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INTEGRATED ENERGY PLAN PRESENTATION TO NCCC 27 JULY 2012. Department of Energy. Contents. High Level Approach Objectives of the Integrated Energy Plan Demand Modeling Approach Optimisation Model Key Policy Questions High Level Work Plan. HIGH-LEVEL APPROACH. HIGH-LEVEL APPROACH.

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slide1

INTEGRATED ENERGY PLAN

PRESENTATION TO NCCC

27 JULY 2012

Department of Energy

contents
Contents
  • High Level Approach
  • Objectives of the Integrated Energy Plan
  • Demand Modeling Approach
  • Optimisation Model
  • Key Policy Questions
  • High Level Work Plan
high level approach2

MODELLING

SYSTEM

Supply

Optimisation

(Least cost, emissions and water)

Test Cases

Demand

Projections

  • HIGH-LEVEL APPROACH
  • Energy planning is an iterative process which entails many feedback loops between the various stages
  • 1) A mechanism of dealing with quantitative (data-driven) as well as qualitative (expert judgement) analysis
  • 2) A parallel consideration of each of the following elements:
  • Existing and future energy technologies and energy carriers
  • Existing and proposed policies within government which have a high-impact on the energy sector
  • Key Indicators outside of control which characterise current and future uncertainties
  • Conflicting criteria upon which different options/alternatives should be evaluated
HIGH-LEVEL APPROACH

MODEL OUTPUT

(ENERGY RESOURCES AND TECHNOLOGY OPTIONS)

EVALUATE MODEL OUTPUT AND POLICY PROPOSALS

(Multi-Criteria Decision Analysis)

RECOMMENDATIONS

RES

(Technologies,

Energy Carriers,

Energy Services)

Base Case

Existing High-Impact Policies and Legislation

Proposed/

New

High-Impact Policies and Policy Options

Key Policy Questions

Key Indicators

Plausible Futures to deal with Key Uncertainties

Key Criteria for Evaluating Alternate Options

identifying the iep objectives
Identifying the IEP objectives

These are further broken down into criteria.

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The criteria are:

Organising the criteria and objectives in this way facilitates scoring the options on the criteria and examining the overall results at the level of the objectives.

slide8

Energy commodities and other materials constrained by availability of local natural resources and international markets

Technology costs, life spans, efficiencies, discount rate and emission factors

Demand for

Energy services

driven by socio-economic needs and desires

Heat

Coal

Hot water

Energy system:

Technology value chains which convert energy commodities into useful energy services

Crude oil

Light

Natural gas

Mechanical work

Solar energy

Refrigeration

Uranium

Transport

Environmental constraints

Wind

Energy systems and their context

slide10

IEP

Energy carriers

Electricity demand

Energy Services

Resource extraction/imports

Refining

Industrial processes

Electricity Generation

Demand technologies

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Modelling tools

  • There is more value derived from modelling processes than the final results as the process increases our understanding of energy systems
  • Energy demand models
    • Macro-economic drivers as input
    • Determine demand for energy services (heating, lighting, transport…)
  • Energy supply optimisation model
    • Macro-economic drivers as input
    • Use demand derived from demand models
    • Minimises the cost of the energy system for demand based on constraints
energy demand in south africa
Energy Demand in South Africa

This what we collect

This what we need for the IEP

slide15

Total Energy Services

(303805 TJ)

Total Energy Carriers

(303805 TJ)

slide22

Components of the modelling system

User interfaces/template

Automated spread sheets for reporting

Data capture and management

Model execution

Results analysis

Optimisation model data and demands

Linear program

(OSeMOSYS)

Demand models

Results tables

Demand model data

Linear program solver

(GLPK)

Database

Model data tables

Data collection (CSIR-Promethium Carbon, Eskom, DOE)

Manual processes

Automated processes

Demand models

(DOE, Eskom)

Data tools and

integration (DOE)

OSeMOSYS enhancements (CSIR)

Third party software

slide27

Base case

Overall modelling process

Optimised energy system 3

Optimised energy system 2

Test case 1

Forecast based on trends

Implemented policy

Optimised energy system 0

Achieves desired outcomes for base case

Optimised energy system 1

Achieves desired outcomes for test case 1

Reference Energy System

Reference Energy System with modified parameters

Test case 3

Plausible future

Policy

options

Modelling system

Test case 2

Plausible future

Plausible futures

Recommendations

The test case which produces the least cost energy system while achieving the desired outcomes

suggests the most effective policies

slide32

Non-Quantitative Analysis of

Policy Options

Policy options not necessarily informed by outputs from energy models

(Specific modelling requirements may be considered for future iterations of IEP)

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