Presentation LEAP

8/4/2019 Presentation LEAP

1/18


2/18

Introduction to LEAP

Developed at the StockholmEnvironment Institute

Has been adopted by hundreds oforaganisations in more than 150

countries worldwide. Widely-used software tool for energy

policy analysis and climate changemitigation assessment

LEAP has had a significant impact inshaping energy and environmentalpolices worldwide.


3/18

What Can be Done WithLEAP Tool for Strategic Integrated Energy-

Environment Scenario Studies:

Energy Outlooks (forecasting)

Integrated Resource Planning Greenhouse gas mitigation analysis

Energy balances and environmental

inventories


4/18

Scenario Analysis

LEAP is designed around the conceptof longrange scenario analysis.

Scenarios are selfconsistent

storylines of how an energy systemmight evolve over time.

Using LEAP, policy analysts cancreate and then evaluate alternative

scenarios by comparing their energyrequirements, their social costs andbenefits and their environmental

impacts.


5/18

Forecasting & Backcasting

?

?

Where is society going?forecast

backcast

Where do we want to go?

How do we get there?


6/18

Integrated Planning

LEAP is an integrated modeling tool thatcan be used to

track energy consumption, production and

resource extraction in all sectors of aneconomy.

account for both energy sector andnonenergy sector greenhouse gas (GHG)

emission sources and sinks. analyze emissions of local and regional air

pollutants, making it wellsuited to studies ofthe climate cobenefits of local air pollution

reduction.


7/18

LEAP Modeling Capabilities Energy Demand

Hierarchical accounting of energy demand (activity levels x energy intensities).

Optional modeling of stock turnover.

Energy Conversion

Simulation of any energy conversion sector (electric generation, transmission anddistribution, CHP, oil refining, charcoal making, coal mining, oil extraction, ethanolproduction, etc.)

Electric system dispatch based on electric load-duration curves.

Modeling of capacity expansion.

Energy Resources:

Tracks requirements, production, sufficiency, imports and exports.

Optional land-area based accounting for biomass and renewable resources.

Costs:

All system costs: capital, O&M, fuel, costs of saving energy, environmentalexternalities.

Environment

All emissions and direct impacts of energy system.

Non-energy sector sources and sinks.


8/18

LEAP Modeling

Methodologies LEAP provides a range of accountingand simulation

methodologies that are powerful enough for modeling electricsector generation and capacity expansion planning, but whichare also sufficiently flexible and transparent to allow LEAP toeasily incorporate data and results from other morespecialized models.

LEAPs modeling capabilities operate at two basic conceptual

levels. At one level, LEAP's builtin calculations handle the energy,

emissions and costbenefit accounting calculations.

At the second level, users enter spreadsheetlike expressions thatcan be used to specify timevarying data or to create a widevariety of sophisticated multivariable models, thus enablingeconometricand simulationapproaches to be embedded within

LEAPs overall accounting framework. LEAP does not currently support optimization modeling (eg,

finding the model with the least cost).

LEAP is intended as a medium to longterm modeling tool.Most of its calculations occur on an annual timestep.

Studies typically include both a historical period known as theCurrent Accounts, as well as multiple forward lookingscenarios. T icall most studies use a forecast eriod of


9/18

Decision Support System

LEAP is more just a model: it is a full decisionsupport system (DSS) providing extensive datamanagement and reporting capabilities.

It can serve as both a historical databaseshowing the evolution of an energy system and a

forwardlooking scenario

based tool that can

create forecasts of how a system might evolve orbackcasts that examine how a society might tryto meet its development goals in the energysector.

LEAP provides powerful data management toolsincluding full importing and exporting to MicrosoftExcel, Word and PowerPoint, and a

rich graphical environment for visualizing dataand results.


10/18

Application of LEAP anExampleAim:

To build future scenarios using LEAP in order to predictthe

future energy demand of the agricultural sector ofPunjab,

taking the base year as 2000 and extrapolating till 2030.(ENERGY DEMAND MODEL)

Method:

Step I: Collect data on past trendsrelated to the

energy requirements associated with field activitiesand agricultural inputs in Punjab.

Step II: Give the past trends as input to LEAP

Step III: Build scenarios in LEAP which utilize thedata

on past trends and extrapolate them to give future


11/18

Scenarios

Three Scenarios created:

1) Reference or Business-as-usual Scenario:

Continuation of past trends, no surprises or major shift.

1%/year growth in agricultural production, on an average.

2) Moderate Improvement Scenario:

Moderate improvement in agriculture production.

2%/year growth in agricultural production.

3) Accelerated Growth Scenario: Rapid growth in both food and non-food crop production.

3%/year growth in agricultural production, most crops.

Emphasis on high-input, conventional farming techniques.


12/18

Simplified Representation

Inputs Outputs

LEAP

Past trends and datapertaining to differentvariables such ascultivated area, crop

yield, share of fuelconsumption inagricultural sector

Expressions to specifyhow data varies with time,i.e.,Growth Rate of thevariables pertaining todifferent scenarios

Future trendspertaining to

different scenarios

The next few slides show examples of data that were extrapolated using

LEAP under the three different scenarios.


13/18

Reference Data (input):

Major crops cultivated area in year

2000


14/18

Results given by LEAP (output):

Comparison of cultivated area by different scenarios developed by LEAP


15/18

Percent share of fuel consumption in agriculture sector

Reference Data (input):


16/18

Results given by LEAP (output):

Comparison of different scenarios (Fuel consumption)


17/18

Purpose of Modeling,Conclusions Drawn

All scenarios were compared to Base (BAU) scenario andtheir

potentials for increasing agricultural production wereexamined.

For example, Cultivated area in base (BAU) scenario was found to be14

thousand hectares in 2030, while in moderate improvementscenario and accelerated growth scenario it was about 18 and 22thousand hectares in 2030 respectively.

Fuel consumption in the agriculture sector in BAU scenario wasabout 2100 thousand tonnes in 2030, while in moderate

improvement and accelerated growth scenarios it was found to beabout 2,600 and 3,200 thousand tonnes.

These predictions show how fast energy needs mightgrow under conditions of both limited and rapid growthin Punjabs agricultural production using a LEAP model.

The predictions help policy-makers to understand theenergy demand of the agricultural sector of Punjab so


18/18

Documents

Presentation LEAP