Distributed energy resources integration and demand response: The role of stochastic demand modelling

  • Emilio J. Palacios-García
  • , Antonio Moreno-Muñoz
  • , Isabel Santiago-Chiquero
  • , José María Flores-Arias
  • , Francisco J. Bellido-Outeiriño

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

Abstract

The chapter has presented the current context of demand modelling with a focus on stochastic bottom-up techniques. This methodology has been contextualised between all other strategies, pointing out the reasons and arguments that make this approach the most suitable in the context of this book. Next, the methodology for implementing this modelling technique has been shown, addressing the main parts of the system, as well as the basis and fundamentals of each of them. Subsequently, the simulation procedure that is employed for generating the results has been explained by means of detailed flow charts, listing the main input parameters and how they can be obtained. Finally, the application areas have been discussed. The validity of this model for demand prediction has been shown, although its stochastic nature does not make it the most suitable tool for accurate energy predictions. However, it has shown a unique ability in the fields of energy policy assessment, demand response strategies development, and distribute energy resources integration and planning, all of these due to its capability of simulating the appliances at a low level and always in relation to human behaviour. This emphasises the important role that stochastic modelling techniques can play in the energy planning and management sector.

Original languageEnglish
Title of host publicationLarge Scale Grid Integration of Renewable Energy Sources, 2nd Edition
Subtitle of host publicationSolutions and technologies
PublisherInstitution of Engineering and Technology
Pages223-254
Number of pages32
ISBN (Electronic)9781839538438
ISBN (Print)9781839538421
DOIs
Publication statusPublished - 1 Jan 2024
Externally publishedYes

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