A review of spatial resolution and regionalisation in national-scale energy systems optimisation models

Abstracts National-scale energy systems optimisation models (ESOMs) have been limited in the past by the lack of sub-national data availability leading to aggregated treatment of spatial dynamics. This review paper first determines how a combination of supply and demand data requirements and socio-economic, environmental and political issues, can challenge the results of a low-spatial resolution model. It also demonstrates the incompleteness of single region ESOMs that do not capture sufficient spatial detail. Specifically, 36 multi-regional ESOMs from 22 countries with varying levels of spatiotemporal resolution, sectoral focus and planning horizon are systematically identified and comprehensively analysed. The review reveals that existing temporally explicit ESOMs with a single sector coverage can permit regional disaggregation up to the first-level administrative divisions within a country (such as state and province) while maintaining computationally tractable. Findings from the literature review also show when, how, and to what extent higher spatial resolution impact on the results of energy system analysis. (1) Finer spatial resolution in ESOMs offers significant added value for regions with heterogeneous renewable potential or across regions with higher variability in energy service demands. However, in homogeneous areas, aggregated single-region modelling is more efficient. (2) Spatially resolved models can significantly change the results of the scenarios with very high shares of variable renewable energies. But it is not straightforward to find a direct relationship between the level of geographic disaggregation and penetration of renewable energies. This trade-off should be explored case-by-case. (3) Total system costs can be under- or over-estimated in various levels of spatial resolutions. Disaggregation of renewable resources leads to lower costs, and disaggregation of transmission grids leads to higher costs.

[1]  Markus Groissböck,et al.  Are open source energy system optimization tools mature enough for serious use? , 2019, Renewable and Sustainable Energy Reviews.

[2]  Ken’ichi Matsumoto,et al.  Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris Agreement targets in Japan , 2018, Applied Energy.

[3]  F. Wiese,et al.  Conceptual model of the industry sector in an energy system model: A case study for Denmark , 2018, Journal of Cleaner Production.

[4]  G Anandarajah.  What Role can Wind Play to Meet the UK & Scotland Renewable & Climate Policies? , 2014 .

[5]  U. Fahl,et al.  Improved representation of investment decisions in the German energy supply sector: An optimization approach using the TIMES model , 2019, Energy Strategy Reviews.

[6]  P. Kyle,et al.  Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework , 2014 .

[7]  J. Glynn,et al.  Zero carbon energy system pathways for Ireland consistent with the Paris Agreement , 2019 .

[8]  W. Short,et al.  Evaluating renewable portfolio standards and carbon cap scenarios in the U.S. electric sector , 2010 .

[9]  Lion Hirth,et al.  Carpe diem: A novel approach to select representative days for long-term power system modeling , 2016 .

[10]  James Price,et al.  The role of floating offshore wind in a renewable focused electricity system for Great Britain in 2050 , 2018, Energy Strategy Reviews.

[11]  Muhammad Aslam Uqaili,et al.  Long-term electricity demand forecast and supply side scenarios for Pakistan (2015–2050): A LEAP model application for policy analysis , 2018, Energy.

[12]  Frieder Borggrefe,et al.  The gap between energy policy challenges and model capabilities , 2019, Energy Policy.

[13]  Amy Sopinka,et al.  Optimal electricity system planning in a large hydro jurisdiction: Will British Columbia soon become a major importer of electricity? , 2013 .

[14]  R. Pietzcker,et al.  Application of a high-detail energy system model to derive power sector characteristics at high wind and solar shares , 2017 .

[15]  R. Weijermars.  US shale gas production outlook based on well roll-out rate scenarios , 2014 .

[16]  B. V. Wæhrens,et al.  Assessment of Energy Arbitrage Using Energy Storage Systems: A Wind Park’s Perspective , 2021, Energies.

[17]  T. Mai,et al.  Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective , 2017 .

[19]  Adam Hawkes,et al.  Energy systems modeling for twenty-first century energy challenges , 2014 .

[20]  Pierre Meukam,et al.  Electricity generation technology options under the greenhouse gases mitigation scenario: Case study of Cameroon , 2016 .

