Integrated Resource Planning: An overview Mark Howells & Bruno Merven Energy Research Centre Energy Research Centre University of Cape Town.

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Presentation transcript:

Integrated Resource Planning: An overview Mark Howells & Bruno Merven Energy Research Centre Energy Research Centre University of Cape Town

Outline Introduction Aims of resource planning The National Integrated Resource Plan NIRP outputs NIRP methodology Future planning

Introduction Why electricity as a source of energy? Electricity - a driver of our economy The Electricity Supply Industry (ESI) is very capital intensive – economies of scale Electricity is hard to store

Aims of Resource Planning Meet electricity demand reliably at the cheapest cost Be consistent with environmental, social and economic policies Meeting increasing demand: Expanding generating capacity Expanding generating capacity Reducing load via demand side management Reducing load via demand side management

The NIRP National Energy Regulator initiative the driven by the Energy Policy White Paper for SA NIRP 1 in March 2002 NIRP 2 in September 2004 Advisory board: NER, DME, ESKOM, ERC, IPP, … Advisory board: NER, DME, ESKOM, ERC, IPP, … Project team: NER, ESKOM, ERC Project team: NER, ESKOM, ERC

NIRP 2 outputs: 1. Capacity Plans

Capacity Plans

NIRP 2 Outputs: 2. Sensitivity to possible scenarios

Cost and Reliability

Methodology 1.Demand and projections 2.Current generation capacity 3.New generation capacity options 4.Demand Side Management options 5.Identify constraints – define scenarios 6.Include all this into the computer model 7.Run optimization Primary energy e.g. Coal Electricity generation Grid Demand process e.g. Electric Heater Final Energy e.g. Heat The Energy System

1. Establish current demand and projections

2. Establish current generation capacity 3. Identify suitable new generation capacity options Be technologically feasible Be economically viable Be socially, politically and environmentally acceptable Have suitable production pattern Have site availability – close to demand Under some level of suitable control

3. Identify Demand Side Management options

4. Program the Computer Model Coal Existing Capacity Nuclear PP Wind PP Transmission and Distribution New Capacity Options Coal PP Normal Demand Technology Efficient Demand Technology Useful energy per sector Heat Light … Coal Gas Nuclear … Gas PP Primary Energy Specified: Capital costs per MW Capital costs per MW Fuel costs (as specified by mining/importing) Fuel costs (as specified by mining/importing) Operation costs per MWh Operation costs per MWh Lifetime (years) Lifetime (years) Operating conditions: Peaking, base load Operating conditions: Peaking, base load Constraints: Technical e.g. Capacity, availability Constraints: Technical e.g. Capacity, availability Constraints: Policy e.g. share of renewables, Emissions Constraints: Policy e.g. share of renewables, Emissions

Model outputs after optimization Capacity and activity of selected processes (including timing + choice of investments) i.e. The Plan Total Costs Marginal cost of electricity Total emissions

Weaknesses of this approach Deterministic approach, uncertainty: handled in reserve margin handled in reserve margin discount rates and scenario based constraints discount rates and scenario based constraints Suitable for finding a robust plan but not necessarily a flexible plan Technology diversity must be forced onto the system as a constraint Bottom up approaches tend to be bulky Difficult to asses impact of plan on overall economy

Possible alleys to be explored in the future To account for flexibility: Decision analysis type approaches Decision analysis type approaches Stochastic programming Stochastic programming Link to general equilibrium models