{"query_echo":{"q":"","filters":{"analysis_type":["technical guide"]},"warnings":[]},"total":{"value":160,"relation":"eq"},"page":7,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=technical+guide&page=7","next":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=technical+guide&page=8","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"sei-000281","url":"https://climateinsightsdirectory.org/document/sei-000281","title":"Tagging Branches","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Tagging_Branches/Tagging_Branches.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document explains the use of tags in LEAP as a flexible alternative or supplement to the software's hierarchical tree structure, particularly for classifying technologies that fit multiple categories. It details how to assign, paint, and manage tags to filter results in charts and tables, and describes the specific toolbar functions for adding, deleting, and color-coding tags.","ai_generated":true,"unit":"sei-000281#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Tags in LEAP allow users to classify data that belongs to multiple categories, which is particularly useful for Transformation modules where sub-folders are not permitted and technologies must be entered as a single list.","ai_generated":true,"unit":"sei-000281#insight-1","date_modified":"2026-10-23"},{"text":"Tags can be used as an additional dimension in Results View charts and tables to filter and organize results, provided that each branch is tagged with only one tag from any single tag group.","ai_generated":true,"unit":"sei-000281#insight-2","date_modified":"2026-10-23"},{"text":"The software provides several tools for tag management, including a tag toolbar for typing labels, a 'Tag Painter' for copying tags between branches, and a 'Manage Tags' screen (Alt+T) for creating color-coded groups.","ai_generated":true,"unit":"sei-000281#insight-3","date_modified":"2026-10-23"},{"text":"Tag settings allow users to determine if new tags should be added to or replace existing tags, and whether tags should be applied only to a specific branch or to that branch and all its children.","ai_generated":true,"unit":"sei-000281#insight-4","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000283","url":"https://climateinsightsdirectory.org/document/sei-000283","title":"Data Pages","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/Help24/TED/TED_Data.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes the interface and data entry fields of the TED data pages, which allow users to record technical specifications, energy demand, conversion efficiency, pollution control, costs, and environmental loadings for various technologies.","ai_generated":true,"unit":"sei-000283#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The TED data page interface is organized into resizable panes, featuring a top section for data editing and a bottom section split between technology-specific notes and bibliographic references.","ai_generated":true,"unit":"sei-000283#insight-1","date_modified":"2026-10-23"},{"text":"The 'General' tab serves as the primary configuration page where users define the technology's applicability by country or region, its development status, lifetime, construction time, and which subsequent data tabs will be displayed.","ai_generated":true,"unit":"sei-000283#insight-2","date_modified":"2026-10-23"},{"text":"The system includes specialized tabs for different technology types: 'Energy Demand' for fuel consumption and intensity; 'Energy Conversion' for efficiency and capacity of conversion plants; and 'Pollution Control Data' for emission reduction percentages and associated energy efficiency losses.","ai_generated":true,"unit":"sei-000283#insight-3","date_modified":"2026-10-23"},{"text":"The 'Costs' tab allows for the entry of operating, maintenance, and capital costs, with the option to distinguish between base and total capital costs (including interest).","ai_generated":true,"unit":"sei-000283#insight-4","date_modified":"2026-10-23"},{"text":"The 'Environment' tab tracks environmental loadings, such as CO2 emissions per unit of fuel, and allows users to link up to three pollution control technologies to energy technologies.","ai_generated":true,"unit":"sei-000283#insight-5","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide emissions"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000299","url":"https://climateinsightsdirectory.org/document/sei-000299","title":"Annual Emission Constraints","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Transformation/Emission_Constraint.