[21]  Erika Zvingilaite,et al.  Human health-related externalities in energy system modelling the case of the Danish heat and power sector , 2011 .

[22]  Brian Vad Mathiesen,et al.  A review of computer tools for analysing the integration of renewable energy into various energy systems , 2010 .

[23]  M. Gargiulo,et al.  Capturing the long-term interdependencies between building thermal energy supply and demand in urban planning strategies , 2020, Applied Energy.

[24]  Leo Schrattenholzer,et al.  MESSAGE-MACRO: Linking an energy supply model with a macroeconomic module and solving it iteratively , 2000 .

[25]  Subhes C. Bhattacharyya,et al.  A review of energy system models , 2010 .

[26]  Karen Byskov Lindberg,et al.  Analysis of the EU renewable energy directive by a techno-economic optimisation model , 2013 .

[27]  J. P. Deane,et al.  Assessing power system security. A framework and a multi model approach , 2015 .

[28]  S. Gyamfi,et al.  Technical and economic feasibility of a 50 MW grid-connected solar PV at UENR Nsoatre Campus , 2020 .

[29]  Carlos Silva,et al.  High-resolution modeling framework for planning electricity systems with high penetration of renewables , 2013 .

[30]  Amit Kanudia,et al.  Low carbon standard and transmission investment analysis in the new multi-region US power sector model FACETS , 2014 .

[31]  Brian Ó Gallachóir,et al.  A new hybrid approach for evaluating technology risks and opportunities in the energy transition in Ireland , 2020 .

[32]  Vahid Aryanpur,et al.  Power sector development in Iran: A retrospective optimization approach , 2017 .

[33]  John P. Weyant,et al.  End use technology choice in the National Energy Modeling System (NEMS): An analysis of the residential and commercial building sectors , 2013 .

[34]  Martin Drechsler,et al.  Efficient and equitable spatial allocation of renewable power plants at the country scale , 2017, Nature Energy.

[35]  E. Shafiei,et al.  Transition to Alternative Fuel Vehicles and Implications for Energy Demand and GHG Emissions in Iran , 2015 .

[36]  David O. Wood,et al.  Energy System Modeling and Forecasting , 1976 .

[37]  W. Short.  Regions in Energy Market Models , 2007 .

[38]  Zhenhong Lin,et al.  Interaction of consumer preferences and climate policies in the global transition to low-carbon vehicles , 2018, Nature Energy.

[39]  Zhenwei Liu,et al.  A Dimensionless Parameter Analysis of a Cylindrical Tube Electromagnetic Vibration Energy Harvester and Its Oscillator Nonlinearity Effect , 2018 .

[40]  Osamu Akashi,et al.  Technological feasibility and costs of achieving a 50 % reduction of global GHG emissions by 2050: mid- and long-term perspectives , 2012, Sustainability Science.

[41]  Francisca Jalil-Vega,et al.  Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities , 2020 .

[42]  Pantelis Capros,et al.  Energy system impacts and policy implications of the European Intended Nationally Determined Contribution and low-carbon pathway to 2050 , 2017 .

[43]  John D. Sterman,et al.  All models are wrong: reflections on becoming a systems scientist† , 2002 .

[44]  T. Mai,et al.  Setting cost targets for zero-emission electricity generation technologies , 2019, Applied Energy.

[45]  Jyotirmay Mathur,et al.  Long-term energy system planning considering short-term operational constraints , 2019, Energy Strategy Reviews.

[46]  Joseph F. DeCarolis,et al.  A review of approaches to uncertainty assessment in energy system optimization models , 2018, Energy Strategy Reviews.

[47]  Christos S. Ioakimidis,et al.  On the planning and analysis of Integrated Community Energy Systems: A review and survey of available tools , 2011 .

[48]  H. Ravn,et al.  The role of district heating in the future Danish energy system , 2012 .

[49]  Nicholas Frank Pidgeon,et al.  Transforming the UK energy system: public values, attitudes and acceptability: synthesis report , 2013 .

[50]  Pantelis Capros,et al.  Implications of delaying transport decarbonisation in the EU: A systems analysis using the PRIMES model , 2018, Energy Policy.

