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PLANNING for the RENEWABLE FUTURE LONG-TERM MODELLING and TOOLS to EXPAND VARIABLE RENEWABLE POWER in EMERGING ECONOMIES Copyright © IRENA 2017

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PLANNING for the RENEWABLE FUTURE LONG-TERM MODELLING and TOOLS to EXPAND VARIABLE RENEWABLE POWER in EMERGING ECONOMIES Copyright © IRENA 2017 PLANNING FOR THE RENEWABLE FUTURE LONG-TERM MODELLING AND TOOLS TO EXPAND VARIABLE RENEWABLE POWER IN EMERGING ECONOMIES Copyright © IRENA 2017 Unless otherwise stated, this publication and material featured herein are the property of the International Renewable Energy Agency (IRENA) and are subject to copyright by IRENA. Material in this publication may be freely used, shared, copied, reproduced, printed and/or stored, subject to proper attribution. Material in this publication attributed to third parties may be subject to third-party copyright and separate terms of use and restrictions, including restrictions in relation to any commercial use. ISBN 978-92-95111-05-9 (Print) ISBN 978-92-95111-06-6 (PDF) Citation: IRENA (2017), Planning for the Renewable Future: Long-term modelling and tools to expand variable renewable power in emerging economies, International Renewable Energy Agency, Abu Dhabi. About IRENA The International Renewable Energy Agency (IRENA) is an intergovernmental organisation that supports countries in their transition to a sustainable energy future and serves as the principal platform for international co-operation, a centre of excellence, and a repository of policy, technology, resource and financial knowledge on renewable energy. IRENA promotes the widespread adoption and sustainable use of all forms of renewable energy, including bioenergy, geothermal, hydropower, ocean, solar and wind energy in the pursuit of sustainable development, energy access, energy security and low-carbon economic growth and prosperity. Acknowledgements This report benefited from the reviews and comments of numerous experts, including: Doug Arent (US National Renewable Energy Laboratory—NREL), Jorge Asturias (Latin American Energy Organization—OLADE), Emna Bali (Tunisian Company of Electricity and Gas—STEG), Morgan D. Bazilian (World Bank Group), Rim Boukhchina (Regional Center for Renewable Energy and Energy Efficiency—RCREEE), Jean Paul Dean (University College of Cork), Fernando De Sisternes (World Bank Group), Virginia Echinope (Ministry of Industry, Energy and Mining (Uruguay)), Hannele Holtinen (VTT Technical Research Center of Finland), Luis Munuera (International Energy Agency—IEA), Bruno Merven (University of Cape Town), Crescent Mushwana (Council for Scientific and Industrial Research—CSIR), Wouter Nijs (European Commission), Kris Poncelet (University of Leuven), Yvonne Scholz (German Aerospace Center—DLR), Chong Suk Song (World Bank Group), Dalius Tarvydas (Lithuanian Energy Institute), Mario Tot (International Atomic Energy Agency—IAEA), Maria Rosa Virdis (Italian National Agency for New Technologies, Energy and Sustainable Economic Development—ENEA), Manuel Welsch (IAEA), Jarrad Wright (CSIR) and Owen Zinaman (NREL). Jennifer DeCesaro, Francisco Gafaro, Dolf Gielen, Paul Komor, Isaac Portugal, Emanuele Taibi and Dennis Volk (IRENA) also provided valuable input. IRENA would like to extend its gratitude to the participants of a brainstorming session, “The modelling of renewables for policy making", held during the 33rd edition of the International Energy Workshop (IEW) on 5 June 2014 in Beijing, China; and also to the participants of the “Expert workshop on how to address variable renewables in long-term energy planning (AVRIL)”, which took place on 2 and 3 March 2015 at the IRENA Innovation and Technology Centre in Bonn, Germany. This report was prepared by Asami Miketa (IRENA) and Falko Ueckerdt (Potsdam Institute for Climate Impact Research— PIK). Special thanks are due to Sean Collins and Spyridon Pantelis for their research assistance in the preparation of this study and also to Daniel Russo (IRENA) and Geoffrey Lean (consultant) for structural review and editing of the report. Disclaimer This publication and the material featured herein are provided “as is”, for informational purposes. All reasonable precautions have been taken by IRENA to verify the reliability of the material featured in this publication. Neither IRENA nor any of its officials, agents, data or other third-party content providers or licensors provides any warranty, including as to the accuracy, completeness, or fitness for a particular purpose or use of such material, or regarding the non-infringement of third-party rights, and they accept no responsibility or liability with regard to the use of this publication and the material featured therein. The information contained herein does not necessarily represent the views of the Members of IRENA. The mention of specific companies or certain projects, products or services does not imply that they are endorsed or recommended by IRENA in preference to others of a similar nature that are not mentioned. The designations employed and the presentation of material herein do not imply the expression of any opinion on the part of IRENA concerning the legal status of any region, country, territory, city or area or of its authorities, or concerning the delimitation of frontiers or boundaries. Front cover design based on Denholm and Hand (2011). Photographs from Shutterstock unless otherwise indicated. PLANNING FOR THE RENEWABLE FUTURE LONG-TERM MODELLING AND TOOLS TO EXPAND VARIABLE RENEWABLE POWER IN EMERGING ECONOMIES CONTENTS Figures ..................................................................................................................................................................4 Tables .................................................................................................................................................................... 6 Boxes ..................................................................................................................................................................... 7 Abbreviations ...................................................................................................................................................... 8 Executive Summary ..........................................................................................................................................10 Introduction: Long-term planning for power sector transformation ............................16 Part One: Planning the transition to variable renewables 1. The planning process ....................................................................................................... 26 1.1 Outlining planning components: Techno-economic assessments across planning time horizons .....27 1.2 Moving towards a more integrated approach for transition planning ....................................................30 2. Key planning implications of variable renewable energy deployment....................... 32 2.1 Key properties of variable renewable energy ................................................................................................33 2.2 Planning for adequate firm capacity ...............................................................................................................34 2.3 Planning for system flexibility ..........................................................................................................................36 2.4 Planning for transmission capacity and voltage control ............................................................................39 2.5 Planning for stability .......................................................................................................................................... 40 2.6 Summary of long-term planning solutions for reliability with variable renewable energy..........................42 3. Key investment implications of variable renewable energy deployment ................... 43 2 PLANNING FOR THE RENEWABLE FUTURE Part Two: Long-term energy models for transition planning 4. A common challenge – long-term model resolution .................................................... 50 4.1 Model resolution in time and space ..................................................................................................................51 4.2 A cross-cutting solution: increasing temporal and spatial resolution .....................................................56 5. Representing firm capacity .............................................................................................61 5.1 Better calibration of time slices using variable renewable power generation data ..............................62 5.2 Adding capacity credit constraints .................................................................................................................70 6. Representing flexibility ....................................................................................................74 6.1 Incorporating constraints on flexibility provision .........................................................................................75 6.2 Validating flexibility balance in a system ...................................................................................................... 90 6.3 Coupling with production cost models ...........................................................................................................91 7. Representing transmission capacity .............................................................................. 94 7.1 Linking grid investment needs with variable renewable energy expansion ............................................95 7.2 Site-specific representations of generation and transmission needs ......................................................97 8. Representing stability constraints on variable renewable energy penetration .......
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