Using TIMES models to inform power sector strategy Steve Pye [s.pye@ucl.ac.uk] IEA Energy Training Week April 12, 2013
Case Study: Developing an integrated energy model for Pakistan Background Project overview Model development Policy analysis Summary comments
Power sector in Pakistan Hydro IPPs 1% Nuclear Public 3% Hydro IPPs 0% Nuclear Public 3% Hydro Public 28% Thermal Public 30% Hydro Public 32% Thermal Public 22% 2010/11 Capacity: 22.6 GW Thermal IPPs 38% 2010/11 Gen: 98.9 TWh Thermal IPPs 43% Plant type Ownership Capacity (MW) Generation (GWh) Thermal Public 6706 21938 IPPs 8587 42433 Hydro Public 6444 31194 IPPs 111 309 Nuclear Public 787 3033
Importance of sustainable planning capability for Pakistan Widening supply gap, leading to extensive load shedding Rapid demand growth Limited new capacity build System losses (24%) and end use sector inefficiency Lack of revenue for investment / operation (leading to circular debt) Falling indigenous oil / gas resources Hydro seasonal variability Limited focus on medium to longer term planning necessary for large scale investment
Widening demand-supply gap Load shedding critical problem, with economic, social and political consequences 8-10 hours in urban areas and 18-20 hours in rural areas
Key policy decisions for power sector in longer term Primary Energy Supply Conversion Technologies End-use Sectors Energy Service Demand Exploitation of Thar coal? Imports of fuels (LNG, pipeline) and electricity? Strong nuclear base? Coal gen., based on Thar? Further hydro exploitation? Demand for electricity? Energy efficiency potential? Strength of demand drivers? Non-hydro renewables? Grid system options? Policy issues (e.g. energy security, environmental sustainability) and wider sector implications
Example: indigenous exploitation of coal Thar coal provides one of the largest deposits of lignite in the world (175 billion tonnes) Key debate over exploitation Cost vs. imports Technology to use e.g. gasification Environmental concerns (pollution, water usage) Grid expansion costs vs. transport How does this option rank against many others in context of future demand, and wider system?
Case Study: Developing an integrated energy model Pak-IEM Background Project overview Model development Policy analysis Summary comments
Project objective Develop a sustainable planning capability by use of a integrated energy system model Enable a national team of experts to assess the impacts of various strategies for meeting future energy requirements in an optimal manner
Why TIMES? Encompasses an entire energy system from resource extraction through to end-use demands Employs least-cost optimization Identifies the most cost-effective pattern of resource use and technology deployment over time Provides a framework for the evaluation of mid-to-longterm policies and programs that can impact the evolution of the energy system Quantifies the costs and technology choices that result from imposition of the policies and programmes Fosters stakeholder buy-in and consensus building
Institutional organisation and capacity building Asian Development Bank Pakistan Planning Commission Define policy studies, integrate into the planning process, and ensure ongoing funding Advisory Committee Ministries of Petroleum and Natural Resources Water and Power Planning and Development Environment, Transport and Communications Pakistan Atomic Energy Commission Regulatory Agencies, Development Institutes, and Others IRG Consultant Team International Experts (IRG) National Experts (ME Consult) Planning Team Energy Wing staff who understand the model, and coordinate use with the Host Institutions Advisory Task Force Experts from the Ministries and Industries to provide technical support Host Institutions Modeling experts who maintain the PIEM database and perform policy analysis University Research Centers Professors and graduate students who use and improve the model
Planning team organisation 7 key energy sector institutions and 3 universities Organized into sector focused subgroups for each of 7 main sectors Organization Pakistan Institute of Development Economics - PIDE, QAU, Islamabad Energy Wing,Planning &Commission, Government of Pakistan Global Change Impact Studies Center - GCISC Hydrocarbon Development Institute of Pakistan - HDIP National Transport Research Center - NTRC NED University of Engineering and Technology Pakistan Atomic Energy Commission - PAEC Pakistan Electric &Power Company - PEPCO Pakistan Institute of Engineering and Applied Sciences - PIEAS University of Engineering & Technology, Lahore - UETL University of Engineering & Technology, Taxila - UETT Demand Forecasting Supply & Resources Sectors Demand Forecasting, Industry Supply & Resources, Transport & Agricultural Electricity, Residential & Commercial Overall In charge Emissions Transport & Agricultural Emissions Supply & Resources, Emissions Transport & Agriculture Industry Residential & Commercial Demand & Forecasting, Industry Electricity Transport & Agricultural, Emissions Emissions Electricity Industry Residential & Commercial Residential & Commercial
Project tasks (across 30 months) Data gathering Task 1 Develop Data for Pakistan s Energy Sector Task 2 Identify Lessons Learned from Similar Modeling Activities Task 3 Recommend a Framework to Institutionalize the Modeling Capability Institutional framework Task 4 Establish the Modeling Framework, Objectives and Requirements Model design / construction Task 5 Procure Model Software, Support Licenses and Training Task 6 Construct the Model and Determine Key Outputs/Indicators Task 7 Define and Analyze Alternative Policy Scenarios Task 8 Provide Training on Database Development and Model Applications Task 9 Capacity Building on Use and Updating of the Model Policy analysis Workshops / Training
Case Study: Developing an integrated energy model Pak-IEM Background Project overview Model development Policy analysis Summary comments
Pak-IEM structure Energy Balance Model Horizon & System Settings Demand Projections Resource Supply Pak-IEM Future Technologies Calibration & Fuel Shares Supply Sector Base- Year Templates Demand Sector Base-Year Templates Agriculture Upstream Commercial Residential Power Industry Transport