[51]  Wolf Fichtner,et al.  Meeting the Modeling Needs of Future Energy Systems , 2017 .

[52]  Jintae Kim,et al.  Long-term energy strategy scenarios for South Korea: Transition to a sustainable energy system , 2019, Energy Policy.

[53]  A. Hawkes,et al.  The effect of spatial resolution on outcomes from energy systems modelling of heat decarbonisation , 2018, Energy.

[54]  Hannele Holttinen,et al.  Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches , 2019, WIREs Energy and Environment.

[55]  Cord Kaldemeyer,et al.  Multi-objective investment optimization for energy system models in high temporal and spatial resolution , 2020 .

[56]  Garvin A. Heath,et al.  Long-term implications of sustained wind power growth in the United States: Potential benefits and secondary impacts , 2016 .

[57]  Rolf Wüstenhagen,et al.  Whatever the customer wants, the customer gets? Exploring the gap between consumer preferences and default electricity products in Germany , 2013 .

[58]  Hailong Li,et al.  Multi-region optimal deployment of renewable energy considering different interregional transmission scenarios , 2016 .

[59]  Keywan Riahi,et al.  The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp): An open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development , 2019, Environ. Model. Softw..

[60]  Adam Hawkes,et al.  Spatially resolved model for studying decarbonisation pathways for heat supply and infrastructure trade-offs , 2018 .

[61]  Brian Ó Gallachóir,et al.  The impact of sub-hourly modelling in power systems with significant levels of renewable generation , 2014 .

[62]  R. Kannan,et al.  A Long-Term Electricity Dispatch Model with the TIMES Framework , 2013, Environmental Modeling & Assessment.

[63]  M. Tavoni,et al.  An inter-model assessment of the role of direct air capture in deep mitigation pathways , 2019, Nature Communications.

[64]  Pei Liu,et al.  Multi-regional power generation expansion planning with air pollutants emission constraints , 2019, Renewable and Sustainable Energy Reviews.

[66]  Zheng Li,et al.  A multi-region load dispatch model for the long-term optimum planning of China’s electricity sector , 2017 .

[67]  Nina Juul,et al.  Optimal configuration of an integrated power and transport system , 2011 .

[68]  Nouredine Hadjsaid,et al.  Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools , 2015 .

[69]  F. Urban,et al.  Modelling energy systems for developing countries , 2007 .

[70]  Tieju Ma,et al.  A multi-regional energy transport and structure model for China’s electricity system , 2018, Energy.

[71]  Venkat Krishnan,et al.  Evaluating the value of high spatial resolution in national capacity expansion models using ReEDS , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[72]  W. Cole,et al.  The impact of planning reserve margins in long-term planning models of the electricity sector , 2019, Energy Policy.

[73]  Kenneth Bernard Karlsson,et al.  Residential heat pumps in the future Danish energy system , 2016 .

[74]  Neil Strachan,et al.  Regional winners and losers in future UK energy system transitions , 2016 .

[75]  Mark Z. Jacobson,et al.  Temporal and spatial tradeoffs in power system modeling with assumptions about storage: An application of the POWER model , 2016 .

[76]  Thomas Pregger,et al.  Comparison of spatially and temporally resolved energy system models with a focus on Germany's future power supply , 2019 .

[77]  Nikolaos E. Koltsaklis,et al.  Review of models for integrating renewable energy in the generation expansion planning , 2019, Applied Energy.

[78]  B. Ó Gallachóir,et al.  Investigating the energy transition to a coal free residential sector in Kazakhstan using a regionally disaggregated energy systems model , 2018, Journal of Cleaner Production.

[79]  Dieter Helm,et al.  Energy policy: security of supply, sustainability and competition , 2002 .

[80]  Bernd Möller,et al.  End-use energy savings and district heating expansion in a local renewable energy system: A short-term perspective , 2012 .

[81]  Veit Hagenmeyer,et al.  The strong effect of network resolution on electricity system models with high shares of wind and solar , 2021 .

[82]  Pierluigi Siano,et al.  An overview of energy planning in Iran and transition pathways towards sustainable electricity supply sector , 2019, Renewable and Sustainable Energy Reviews.