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes the functionality of annual emission constraints in LEAP, noting they are used to set maximum annual pollutant levels across an energy system during least cost optimization of a Transformation module.","ai_generated":true,"unit":"sei-000299#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Annual emission constraints in LEAP are only applicable and relevant when running scenarios that utilize least cost optimization of a Transformation module; they are ignored in scenarios calculated without these optimization calculations.","ai_generated":true,"unit":"sei-000299#insight-1","date_modified":"2026-10-23"},{"text":"The purpose of emission constraints is to define a maximum annual emission level for a specific pollutant, which LEAP then uses to determine the least cost configuration of a Transformation module to keep total system-wide emissions below that limit.","ai_generated":true,"unit":"sei-000299#insight-2","date_modified":"2026-10-23"},{"text":"While pollutant emissions can originate from Demand sectors, Transformation modules, and Non energy sectors, LEAP's optimization calculations typically only operate on a single Transformation module, such as the electric generation module.","ai_generated":true,"unit":"sei-000299#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy modeling"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000310","url":"https://climateinsightsdirectory.org/document/sei-000310","title":"Using IBC","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/Help24/IBC/Using_IBC.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document outlines the requirements for using the Integrated Benefit Calculator (IBC) with LEAP, specifying that it supports 161 countries and requires national or multi-national scale areas. It details the necessary pollutant accounting—including CO2, methane, and various short-lived climate pollutants—and the specific data structure (Tree branches) required for the tool to function. Once configured, IBC allows users to analyze premature mortality, crop losses, and temperature changes based on geographic sources and pollutant contributions.","ai_generated":true,"unit":"sei-000310#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"IBC is compatible only with national-scale or multi-national scale LEAP areas and has been calibrated for 161 countries.","ai_generated":true,"unit":"sei-000310#insight-1","date_modified":"2026-10-23"},{"text":"When using PM Scaling, the LEAP model must provide a comprehensive accounting of all major long- and short-lived climate pollutants (SLCPs) and local air pollutants, including CO2, methane (CH4), black carbon, organic carbon, PM2.5, non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NOx), sulfur dioxide (SO2), and ammonia (NH3), covering both energy and non-energy sectors.","ai_generated":true,"unit":"sei-000310#insight-2","date_modified":"2026-10-23"},{"text":"The tool requires a specific data structure under the Key Assumptions and Indicators branches; specifically, folders for Demographics, Economics, Disease Rates, Crop Production, and Transport must exist, or the IBC will fail to run.","ai_generated":true,"unit":"sei-000310#insight-3","date_modified":"2026-10-23"},{"text":"If Base Year Particulate Matter Scaling is enabled, the user must set the Base Year to 2010 and the First Scenario Year to 2011, while the End Year must be 2020 or later.","ai_generated":true,"unit":"sei-000310#insight-4","date_modified":"2026-10-23"},{"text":"Successful IBC implementation enables the analysis of results such as premature mortality, crop losses, and temperature change, which can be disaggregated by geographic source, pollutant contribution, or age group.","ai_generated":true,"unit":"sei-000310#insight-5","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide","methane","particulates","Green ammonia","climate impact"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000327","url":"https://climateinsightsdirectory.org/document/sei-000327","title":"Demand Costs","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Demand/Demand_Cost_Analysis.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document details four methods for entering non-fuel costs (capital, O&M, and administrative) in LEAP: Costs Per Activity, Costs Per Device Sold, Total Costs, and Cost of Saved Energy (CSE). It provides the specific calculation logic for each method and advises users to enter costs only for branches where activities or energy intensities deviate from the baseline for comparative analysis.","ai_generated":true,"unit":"sei-000327#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP offers four distinct methods for specifying non-fuel demand costs: Costs Per Activity, Costs Per Device Sold, Total Costs, and Cost of Saved Energy (CSE).","ai_generated":true,"unit":"sei-000327#insight-1","date_modified":"2026-10-23"},{"text":"The 'Costs Per Activity' method calculates costs by multiplying the cost per activity by the activity levels for a given year.","ai_generated":true,"unit":"sei-000327#insight-2","date_modified":"2026-10-23"},{"text":"The 'Costs Per Device Sold' method is available for technologies using Stock Analysis or Transport Analysis and is considered more accurate for tracking new and replacement devices, though it requires more data.","ai_generated":true,"unit":"sei-000327#insight-3","date_modified":"2026-10-23"},{"text":"The 'Total Costs' method allows for the entry of a total