Power sector structure
Power sector inputs All existing power plants in the PEPCO / KESC system characterized individually Hydro plants operating with seasonal availability taken into account Existing plants forced to operate to at least the level observed in 2006-07 for remaining lifetime Committed plants are included in the model Electricity supply responding to temporal demands based on a 12- period day/season resolution of the load curve Load shedding reflected as an unmet demand increasing to the 2010 level and decreasing to zero in 2015 Transmission & distribution losses (24% in 2007), with 6% assigned to transmission Full set of new technology options including renewables Limits on the rate at which new power plants can be built
Load-MW Load-MW PEPCO 24 hour load data (Monthly averages) 24 Hour Load Profile-Summer (2006-07) 16000 Night Day Shoulder Peak Sh 14000 May - WD June - WD 12000 July - WD August - WD 10000 May - WE June - WE 8000 July - WE August - WE 6000 24 Hour Load Profile-Winter (2006-07) 4000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time 16000 Night Day Sh Peak Shoulder 14000 November - WD December - WD 12000 January - WD February - WD March - WD 10000 November - WE December - WE January - WE 8000 February - WE March - WE 6000 4000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time
Modelling challenges Data availability (although power sector least problematic) Characterising near term issues such as load shedding, circular debt, fuel price volatility etc. Issue of lumpy investment for large-scale infrastructure Capturing uncertainty in deterministic model Engaging and bringing experts on board
GWh GWh Issue of load shedding 14000 12000 10000 Demand System Significant problem of supply shortfall in specific countries 8000 6000 4000 Optimisation model will ignore the problem of deficit as it will supply what is demanded 2000 140000 0 Jul 06 Oct 06 Jan 07 Apr 07 Jul 07 Oct 07 Jan 08 Apr 08 Jul 08 Oct 08 Jan 09 Apr 09 130000 Deficit Actual supply 120000 Force problem to be recognised by introducing unmet demand which adds high costs to the model Model saves costs by building new capacity, resolving the deficit problem 110000 100000 90000 80000 70000 2007 2008 2009 2010 2011 2012 2013 2014 2015
Case Study: Developing an integrated energy model Pak-IEM Background Project overview Model development Policy analysis Summary comments
Scenarios Reference (BAU) Storyline 1 Pursue Best Practices Electricity T&D efficiency improvements Increased potential for Renewable Energy (wind and solar thermal) Higher levels of Energy Efficient device deployment permitted in the demand sectors Expanded domestic Oil & Gas reserves Storyline 2 Challenges Persist Delay of Hydro and Nuclear investments by 5 years and No Thar Coal No Imported Coal port facilities and power plants No Imported Natural gas
Mtoe Reference case: Primary energy supply Growing contribution from coal and hydro (power sector) and oil (transport) 250 200 150 Per Capita Primary Commercial Energy Use (TOE/capita) 2007 2030 Pakistan 0.42 0.77 World average 1.82 Primary Energy Supply Renewables (excl. hydro) Oil & Products Nuclear 100 50 Natural Gas Hydroelectric COAL 0 2007 2010 2015 2020 2025 2030 Reference
Reference case: Gas supply Big shift in gas supply and share of imports
Reference case: Power generation Strong growth in power generation, w/ increasing contributions from coal and hydro
GW Reference case: New power generation capacity Large-scale investment requirement to meet growing demand Power Plant Annual New Capacity Additions 6.0 5.0 4.0 Total Installed Capacity by 2030 Oil & Gas Hydro Nuclear Coal 82 GW 6 GW 28 GW 5 GW 39GW Requiring $17Billion Renewables (non-hydro) Oil-fired Power Plants Nuclear Power Plants 3.0 Renewables 2.9 GW Hydro Plants 2.0 Gas-fired Power Plants Dual-fired Power Plants 1.0 Diesel generators Coal-fired Power Plants 0.0 2010 2011 2012 2013 2014 2015 2020 2025 2030 Reference
Storyline 1 Best practice: Costs Incremental improvements result in increasingly low system costs
Storyline 1 Best practice: Annual expenditure Increased investment in energy efficiency devices, leading to lower power sector investment
Storyline 1 Best practice: Generation Smaller system due to efficiency measures, with less coal / nuclear in the long term
Storyline 1 Best practice: CO2 taxes Additional costs of CO2 tax can be significantly offset through best practice
Storyline 2 Challenges: Costs Key challenges in system can be offset by best practice measures
Storyline 2 Challenges: Generation Stronger role for nuclear in absence of domestic coal resource
Storyline 2 Challenges: Final energy Greater role for gas / oil compared to electricity; increased efficiency through best practice
Case Study: Developing an integrated energy model Pak-IEM Background Project overview Model development Policy analysis Summary comments
Key insights Whatever the technology choices, long term investment requirements are significant These will be even higher if near term challenges persist.but can also be offset by best practice approaches There are some key resource supply issues that will have large consequences across the system (gas imports, coal exploitation) Planning needs to start now, based on integrated view of the system to inform strategy TIMES model is one of the tools now available to support process
Critical success factors Engagement of the Planning Team Dedicated staff in the Energy Wing Strong contributions from other institutions, and independent use Involvement of the key Ministries, agencies and private sector for improved data development Wide dissemination of model capabilities and results But could be improved through. Integration of Pak-IEM into the decision making process Regular (bi-annual) analysis in support of the publication the Pakistan Energy Sector Development and Investment Strategy
Challenges of gaining traction with stakeholders Long term nature of analysis Switching to an integrated framework Large amounts of inputs (consensus) / outputs (dissemination) Supply side focused Deterministic approach in an uncertain world
Extra slides: Additional Pak-IEM analysis
Reducing gas supply to fertilizer sector
Increasing gas supply to power sector