[83]  Michael C. Georgiadis,et al.  An integrated stochastic multi-regional long-term energy planning model incorporating autonomous power systems and demand response , 2015 .

[84]  Clara F. Heuberger,et al.  The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment , 2020 .

[85]  Pei Liu,et al.  A multi-region optimization planning model for China's power sector , 2015 .

[86]  C. Fleischer.  Minimising the effects of spatial scale reduction on power system models , 2020 .

[87]  M. Rocco,et al.  Modelling for power generation sector in Developing Countries: Case of Egypt , 2018, Energy.

[88]  R. Martínez-Gordón,et al.  A review of the role of spatial resolution in energy systems modelling: Lessons learned and applicability to the North Sea region , 2021 .

[89]  Eamonn Mulholland,et al.  A Long-Term Strategy to Decarbonise the Danish Inland Passenger Transport Sector , 2018 .

[90]  Tom Brown,et al.  The role of spatial scale in joint optimisations of generation and transmission for European highly renewable scenarios , 2017, 2017 14th International Conference on the European Energy Market (EEM).

[91]  Tom Kober,et al.  Long term evaluation of electric storage technologies vs alternative flexibility options for the Swiss energy system , 2019, Applied Energy.

[92]  N. Meinshausen,et al.  Greenhouse-gas emission targets for limiting global warming to 2 °C , 2009, Nature.

[93]  Sonia Yeh,et al.  Modal Shift of Passenger Transport in a TIMES Model: Application to Ireland and California , 2015 .

[94]  T. Burandt,et al.  Analyzing Scenarios for the Integration of Renewable Energy Sources in the Mexican Energy System—An Application of the Global Energy System Model (GENeSYS-MOD) , 2019, Energies.

[95]  Maryse Labriet,et al.  A Canadian 2050 energy outlook: Analysis with the multi-regional model TIMES-Canada , 2013 .

[96]  Stefan Pfenninger,et al.  Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability , 2017 .

[97]  Christian von Hirschhausen,et al.  Pathways for Germany’s Low-Carbon Energy Transformation Towards 2050 , 2019, Energies.

[98]  P. Ferrao,et al.  Modeling hourly electricity dynamics for policy making in long-term scenarios , 2011 .

[99]  Mine Isik,et al.  Transportation emissions scenarios for New York City under different carbon intensities of electricity and electric vehicle adoption rates , 2021 .

[100]  Charles Zelek,et al.  The U.S. power sector decarbonization: Investigating technology options with MARKAL nine-region model , 2018, Energy Economics.

[101]  Alan H. Sanstad,et al.  Economic models for climate policy analysis: A critical discussion , 1998 .

[102]  D. Steinberg,et al.  Sensitivity of natural gas deployment in the US power sector to future carbon policy expectations , 2017 .

[103]  Yigang Wei,et al.  The decomposition of total-factor CO2 emission efficiency of 97 contracting countries in Paris Agreement , 2019, Energy Economics.

[104]  Dong Gu Choi,et al.  Quantitatively exploring the future of renewable portfolio standard in the Korean electricity sector via a bottom-up energy model , 2015 .

[105]  Jacopo Tattini,et al.  Reaching carbon neutral transport sector in Denmark – Evidence from the incorporation of modal shift into the TIMES energy system modeling framework , 2018 .

[106]  P. E. Grohnheit,et al.  A global renewable energy system: A modelling exercise in ETSAP/TIAM , 2011 .

[107]  Eric Lantz,et al.  Long-term implications of sustained wind power growth in the United States: Direct electric system impacts and costs , 2016 .

[108]  N. V. Beeck.  Classification of Energy Models , 1999 .

[109]  Tao Lv,et al.  Power system planning with increasing variable renewable energy: A review of optimization models , 2020 .

[110]  Jacopo Tattini,et al.  TIMES-DK: Technology-rich multi-sectoral optimisation model of the Danish energy system , 2019, Energy Strategy Reviews.

[111]  G. Mothé,et al.  Renewable energy in reducing greenhouse gas emissions: Reaching the goals of the Paris agreement in Brazil , 2020 .