annual cost at a demand branch, which is useful for administrative or overall program costs; users can employ the AnnualizedCost function to levelize capital costs.","ai_generated":true,"unit":"sei-000327#insight-4","date_modified":"2026-10-23"},{"text":"The 'Cost of Saved Energy' (CSE) method calculates the incremental cost of energy efficiency investments relative to a baseline scenario or Current Accounts, enabling a direct comparison between demand-side efficiency and conventional energy supply investments.","ai_generated":true,"unit":"sei-000327#insight-5","date_modified":"2026-10-23"}],"climate_tags":["energy efficiency","demand-side management"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000335","url":"https://climateinsightsdirectory.org/document/sei-000335","title":"Stock and Stock Share","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Demand/Stocks.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes the functionality of the Stock variable in LEAP, which is used to model how new energy efficiency or emissions standards for new technology sales gradually improve the average values of a total device stock as older units are replaced. It details the two types of stock-turnover analysis—Transport Analysis for vehicles and standard Stock Analysis for other devices—and explains the choice between top-down and bottom-up data entry. The guide specifies that the Stock variable initializes calculations and works with the Stock Vintage Profile and First Sales Year to determine how stocks evolve through sales, retirement, and forced scrappage.","ai_generated":true,"unit":"sei-000335#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Stock-turnover analysis allows users to model the gradual improvement of average values across a total stock of devices as new technologies with higher energy efficiency or emissions standards replace older ones.","ai_generated":true,"unit":"sei-000335#insight-1","date_modified":"2026-10-23"},{"text":"LEAP supports two methods for specifying stock and sales data: a bottom-up approach at technology branches or a top-down approach where total values are entered at top-level branches and distributed via Stock Share and Sales Share variables.","ai_generated":true,"unit":"sei-000335#insight-2","date_modified":"2026-10-23"},{"text":"The Stock variable initializes calculations and operates alongside the Stock Vintage Profile, which tracks device distribution by age, and the First Sales Year, which marks the transition from manual stock entry to automated calculations based on sales, retirement, and forced scrappage.","ai_generated":true,"unit":"sei-000335#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy efficiency","emission standard"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000354","url":"https://climateinsightsdirectory.org/document/sei-000354","title":"Insert Plugin from Folder","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/help24/Plugins/Insert_Plugin_from_Folder.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document describes the process of using the Add Plugin wizard in LEAP to import .LEAPPlugin files, which can contain standardized methodologies, data structures, and country-specific data when used with the LEAP Cloud Data Server (LCDS). It details how users can map plugin root branches to their model's structure and manage cross-cutting data like fuels and scenarios using either simple or advanced options. After insertion, LEAP provides a summary of changes, developer instructions, and color-coded highlighting of plugin-associated branches.","ai_generated":true,"unit":"sei-000354#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP plugins function as \"mini models\" for specific sectors, subsectors, and industries, and can include standardized methodologies such as data structures, modeling relationships, and default data. When integrated with the LEAP Cloud Data Server (LCDS), these plugins can incorporate data that varies by country.","ai_generated":true,"unit":"sei-000354#insight-1","date_modified":"2026-10-23"},{"text":"The Add Plugin wizard allows users to connect plugin root branches to their model's structure, with LEAP performing checks to prevent incorrect positioning. Users can manage cross-cutting data (such as fuels, scenarios, and units) via a 'simple' option that adds all new data or an 'advanced' option that allows for adding, assigning, or ignoring individual data items, such as mapping a general fuel like \"coal\" to a specific type like \"bituminous coal\".","ai_generated":true,"unit":"sei-000354#insight-2","date_modified":"2026-10-23"},{"text":"Following the insertion of a plugin, the software provides a summary of changes and developer-written instructions. To maintain clarity, branches added via plugins are tagged with the plugin's name and are visually distinguished in the LEAP tree through color coding.","ai_generated":true,"unit":"sei-000354#insight-3","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000370","url":"https://climateinsightsdirectory.org/document/sei-000370","title":"Cost Calculations","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/Help24/Concepts/Transformation_Cost_Calculations.