Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework - 1st Edition - ISBN: 9780128053225, 9780081009536

Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework

1st Edition

Authors: Javier Contreras Miguel Asensio Pilar Meneses de Quevedo Gregorio Muñoz-Delgado Sergio Montoya-Bueno
eBook ISBN: 9780081009536
Paperback ISBN: 9780128053225
Imprint: Academic Press
Published Date: 3rd May 2016
Page Count: 110
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Description

Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework explains the implementation of the algorithms needed for joint expansion planning of distributed generation and distribution network models, discussing how to expand the generation and distribution network by adding renewable generation, demand response, storage units, and new assets (lines and substations) so that the current and future energy supply in islands is served at a minimum cost, and with quality requirements.

This book discusses the outcomes of the models discussed, including factors such as the location and size of new generation assets to be installed. It also introduces other issues relevant to the planning of insular distribution systems, including DR and hybrid storage. DR and ESS will play a much more significant role in future expansion planning models, where the present study stresses their relevance, including additional considerations to the planning model.

Key Features

  • Investigates the costs and benefits of deploying energy storage systems (ESS) and DR
  • Explores distribution and generation expansion planning
  • Analyzes and addresses power flow constraints and the impact of real time pricing mechanisms
  • Details the RES integration challenge at length

Readership

Power system engineers, energy engineers, electrical engineers, energy policy professionals and electrical engineering academics

Table of Contents

  • Chapter 1. Introduction
    • Abstract
    • 1.1 Historical Background and Motivation
    • 1.2 Outline
  • Chapter 2. Renewable Power Generation Models
    • Abstract
    • 2.1 Photovoltaic Energy
    • 2.2 Wind Energy
  • Chapter 3. Uncertainty Modeling
    • Abstract
    • 3.1 Introduction
    • 3.2 Method Based on Load, Wind, and Irradiation Curves
  • Chapter 4. Demand Response Modeling
    • Abstract
    • 4.1 Demand Response Modeling
    • 4.2 Formulation
    • 4.3 Methodologies to Include Short-Term DR Into Expansion Planning
  • Chapter 5. Energy Storage Systems Modeling
    • Abstract
    • 5.1 Benefits Derived From the Use of ESS
    • 5.2 ESS Technologies
    • 5.3 Storage Unit Model
  • Chapter 6. Optimization Problem Formulation
    • Abstract
    • 6.1 Objective Function
    • 6.2 Constraints
    • 6.3 Linearizations
  • Chapter 7. Case Study
    • Abstract
    • 7.1 La Graciosa Case Study
    • 7.2 Results Without DR and Hybrid Storage
    • 7.3 Results With DR
    • 7.4 Results With Hybrid Storage
    • 7.5 Results With DR and Hybrid Storage
    • 7.6 Impact of DR and Hybrid Storage in Generation and Distribution Expansion Planning
    • 7.7 Cost–Benefit Analysis
  • Chapter 8. Summary and Conclusions
    • Abstract
    • 8.1 Summary
    • 8.2 Conclusions
  • Nomenclature
    • 1 Sets and Indexes
    • 2 Parameters
    • 3 Variables
  • References

Details

No. of pages:
110
Language:
English
Copyright:
© Academic Press 2016
Published:
Imprint:
Academic Press
eBook ISBN:
9780081009536
Paperback ISBN:
9780128053225

About the Author

Javier Contreras

Javier Contreras (IEEE SM’05, IEEE F’15) received the B.S. degree in electrical engineering from the University of Zaragoza, Zaragoza, Spain, in 1989, the M.Sc. degree from the University of Southern California, Los Angeles, in 1992, and the Ph.D. degree from the University of California, Berkeley, in 1997. He is currently Full Professor at the University of Castilla – La Mancha, Ciudad Real, Spain. His research interests include power systems planning, operations and economics, and electricity markets.

Affiliations and Expertise

Professor at University of Castilla – La Mancha, Ciudad Real, Spain

Miguel Asensio

Pilar Meneses de Quevedo

Gregorio Muñoz-Delgado

Sergio Montoya-Bueno