[112]  Pantelis Capros,et al.  Outlook of the EU energy system up to 2050: The case of scenarios prepared for European Commission's “clean energy for all Europeans” package using the PRIMES model , 2018, Energy Strategy Reviews.

[113]  D. Ingham,et al.  Large scale integration of renewable energy sources (RES) in the future Colombian energy system , 2019, Energy.

[114]  S. Paltsev,et al.  Turkish energy sector development and the Paris Agreement goals: A CGE model assessment , 2018, Energy Policy.

[115]  From 2 °C to 1.5 °C: How Ambitious Can Ireland Be? , 2018 .

[116]  Detlef Stolten,et al.  A review of current challenges and trends in energy systems modeling , 2018, Renewable and Sustainable Energy Reviews.

[117]  Milan Ščasný,et al.  Brown coal and nuclear energy deployment: Effects on fuel-mix, carbon targets, and external costs in the Czech Republic up to 2050 , 2018 .

[118]  Pernille Seljom,et al.  Modelling the effects of climate change on the energy system—A case study of Norway , 2011 .

[119]  David Watts,et al.  Impacts of wind and solar spatial diversification on its market value: A case study of the Chilean electricity market , 2019, Renewable and Sustainable Energy Reviews.

[120]  Yuki Kudoh,et al.  Hydrogen in low-carbon energy systems in Japan by 2050: The uncertainties of technology development and implementation , 2018, International Journal of Hydrogen Energy.

[121]  Vahid Aryanpur,et al.  Optimal deployment of renewable electricity technologies in Iran and implications for emissions reductions , 2015 .

[122]  Gareth Harrison,et al.  Change in public attitudes towards a Cornish wind farm: Implications for planning , 2008 .

[123]  Gernot Stoeglehner,et al.  Spatiotemporal modelling for integrated spatial and energy planning , 2018 .

[124]  Peter M. Haugan,et al.  A review of modelling tools for energy and electricity systems with large shares of variable renewables , 2018, Renewable and Sustainable Energy Reviews.

[125]  Paul Deane,et al.  High performance computing for energy system optimization models: Enhancing the energy policy tool kit , 2019 .

[126]  Wenying Chen,et al.  Decarbonization of China's transportation sector: In light of national mitigation toward the Paris Agreement goals , 2018, Energy.

[127]  S. Iniyan,et al.  A review of energy models , 2006 .

[128]  Shafiullah,et al.  Role of spatial analysis technology in power system industry: An overview , 2016 .

[129]  Liming Yao,et al.  Policy implications for achieving the carbon emission reduction target by 2030 in Japan-Analysis based on a bilevel equilibrium model , 2019, Energy Policy.

[130]  Trieu Mai,et al.  The role of input assumptions and model structures in projections of variable renewable energy: A multi-model perspective of the U.S. electricity system , 2018, Energy Economics.

[131]  A. Welfle,et al.  From Paris agreement to business cases for upgraded biogas: Analysis of potential market uptake for biomethane plants in Germany using biogenic carbon capture and utilization technologies , 2019, Biomass and Bioenergy.

[132]  Bernd Resch,et al.  GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues , 2014, ISPRS Int. J. Geo Inf..

[133]  Brian Bush,et al.  Future integrated mobility-energy systems: A modeling perspective , 2020 .

[134]  Nazmiye Balta-Ozkan,et al.  Spatial development of hydrogen economy in a low-carbon UK energy system , 2013 .

[135]  Raul Miranda,et al.  Adding detailed transmission constraints to a long-term integrated assessment model – A case study for Brazil using the TIMES model , 2019, Energy.

[136]  Kalai Ramea,et al.  The cost of electrifying private transport – Evidence from an empirical consumer choice model of Ireland and Denmark , 2018, Transportation Research Part D: Transport and Environment.

[137]  Jacopo Tattini,et al.  Modelling transport modal shift in TIMES models through elasticities of substitution , 2018, Applied Energy.

[138]  E. Pyrgioti,et al.  Wide scale penetration of renewable electricity in the Greek energy system in view of the European decarbonization targets for 2050 , 2015 .

