Long-term energy system planning considering short-term operational constraints

Abstract The intermittent nature of renewable energy sources (RESs) brings formidable challenges in the operation of power system. Long-term energy system planning models overlook the impact of renewable intermittency on system operations due to the computational burden associated with large model size and long planning horizon. Hence, strategies such as soft-linking multiple models are developed, but they do not assure the convergence and optimality of such incoherent modeling framework. In this context, this paper utilizes unit commitment (UC) extension of TIMES modeling framework to integrate operational constraints directly in a long-term power system planning model. This strategy eliminates the complexity of handling multiple models. Results indicate that incorporation of UC constraints improve the performance of conventional generators in terms of increased capacity utilization, and help to assess flexibility requirements with high RESs. Energy storage provides the balancing and flexibility needs with stringent generator constraints. Sensitivity analysis shows that improved flexibility of thermal generators enables increased renewable penetrations.

[1]  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.

[2]  Christian von Hirschhausen,et al.  Designing a Model for the Global Energy System—GENeSYS-MOD: An Application of the Open-Source Energy Modeling System (OSeMOSYS) , 2017 .

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

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

[5]  Marcin Jaskólski,et al.  Modelling long-term technological transition of Polish power system using MARKAL: Emission trade impact , 2016 .

[6]  C. J. M. Emmott,et al.  India's CO2 emissions pathways to 2050: Energy system, economic and fossil fuel impacts with and without carbon permit trading , 2014 .

[7]  R. Madlener,et al.  CO2 Emission Reduction Potential Assessment Using Renewable Energy in India , 2016 .

[8]  Machteld van den Broek,et al.  Operational flexibility and economics of power plants in future low-carbon power systems , 2015 .

[9]  Neil Strachan,et al.  Characterising the Evolution of Energy System Models Using Model Archaeology , 2014, Environmental Modeling & Assessment.

[10]  M. Howells,et al.  Long-term optimisation model of the Tunisian power system , 2017 .

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

[12]  Rodrigo Palma-Behnke,et al.  A column generation approach for solving generation expansion planning problems with high renewable energy penetration , 2016 .

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

[14]  Thomas Ackermann,et al.  Wind Power in Power Systems , 2005 .

[15]  Sanjay Kumar,et al.  Present and Future Energy Scenario in India , 2014 .

[16]  John R. Birge,et al.  A stochastic model for the unit commitment problem , 1996 .

[17]  Maryse Labriet,et al.  ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure , 2008, Comput. Manag. Sci..

[18]  M. Milligan,et al.  Assessing Wind Integration Costs with Dispatch Models: A Case Study of PacifiCorp; Preprint , 2003 .

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

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

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

[22]  Nate Blair,et al.  Regional Energy Deployment System (ReEDS) Model Documentation: Version 2016 , 2016 .

[23]  N. K. Bansal,et al.  Allocation of energy resources for power generation in India: Business as usual and energy efficiency , 2010 .

[24]  Wolf Fichtner,et al.  On the economic potential for electric load management in the German residential heating sector : An optimising energy system model approach , 2014 .

[25]  M. Kirkengen,et al.  The role of the discount rates in energy systems optimisation models , 2016 .

[26]  Muhammad Aslam Uqaili,et al.  Decarbonization of Electricity Sector of Pakistan—An Application of Times Energy Model , 2017 .

[27]  Ramachandran Kannan,et al.  The development and application of a temporal MARKAL energy system model using flexible time slicing , 2011 .

[28]  David W. Coit,et al.  Stochastic optimization for electric power generation expansion planning with discrete climate change scenarios , 2016 .

[29]  Jyotirmay Mathur,et al.  Implications of short-term renewable energy resource intermittency in long-term power system planning , 2018, Energy Strategy Reviews.

[30]  Pavlos S. Georgilakis,et al.  Technical challenges associated with the integration of wind power into power systems , 2008 .

[31]  Neil Strachan,et al.  Scenarios and Sensitivities on Long-term UK Carbon Reductions using the UK MARKAL and MARKAL-Macro Energy System Models , 2008 .

[32]  Bryan Palmintier,et al.  Impact of unit commitment constraints on generation expansion planning with renewables , 2011, 2011 IEEE Power and Energy Society General Meeting.

[33]  Hossein Seifi,et al.  Electric Power System Planning: Issues, Algorithms and Solutions , 2011 .

[34]  H. Rogner,et al.  Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland , 2014 .

[35]  Gabrial Anandarajah,et al.  India’s CO2 emission pathways to 2050: What role can renewables play? , 2014 .

[36]  Manuel Welsch,et al.  Assessing the technical wind energy potential in Africa a GIS-based approach , 2015 .

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

[38]  David L. McCollum,et al.  Deep greenhouse gas reduction scenarios for California – Strategic implications from the CA-TIMES energy-economic systems model , 2012 .

[39]  Neil Strachan,et al.  Indirect CO2 Emission Implications of Energy System Pathways: Linking IO and TIMES Models for the UK. , 2015, Environmental science & technology.

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

[41]  S. D. Pohekar,et al.  Electricity demand and supply scenarios for Maharashtra (India) for 2030: An application of long range energy alternatives planning , 2014 .