stochastic nature, particularly when considering the non-convex constraints of microgrid components. This study focuses on a multi-objective formulation for an islanded solar microgrid, aiming to minimize operational costs (OC) while ensuring a minimum loss of load probability (LOLP). By applying the principle of Pareto-optimality, the problem is represented as a Markov Decision Process and solved using a Pareto-Q learning (PQL) algorithm. Real-time data from the IEEE open dataset repository was utilized to train the microgrid agent. The obtained results for the seven-day period considered revealed that the agent achieved an optimal policy for each day while still adhering to the state-of-charge constraint, and simultaneously obtaining the Pareto-front for each system state. In comparison to three baseline methods, the PQL agent exhibited an overall improvement of 25-45% across all reward values obtained, along with OC enhancements ranging from 40% to 43% respectively.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665471640
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023 - Wollongong, Australia
Duration: Dec 3 2023Dec 6 2023

Publication series

Name2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

Conference

Conference2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
Country/TerritoryAustralia
CityWollongong
Period12/3/2312/6/23

Keywords

  • Energy management system
  • Microgrids
  • Q learning
  • Reinforcement learning
  • Reliability

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Safety, Risk, Reliability and Quality

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