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Joint RES and distribution network expansion planning under a demand response framework

Record Type:	Electronic resources : Monograph/item
Title/Author:	Joint RES and distribution network expansion planning under a demand response framework/ Javier Contreras, Miguel Asensio, Pilar Meneses de Quevedo, Gregorio Muñoz-Delgado, and Sergio Montoya-Bueno.
Author:	Contreras, Javier,
other author:	Asensio, Miguel,
Published:	London, UK :Academic Press is an imprint of Elsevier, : 2016.,
Description:	1 online resource (vi, 102 p.).
[NT 15003449]:	Front Cover; Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework; Copyright Page; Contents; 1 Introduction; 1.1 Historical Background and Motivation; 1.2 Outline; 2 Renewable Power Generation Models; 2.1 Photovoltaic Energy; 2.1.1 Introduction; 2.1.2 Power Output and I-V Curves; 2.1.3 Parameters and Operating Conditions; 2.1.4 Models for Photovoltaic Systems; 2.1.4.1 Progensa's Model [37]; 2.1.4.2 Atwa's Model [38]; 2.1.4.3 Borowy's Model [39]; 2.2 Wind Energy; 2.2.1 Introduction; 2.2.2 Impact of Height; 2.2.3 Wind Generation Model; 3 Uncertainty Modeling.
[NT 15003449]:	3.1 Introduction3.2 Method Based on Load, Wind, and Irradiation Curves; 3.2.1 Step 1; 3.2.2 Step 2; 3.2.3 Step 3; 3.2.4 Step 4; 3.2.5 Step 5; 3.2.6 Step 6; 3.2.7 Step 7; 4 Demand Response Modeling; 4.1 Demand Response Modeling; 4.1.1 Incentive-Based Programs (IBP); 4.1.2 Price-Based Programs (PBP); 4.2 Formulation; 4.3 Methodologies to Include Short-Term DR Into Expansion Planning; 5 Energy Storage Systems Modeling; 5.1 Benefits Derived From the Use of ESS; 5.1.1 Technical Benefits; 5.1.2 Economic Benefits; 5.2 ESS Technologies; 5.3 Storage Unit Model; 6 Optimization Problem Formulation.
[NT 15003449]:	6.1 Objective Function6.2 Constraints; 6.2.1 Integrality Constraints; 6.2.2 Balance Equations; 6.2.3 Kirchhoff's Voltage Law; 6.2.4 Voltage Limits; 6.2.5 Capacity Limits for Feeders; 6.2.6 Capacity Limits for Transformers; 6.2.7 Capacity Limits for Generators; 6.2.8 Unserved Energy; 6.2.9 DG Penetration Limit; 6.2.10 Capacity Limits for Storage; 6.2.11 Investment Constraints; 6.2.12 Utilization Constraints; 6.2.13 Investment Limits; 6.2.14 Radiality Constraints; 6.2.15 Demand Response to Load Level-Changing Prices; 6.2.16 Generic Storage Formulation; 6.3 Linearizations; 6.3.1 Energy Losses.
[NT 15003449]:	6.3.2 Kirchhoff's Voltage Law7 Case Study; 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; 8 Summary and Conclusions; 8.1 Summary; 8.2 Conclusions; Nomenclature; 1 Sets and Indexes; 2 Parameters; 3 Variables; References; Back Cover.
Subject:	Electric power systems - Mathematical models. -
Online resource:	https://www.sciencedirect.com/science/book/9780128053225
ISBN:	9780081009536 (electronic bk.)

Joint RES and distribution network expansion planning under a demand response framework
Contreras, Javier,

Joint RES and distribution network expansion planning under a demand response framework[electronic resource] /Javier Contreras, Miguel Asensio, Pilar Meneses de Quevedo, Gregorio Muñoz-Delgado, and Sergio Montoya-Bueno. - London, UK :Academic Press is an imprint of Elsevier,2016. - 1 online resource (vi, 102 p.).

Includes bibliographical references.

Front Cover; Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework; Copyright Page; Contents; 1 Introduction; 1.1 Historical Background and Motivation; 1.2 Outline; 2 Renewable Power Generation Models; 2.1 Photovoltaic Energy; 2.1.1 Introduction; 2.1.2 Power Output and I-V Curves; 2.1.3 Parameters and Operating Conditions; 2.1.4 Models for Photovoltaic Systems; 2.1.4.1 Progensa's Model [37]; 2.1.4.2 Atwa's Model [38]; 2.1.4.3 Borowy's Model [39]; 2.2 Wind Energy; 2.2.1 Introduction; 2.2.2 Impact of Height; 2.2.3 Wind Generation Model; 3 Uncertainty Modeling.

Joint RES and Distribution Network Expansion Planning under a Demand Response Framework explains the implementation of algorithms needed for joint expansion planning of distributed generation and the distribution network models. It discusses how to expand the generation and distribution network 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 the quality required. This book discusses the outcomes of the models discussed and factors such as the locations and sizes 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 more and more significant role in future expansion planning model. The present study stresses their relevance, including additional considerations to the planning model. Investigates the costs and benefits of deploying energy storage systems (ESS) and DRExplores distribution and generation expansion planningAnalyses and addresses power flow constraints and the impact of real time pricing mechanismsDetails the RES integration challenge at length.

