Intelligent Approaches to Support Demand Response in Microgrid Planning

Rahmat Khezri, Amin Mahmoudi, Hirohisa Aki

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Microgrids are facing several challenges by increasing the penetration level of distributed renewable energy resources (DRERs) and energy storage systems (ESSs). However, the cost of renewable generation and storage components is not yet affordable for a secure economic integration. Planning of microgrid to use the optimal capacity of components is, accordingly, an important stage to achieve the minimum cost. Demand response (DR) is an efficient solution to decrease the capacity of components while making microgrids more reliable. By changing the electricity consumption pattern of customers using DR programs, microgrid's load can better match DRERs generation and stored energy of ESSs. Application of DR in microgrids is, however, a complex program. This is because of the variety of available generation-storage components, massive data analysis of weather forecasts for DRER generation, electricity pattern prediction, and comfort level of consumers for DR application. This chapter investigates the application of intelligent approaches to support DR for microgrids planning. The planning problem is introduced by considering the available components, operation, and required data to solve the problem. The types of DR programs in microgrids are identified and explained. Data mining techniques are discussed to analyze the large amount of data in microgrid. The intelligent approaches to support DR and their applications and effects are described.

Original languageEnglish
Title of host publicationIntelligent Data Mining and Analysis in Power and Energy Systems
Subtitle of host publicationModels and Applications for Smarter Efficient Power Systems
EditorsZita Vale, Tiago Pinto, Michael Negnevitsky, Ganesh Kumar Venayagamoorthy
Place of PublicationHoboken, New Jersey
Number of pages20
ISBN (Electronic)9781119834052, 9781119834038, 9781119834045
ISBN (Print)9781119834021
Publication statusPublished - 2023

Publication series

NameIEEE Press Series on Power and Energy Systems
PublisherIEEE Press


  • Artificial intelligence
  • Data mining
  • Demand response
  • Microgrid
  • Optimal planning


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