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|q (electronic bk.)
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|a 3030476022
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|z 3030476014
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|z 9783030476014
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|a 10.1007/978-3-030-47602-1
|2 doi
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|a 10.1007/978-3-030-47
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|a com.springer.onix.9783030476021
|b Springer Nature
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|a TK1191
|b .V57 2020eb
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|a HCDD
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|a Baringo, Luis,
|e author.
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|a Virtual power plants and electricity markets :
|b decision making under uncertainty /
|c Luis Baringo, Morteza Rahimiyan.
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|a Cham, Switzerland :
|b Springer,
|c 2020.
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|a 1 online resource
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a Includes bibliographical references and index.
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|a Intro -- Preface -- Contents -- 1 Virtual Power Plants -- 1.1 Background -- 1.2 Overview of Electricity Markets -- 1.3 Virtual Power Plants and Smart Grids -- 1.4 Decision Making Under Uncertainty -- 1.4.1 Stochastic Programming -- 1.4.2 Robust Optimization -- 1.5 Operation and Expansion Strategies for Virtual Power Plants -- 1.5.1 Operation Strategies -- 1.5.2 Expansion Planning Strategies -- 1.6 Scope of the Book -- References -- 2 Virtual Power Plant Model -- 2.1 Introduction -- 2.2 Notation -- 2.2.1 Indexes -- 2.2.2 Sets -- 2.2.3 Parameters -- 2.2.4 Variables -- 2.3 Demands
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|a 2.4 Conventional Power Plants -- 2.5 Stochastic Renewable Production Facilities -- 2.6 Energy Storage Units -- 2.7 Network -- 2.8 Smart Grid Technology -- 2.9 Summary and Further Reading -- 2.10 GAMS Codes -- 2.10.1 Flexible Demand -- 2.10.2 Conventional Power Plant -- 2.10.3 Stochastic Renewable and Storage Units -- 2.10.4 Network Constraints -- References -- 3 Optimal Scheduling of a Risk-Neutral Virtual Power Plant in Energy Markets -- 3.1 Introduction -- 3.2 Problem Description -- 3.2.1 Notation -- 3.2.1.1 Indexes -- 3.2.1.2 Sets -- 3.2.1.3 Parameters -- 3.2.1.4 Variables
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|a 3.2.2 Scheduling Problem -- 3.2.3 Decision and Information Flow -- 3.3 Deterministic Approach -- 3.3.1 Deterministic Scheduling in the Day-Ahead Energy Market -- 3.3.2 Deterministic Scheduling in the Real-Time Energy Market -- 3.4 Stochastic Programming Approach -- 3.4.1 Uncertainty Model -- 3.4.2 Stochastic Scheduling in the Day-Ahead Energy Market -- 3.4.3 Stochastic Scheduling in the Real-Time Energy Market -- 3.5 Participation of Virtual Power Plants in Futures Markets -- 3.6 Summary and Further Reading -- 3.7 GAMS Codes -- 3.7.1 Deterministic Scheduling in the Day-Ahead Energy Market
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|a 3.7.2 Deterministic Scheduling in the Real-Time Energy Market -- 3.7.3 Stochastic Scheduling in the Day-Ahead Energy Market -- 3.7.4 Stochastic Scheduling in the Real-Time Energy Market -- References -- 4 Optimal Scheduling of a Risk-Averse Virtual Power Plant in Energy Markets -- 4.1 Introduction -- 4.2 Notation -- 4.2.1 Indexes -- 4.2.2 Sets -- 4.2.3 Parameters -- 4.2.4 Variables -- 4.3 Stochastic Programming Approach -- 4.3.1 Problem Description -- 4.3.2 Uncertainty Model -- 4.3.3 Formulation -- 4.4 Robust Optimization Approach -- 4.4.1 Problem Description -- 4.4.2 Uncertainty Model
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|a 4.4.3 Formulation -- 4.5 Hybrid Stochastic-Robust Optimization Approach -- 4.5.1 Problem Description -- 4.5.2 Uncertainty Model -- 4.5.3 Formulation -- 4.6 Adaptive Robust Optimization Approach -- 4.6.1 Problem Description -- 4.6.2 Formulation -- 4.6.3 Uncertainty Set -- 4.6.4 Feasibility of Operating Decision Variables -- 4.6.5 Detailed Formulation -- 4.6.6 Solution Procedure -- 4.6.6.1 Master Problem -- 4.6.6.2 Subproblem -- 4.6.6.3 Solution Algorithm -- 4.7 Summary and Further Reading -- 4.8 GAMS Codes -- 4.8.1 Stochastic Programming Approach -- 4.8.2 Robust Optimization Approach
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|a This textbook provides a detailed analysis of operation and planning problems faced by virtual power plants participating in different electricity markets. The chapters address in-depth, topics such as: optimization, market power, expansion, and modelling uncertainty in operation and planning problems of virtual power plants. The book provides an up-to-date description of decision-making tools to address challenging questions faced by virtual power plants such as: How can virtual power plants optimize their participation in electricity markets? How can a virtual power plant exercise market power? How can virtual power plants be optimally expanded? How can uncertainty be efficiently modelled in the operation and planning problems of virtual power plants? The book is written in a tutorial style and modular format, and includes many illustrative examples to facilitate comprehension. It is intended for a diverse audience including advanced undergraduate and graduate students in the fields of electric energy systems, operations research, and economics. Practitioners in the energy sector will also benefit from the concepts and techniques presented in this book. In particular, this book: Provides students with the GAMS codes to solve the examples in the book; Provides a basis for the formulation of decision-making problems under uncertainty; Contains a blend of theoretical concepts and practical applications that are developed as working algorithms.
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|a Electric power-plants
|x Decision making.
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|a Electric power-plants
|x Management.
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650 |
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|a Electric utilities
|x Management.
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|a Electric utilities
|x Decision making.
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|a Alternative & renewable energy sources & technology.
|2 bicssc
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|a Energy technology & engineering.
|2 bicssc
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|a Operational research.
|2 bicssc
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|a Electrical engineering.
|2 bicssc
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|a Technology & Engineering
|x Power Resources
|x Alternative & Renewable.
|2 bisacsh
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|a Technology & Engineering
|x Power Resources
|x General.
|2 bisacsh
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|a Business & Economics
|x Operations Research.
|2 bisacsh
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|a Technology & Engineering
|x Machinery.
|2 bisacsh
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|a Electric power-plants
|x Management
|2 fast
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|a Electric utilities
|x Decision making
|2 fast
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|a Electric utilities
|x Management
|2 fast
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655 |
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|a Electronic books.
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700 |
1 |
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|a Rahimiyan, Morteza,
|e author.
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758 |
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|i has work:
|a Virtual power plants and electricity markets (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGFgrfWwT98rvKcBdfqpHd
|4 https://id.oclc.org/worldcat/ontology/hasWork
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776 |
0 |
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|i Print version:
|a Baringo, Luis.
|t Virtual power plants and electricity markets.
|d Cham, Switzerland : Springer, 2020
|z 3030476014
|z 9783030476014
|w (OCoLC)1150958023
|
856 |
4 |
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|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-47602-1
|y Click for online access
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|a SPRING-ENERGY2020
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|a 92
|b HCD
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