Optimization of Aggregated Energy Resources using Sequential Decision Making

Trishant Roy, Aryyama K. Jana, Kory W. Hedman

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

1 Scopus citations


Due to the limited non-renewable sources and focus on clean energy in the contemporary world, most governments are focusing more on renewable energy sources for electrical power. However, the unpredictable variations in the renewable energy source itself can pose serious threats to the grid's operation unless managed. A plausible solution is to manage a combination of resources that can complement each other's generation to meet the total demand reliably. In this paper, we consider a utility with solar energy as a renewable resource, battery for storage, and interaction with the electrical grid. The objective is to develop a decision-making approach to help the utilities better manage their resources to decide when and how to dispatch battery, solar power, and how much electricity to buy/sell from the grid. Here, the management problem has been formulated as Markov Decision Process. We have implemented and compared the performance of a conventional approach of dynamic programming and a Q-learning approach to solve the optimization problem. The advantages and disadvantages of these approaches are also highlighted in this paper.

Original languageEnglish (US)
Title of host publication2022 North American Power Symposium, NAPS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665499217
StatePublished - 2022
Event2022 North American Power Symposium, NAPS 2022 - Salt Lake City, United States
Duration: Oct 9 2022Oct 11 2022

Publication series

Name2022 North American Power Symposium, NAPS 2022


Conference2022 North American Power Symposium, NAPS 2022
Country/TerritoryUnited States
CitySalt Lake City


  • Battery storage
  • Q-learning
  • dynamic programming
  • sequential decision making

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization


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