A microgrid energy management system based on chance-constrained stochastic optimization and big data analytics

Carlos Antonio Marino, Mohammad Marufuzzaman

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

A Microgrid (MG) is a promising distributed technology to solve todays energy challenges. They are changing how electricity is produced, transmitted, and distributed, enabling to capture massive amounts of data from sensors, and other electrical infrastructures. However, recent advances in modeling and optimization of MG neither integrate the use of big data technologies aggressively nor focus on developing an optimal operational strategy for a single building. To bridge this gap, this research proposes to use Apache Spark to enhance the performance of a scalable stochastic optimization model for an MG for multiple buildings, and to ensure that a significant portion of the wind power output will be utilized. The decision model is formulated as a chance constraint two-stage optimization problem to obtain operation decisions for a behind-the-meter topology. The comparison between the current practice of using historical data and integrating Apache Spark technologies demonstrates the superiority of the streaming data as energy management strategy. Experiments under different settings show that using big data strategy, the model can (1) achieve more cost savings of the total system, (2) increase resiliency to power disturbances, and (3) build a data analytics framework to enhance the decision-making process.

Original languageEnglish
Article number106392
JournalComputers and Industrial Engineering
Volume143
DOIs
StatePublished - May 2020
Externally publishedYes

Keywords

  • Big data
  • Microgrid
  • Spark streaming
  • Stochastic optimization
  • Sustainability
  • Wind power

Fingerprint

Dive into the research topics of 'A microgrid energy management system based on chance-constrained stochastic optimization and big data analytics'. Together they form a unique fingerprint.

Cite this