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes the cost-benefit calculation capabilities of LEAP, detailing the types of costs it can track, the importance of defining system boundaries to avoid double counting, and the use of real and discounted currency units to determine Net Present Value (NPV) between scenarios.","ai_generated":true,"unit":"sei-000370#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP calculates societal cost-benefit by aggregating various energy system costs, including demand costs, transformation capital and operating costs, fuel costs (indigenous, imported, or exported), pollutant emission externalities, and costs of unmet requirements.","ai_generated":true,"unit":"sei-000370#insight-1","date_modified":"2026-10-23"},{"text":"To prevent double counting, users must establish a consistent system boundary. While the default boundary covers the complete energy system, users can specify smaller boundaries to exclude specific modules, such as refining, and instead use 'Delivered Costs' for fuel products.","ai_generated":true,"unit":"sei-000370#insight-2","date_modified":"2026-10-23"},{"text":"All cost calculations in LEAP are conducted in real (constant) currency units, though results can be displayed in discounted units based on a specified discount rate. The Net Present Value (NPV) is calculated as the sum of all discounted costs and benefits of one scenario minus another across the study period.","ai_generated":true,"unit":"sei-000370#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy modeling","climate finance","energy efficiency"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000410","url":"https://climateinsightsdirectory.org/document/sei-000410","title":"Endogenous Capacity","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Transformation/Endogenous_Capacity.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document describes the functionality of endogenous capacity in LEAP, which allows the software to automatically calculate and add capacity based on user-defined processes, addition sizes, and order to ensure a planning reserve margin is maintained. It details the user's role in balancing base and peak load plants, the use of conditional expressions for addition sizes, and the ability to create supply curves using maximum built capacity and next-generation technology markers.","ai_generated":true,"unit":"sei-000410#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Endogenous capacity is a feature in LEAP that automatically calculates capacity additions to maintain a minimum planning reserve margin, operating as a supplement to exogenous capacity levels. However, this variable is not utilized when the least-cost optimization methodology is applied to a LEAP module.","ai_generated":true,"unit":"sei-000410#insight-1","date_modified":"2026-10-23"},{"text":"Users define endogenous capacity by listing available processes, specifying their addition size and the order in which they are added. LEAP cycles through these processes in the specified order to meet reserve margin requirements, and automatically retires processes once they reach their specified lifetime.","ai_generated":true,"unit":"sei-000410#insight-2","date_modified":"2026-10-23"},{"text":"The timing for when LEAP begins adding endogenous capacity is influenced by the rate of electricity requirement increases, the initial reserve margin relative to the planning reserve margin, and whether exogenous capacity is being added.","ai_generated":true,"unit":"sei-000410#insight-3","date_modified":"2026-10-23"},{"text":"LEAP allows for the creation of supply curves by combining the endogenous capacity screen with the Maximum Built Capacity variable. This enables a sequence where one process is built up to its limit before a 'next generation technology' with a later build order is added.","ai_generated":true,"unit":"sei-000410#insight-4","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000423","url":"https://climateinsightsdirectory.org/document/sei-000423","title":"Transformation Calculations","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Transformation/Transformation_Calculations.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"Transformation calculations operate on a demand-driven basis, where modules are processed sequentially to determine the primary fossil and renewable resources needed to meet domestic and export demands. The order of modules in the system tree is critical to the accuracy of the results, as outputs from one module decrement the requirements for the next while adding their own fuel inputs.","ai_generated":true,"unit":"sei-000423#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Transformation calculations are demand-driven, meaning modules operate to satisfy domestic requirements and export demands, minus any minimum specified imports.","ai_generated":true,"unit":"sei-000423#insight-1","date_modified":"2026-10-23"},{"text":"The