[139]  William D'haeseleer,et al.  Impact of the level of temporal and operational detail in energy-system planning models , 2016 .

[140]  G. Anandarajah,et al.  Climate change impacts on the energy system: a review of trends and gaps , 2018, Climatic Change.

[141]  M. Münster,et al.  How to maximise the value of residual biomass resources: The case of straw in Denmark , 2019, Applied Energy.

[142]  Dejene Assefa Hagos,et al.  Exploring cost-effective transitions to fossil independent transportation in the future energy system of Denmark , 2020 .

[143]  Mark Jennings,et al.  A review of urban energy system models: Approaches, challenges and opportunities , 2012 .

[144]  Nazmiye Balta-Ozkan,et al.  Spatially uneven development and low carbon transitions: Insights from urban and regional planning , 2015 .

[145]  Paulien M. Herder,et al.  A spatially explicit planning approach for power systems with a high share of renewable energy sources , 2020 .

[146]  Christopher Nichols,et al.  Multi-regional evaluation of the U.S. electricity sector under technology and policy uncertainties: Findings from MARKAL EPA9rUS modeling , 2013 .

[147]  Kristen E. Brown,et al.  Energy and emissions implications of automated vehicles in the U.S. energy system. , 2019, Transportation research. Part D, Transport and environment.

[148]  Diego Luca de Tena,et al.  Integrated modelling of variable renewable energy-based power supply in Europe , 2017 .

[149]  Christoph Kost,et al.  Renewable energy expansion and interaction in Europe: High resolution of RES potentials in energy system modeling , 2015, 2015 12th International Conference on the European Energy Market (EEM).

[150]  Gabrial Anandarajah,et al.  What are the costs of Scotland's climate and renewable policies? , 2012 .

[151]  John Bistline,et al.  The economic geography of variable renewable energy and impacts of trade formulations for renewable mandates , 2019, Renewable and Sustainable Energy Reviews.

[152]  Tomoko Hasegawa,et al.  Energy transformation cost for the Japanese mid-century strategy , 2019, Nature Communications.

[153]  Thomas Huld,et al.  Impact of different levels of geographical disaggregation of wind and PV electricity generation in large energy system models: A case study for Austria , 2017 .

[154]  Jan-Philipp Sasse,et al.  Distributional trade-offs between regionally equitable and cost-efficient allocation of renewable electricity generation , 2019, Applied Energy.

[155]  Ruben Mouangue,et al.  Analysis of a wind turbine project in the city of Bouar (Central African Republic) , 2020 .

[156]  Erik Delarue,et al.  Integrating short term variations of the power system into integrated energy system models: A methodological review , 2017 .

[157]  T. Brown,et al.  Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system , 2018, Energy.

[158]  B. Ó. Gallachóir,et al.  Improvements in the representation of behavior in integrated energy and transport models , 2018, International Journal of Sustainable Transportation.

[159]  D. Loughlin,et al.  Exploring the role of natural gas power plants with carbon capture and storage as a bridge to a low-carbon future , 2017, Clean Technologies and Environmental Policy.

[160]  Wenying Chen,et al.  Modelling building’s decarbonization with application of China TIMES model☆ , 2016 .

[161]  Wesley J. Cole,et al.  Wind and solar PV deployment after tax credits expire: A view from the standard scenarios and the annual energy outlook , 2019, The Electricity Journal.

[162]  Neil Strachan,et al.  A review of socio-technical energy transition (STET) models , 2015 .

[163]  N. Strachan,et al.  Incorporating homeowners' preferences of heating technologies in the UK TIMES model , 2018 .

[164]  M. Haller,et al.  Fluctuating renewables in a long-term climate change mitigation strategy , 2011 .

[165]  Will McDowall,et al.  Designing future hydrogen infrastructure: Insights from analysis at different spatial scales , 2013 .

[166]  T. Santos.  Regional energy security goes South: Examining energy integration in South America , 2021 .

[167]  Nan Li,et al.  Energy-water nexus in China's energy bases: From the Paris agreement to the Well Below 2 Degrees target , 2019, Energy.