ISBN: 9780081009536 (electronic bk.)Subjects--Topical Terms:

678375
Electric power systems
--Mathematical models.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: TK1005

Dewey Class. No.: 621.3101/5118

Joint RES and distribution network expansion planning under a demand response framework
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245 1 0 $a Joint RES and distribution network expansion planning under a demand response framework $h [electronic resource] / $c Javier Contreras, Miguel Asensio, Pilar Meneses de Quevedo, Gregorio Muñoz-Delgado, and Sergio Montoya-Bueno.
260 $a London, UK : $b Academic Press is an imprint of Elsevier, $c 2016.
300 $a 1 online resource (vi, 102 p.).
504 $a Includes bibliographical references.
505 0 $a Front Cover; Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework; Copyright Page; Contents; 1 Introduction; 1.1 Historical Background and Motivation; 1.2 Outline; 2 Renewable Power Generation Models; 2.1 Photovoltaic Energy; 2.1.1 Introduction; 2.1.2 Power Output and I-V Curves; 2.1.3 Parameters and Operating Conditions; 2.1.4 Models for Photovoltaic Systems; 2.1.4.1 Progensa's Model [37]; 2.1.4.2 Atwa's Model [38]; 2.1.4.3 Borowy's Model [39]; 2.2 Wind Energy; 2.2.1 Introduction; 2.2.2 Impact of Height; 2.2.3 Wind Generation Model; 3 Uncertainty Modeling.
505 8 $a 3.1 Introduction3.2 Method Based on Load, Wind, and Irradiation Curves; 3.2.1 Step 1; 3.2.2 Step 2; 3.2.3 Step 3; 3.2.4 Step 4; 3.2.5 Step 5; 3.2.6 Step 6; 3.2.7 Step 7; 4 Demand Response Modeling; 4.1 Demand Response Modeling; 4.1.1 Incentive-Based Programs (IBP); 4.1.2 Price-Based Programs (PBP); 4.2 Formulation; 4.3 Methodologies to Include Short-Term DR Into Expansion Planning; 5 Energy Storage Systems Modeling; 5.1 Benefits Derived From the Use of ESS; 5.1.1 Technical Benefits; 5.1.2 Economic Benefits; 5.2 ESS Technologies; 5.3 Storage Unit Model; 6 Optimization Problem Formulation.
505 8 $a 6.1 Objective Function6.2 Constraints; 6.2.1 Integrality Constraints; 6.2.2 Balance Equations; 6.2.3 Kirchhoff's Voltage Law; 6.2.4 Voltage Limits; 6.2.5 Capacity Limits for Feeders; 6.2.6 Capacity Limits for Transformers; 6.2.7 Capacity Limits for Generators; 6.2.8 Unserved Energy; 6.2.9 DG Penetration Limit; 6.2.10 Capacity Limits for Storage; 6.2.11 Investment Constraints; 6.2.12 Utilization Constraints; 6.2.13 Investment Limits; 6.2.14 Radiality Constraints; 6.2.15 Demand Response to Load Level-Changing Prices; 6.2.16 Generic Storage Formulation; 6.3 Linearizations; 6.3.1 Energy Losses.
505 8 $a 6.3.2 Kirchhoff's Voltage Law7 Case Study; 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; 8 Summary and Conclusions; 8.1 Summary; 8.2 Conclusions; Nomenclature; 1 Sets and Indexes; 2 Parameters; 3 Variables; References; Back Cover.
520 $a Joint RES and Distribution Network Expansion Planning under a Demand Response Framework explains the implementation of algorithms needed for joint expansion planning of distributed generation and the distribution network models. It discusses how to expand the generation and distribution network 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 the quality required. This book discusses the outcomes of the models discussed and factors such as the locations and sizes 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 more and more significant role in future expansion planning model. The present study stresses their relevance, including additional considerations to the planning model. Investigates the costs and benefits of deploying energy storage systems (ESS) and DRExplores distribution and generation expansion planningAnalyses and addresses power flow constraints and the impact of real time pricing mechanismsDetails the RES integration challenge at length.
588 0 $a Online resource; title from PDF title page (EBSCO, viewed May 20, 2016).
650 0 $a Electric power systems $x Mathematical models. $3 678375
650 0 $a Electric power production $x Mathematical models. $3 2089102
650 0 $a Electric power distribution $x Mathematical models. $3 3462971
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Asensio, Miguel, $e author. $3 3462967
700 1 $a Quevedo, Pilar Meneses de. $3 3462968
700 1 $a Muñoz-Delgado, Gregorio. $3 3462969
700 1 $a Montoya-Bueno, Sergio. $3 3462970
856 4 0 $u https://www.sciencedirect.com/science/book/9780128053225