calculation process iteratively adjusts domestic requirements by subtracting the outputs of a calculated module and adding the input fuels that the module requires, eventually identifying the total primary resource needs for fossil and renewable sources.","ai_generated":true,"unit":"sei-000423#insight-2","date_modified":"2026-10-23"},{"text":"The sequence of modules in the tree affects the calculation results; for example, an electric transmission and distribution module must be positioned above an electric generation module.","ai_generated":true,"unit":"sei-000423#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy transition","fossil fuel","renewable energy","electricity generation"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000460","url":"https://climateinsightsdirectory.org/document/sei-000460","title":"Dispatch Rule","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/help24/Transformation/Process_Dispatch_Rules.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes how LEAP handles process dispatching during simulation, detailing five specific rules—PercentShare, ProportionalToCapacity, FullCapacity, MeritOrderDispatch, and RunningCost—and the data requirements necessary to enable each.","ai_generated":true,"unit":"sei-000460#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP distinguishes between two dispatch modes: Historical Dispatch, which runs processes based on the 'Historical Production' variable for years preceding the first simulation year, and Simulation, which applies specific Process Dispatch Rules from the first simulation year onwards.","ai_generated":true,"unit":"sei-000460#insight-1","date_modified":"2026-10-23"},{"text":"The 'PercentShare' rule allows users to specify that a process meets a certain percentage of a module's requirements, provided there is enough capacity; this is particularly useful for integrating results from external models into LEAP.","ai_generated":true,"unit":"sei-000460#insight-2","date_modified":"2026-10-23"},{"text":"Two dispatch rules require capacity data: 'ProportionalToCapacity', which dispatches processes based on the ratio of their available capacity (Capacity * Maximum Availability), and 'FullCapacity', which runs processes at maximum available capacity regardless of module requirements, suitable for export-driven industries.","ai_generated":true,"unit":"sei-000460#insight-3","date_modified":"2026-10-23"},{"text":"The 'MeritOrderDispatch' rule, which requires both capacity and system load curve data, simulates power plant dispatch to meet both annual electricity demand and instantaneous power demand in time slices, based on defined merit orders.","ai_generated":true,"unit":"sei-000460#insight-4","date_modified":"2026-10-23"}],"climate_tags":["energy modeling","electric energy consumption"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000550","url":"https://climateinsightsdirectory.org/document/sei-000550","title":"Reserved Words","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/help24/Expressions/Reserved_Words.htm?agt=index","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document provides a comprehensive list of reserved words that cannot be used as names for LEAP branches, fuels, or regions because they are designated for use in expressions. It also outlines technical constraints for branch names, including a length limit of 2 to 50 characters, the requirement to start with an alphabetic character, and a list of permitted special characters.","ai_generated":true,"unit":"sei-000550#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP maintains a specific list of reserved words—including mathematical functions, units of measurement, and system indicators—that are prohibited from being used as names for branches, fuels, or regions.","ai_generated":true,"unit":"sei-000550#insight-1","date_modified":"2026-10-23"},{"text":"Branch names in LEAP must be between 2 and 50 characters long, must start with an alphabetic character, and are not case-sensitive.","ai_generated":true,"unit":"sei-000550#insight-2","date_modified":"2026-10-23"},{"text":"Branch names may only consist of alphabetic and numeric characters, or a specific set of allowed symbols: |, &, ~, \", _, ., $, #, [, ], {, and }.","ai_generated":true,"unit":"sei-000550#insight-3","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000553","url":"https://climateinsightsdirectory.org/document/sei-000553","title":"Renewable Target","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/Help24/Transformation/Renewable_Target.