[168]  Brian Ó Gallachóir,et al.  Soft-linking of a power systems model to an energy systems model , 2012 .

[169]  Gabriele Comodi,et al.  Achieving low carbon local energy communities in hot climates by exploiting networks synergies in multi energy systems , 2019 .

[170]  Birgit Fais,et al.  Spatially and Temporally Explicit Energy System Modelling to Support the Transition to a Low Carbon Energy Infrastructure – Case Study for Wind Energy in the UK , 2015 .

[171]  Ayobami Solomon Oyewo,et al.  A cost optimal resolution for Sub-Saharan Africa powered by 100% renewables in 2030 , 2018, Renewable and Sustainable Energy Reviews.

[172]  Edi Assoumou,et al.  Sub-national TIMES model for analyzing future regional use of biomass and biofuels in Sweden and France , 2013 .

[173]  Marie Münster,et al.  Balmorel open source energy system model , 2018 .

[174]  Dagnija Blumberga,et al.  Review of modelling energy transitions pathways with application to energy system flexibility , 2019, Renewable and Sustainable Energy Reviews.

[175]  Roland De Guio,et al.  Modelling and uncertainties in integrated energy planning , 2015 .

[176]  Justin Caron,et al.  The economic impacts of high wind penetration scenarios in the United States , 2018, Energy Economics.

[177]  D. Konadu,et al.  Low carbon electricity systems for Great Britain in 2050: An energy-land-water perspective , 2018, Applied Energy.

[178]  Pao-Yu Oei,et al.  Exploring Energy Pathways for the Low-Carbon Transformation in India—A Model-Based Analysis , 2018, Energies.

[179]  Marilyn A. Brown,et al.  The forest products industry at an energy/climate crossroads , 2010 .

[180]  Constantinos Taliotis,et al.  An indicative analysis of investment opportunities in the African electricity supply sector — Using TEMBA (The Electricity Model Base for Africa) , 2016 .

[181]  Maryse Labriet,et al.  Assessing Climate Impacts on the Energy Sector with TIAM-WORLD: Focus on Heating and Cooling and Hydropower Potential , 2015 .

[182]  Markus Haller,et al.  Assessment of transformation strategies for the German power sector under the uncertainty of demand development and technology availability , 2015 .

[183]  Alastair R. Buckley,et al.  A review of energy systems models in the UK: Prevalent usage and categorisation , 2016 .

[184]  T. Burandt,et al.  Decarbonizing China’s energy system – Modeling the transformation of the electricity, transportation, heat, and industrial sectors , 2019, Applied Energy.

[185]  Wenying Chen,et al.  Modelling national, provincial and city-level low-carbon energy transformation pathways , 2020 .

[186]  Olga Ivanova,et al.  Using a hybrid hard-linked model to analyze reduced climate gas emissions from transport , 2018, Energy.

[187]  Ann Mari Svensson,et al.  Market penetration analysis of hydrogen vehicles in Norwegian passenger transport towards 2050 , 2010 .

[188]  R. Castro,et al.  Forecasting and assessment of the 2030 australian electricity mix paths towards energy transition , 2020 .

[189]  Nikolaos E. Koltsaklis,et al.  A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints , 2015 .

[190]  Toshihiko Masui,et al.  GHG emission scenarios in Asia and the world: The key technologies for significant reduction , 2012 .

[191]  Khizir Mahmud,et al.  A review of computer tools for modeling electric vehicle energy requirements and their impact on power distribution networks , 2016 .

[192]  Tobias Naegler,et al.  Electrical energy storage in highly renewable European energy systems: Capacity requirements, spatial distribution, and storage dispatch , 2017 .

[193]  Vítor Leal,et al.  The relevance of the energy resource dynamics in the mid/long-term energy planning models , 2011 .

[194]  Mohammad Saeid Atabaki,et al.  Multi-objective optimization for sustainable development of the power sector: An economic, environmental, and social analysis of Iran , 2018, Energy.

[195]  Edmilson Moutinho dos Santos,et al.  Energy systems modeling: Trends in research publication , 2018, WIREs Energy and Environment.