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The 'Renewable Target' variable defines the minimum percentage of fuel requirements that must be met by processes marked as 'Renewable Qualified'. It is used specifically for optimization-based scenarios to implement Renewable Portfolio Standards (RPS). Users must manually designate processes as renewable qualified at the process level, noting that while wind, solar, hydro, and biomass are typical candidates, certain hydro and biomass projects may not qualify for an RPS depending on the situation.","ai_generated":true,"unit":"sei-000553#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The 'Renewable Target' variable establishes the minimum percentage of fuel requirements that must be sourced from processes designated as 'Renewable Qualified' and is used to set generation targets for a Renewable Portfolio Standard (RPS).","ai_generated":true,"unit":"sei-000553#insight-1","date_modified":"2026-10-23"},{"text":"The variable is only functional in optimization-based scenarios and is currently located within Transformation modules, having been moved from load shape branches.","ai_generated":true,"unit":"sei-000553#insight-2","date_modified":"2026-10-23"},{"text":"Users must mark processes as 'Renewable Qualified' at the process level; while wind, solar, hydro, and biomass are standard, the tool allows any process to be marked as renewable regardless of feedstock, and some hydro or biomass projects may not meet RPS qualifications.","ai_generated":true,"unit":"sei-000553#insight-3","date_modified":"2026-10-23"}],"climate_tags":["renewable energy","Renewable portfolio standard","wind power","solar energy","hydropower","biomass"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000571","url":"https://climateinsightsdirectory.org/document/sei-000571","title":"Fraction of Scrapped Replaced (%)","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/Help24/Demand/Fraction_of_Scrapped_Replaced.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The 'Fraction of Scrapped Replaced (%)' variable in LEAP determines what proportion of scrapped devices are immediately replaced by new sales, which then affect the stock's energy intensities and emission factors. The default setting is 100%, meaning all scrapped vehicles are replaced, and these replacements are counted separately from the primary 'sales' variable.","ai_generated":true,"unit":"sei-000571#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The 'Fraction of Scrapped Replaced' variable defines the proportion of devices scrapped in a given year that are immediately replaced by new device sales, which are added to the stock at the same LEAP tree branch.","ai_generated":true,"unit":"sei-000571#insight-1","date_modified":"2026-10-23"},{"text":"Replacement sales triggered by this variable typically result in changes to emission factors, fuel economies, or energy intensities for the stock.","ai_generated":true,"unit":"sei-000571#insight-2","date_modified":"2026-10-23"},{"text":"The default value for this variable is 100%, and these replacement sales are calculated in addition to the figures provided in the 'sales' variable.","ai_generated":true,"unit":"sei-000571#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy modeling","fuel economy"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000583","url":"https://climateinsightsdirectory.org/document/sei-000583","title":"Expressions","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/Help24/Concepts/Expressions.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document describes the functionality of expressions in LEAP, which are mathematical formulae used to define variable values in the Analysis View for both historical data and future scenarios. It details the various methods for editing expressions—including the Expression Builder, Time-Series Wizard, and Function Wizard—and explains the system of expression inheritance, where scenarios can inherit data from parent scenarios to reduce manual entry. The guide also covers color-coding for identifying expression sources, the ability to reference both data and results variables to create endogenous models, and the 'Expression Elaboration' feature for tracking dependencies between variables.","ai_generated":true,"unit":"sei-000583#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Expressions in LEAP are mathematical formulae used to define variable values; they specify historical values in Current Accounts and define how variables change over time from the First Scenario Year to the End Year in scenarios.","ai_generated":true,"unit":"sei-000583#insight-1","date_modified":"2026-10-23"},{"text":"LEAP utilizes a hierarchical expression inheritance system to minimize data entry, allowing scenarios to inherit data from ancestor scenarios unless a different value is explicitly entered.","ai_generated":true,"unit":"sei-000583#insight-2","date_modified":"2026-10-23"},{"text":"The software uses a specific color-coding system in the Analysis View to indicate the origin of an expression: purple for explicit entry, black for inheritance from another scenario or region, green for inheritance from another region in multi-region sets, silver for default expressions, and red italics for errors.","ai_generated":true,"unit":"sei-000583#insight-3","date_modified":"2026-10-23"},{"text":"Users can create models with both exogenous and endogenous variables by referencing data variables (specified in Analysis View) and results variables (calculated internally by LEAP). Referencing results variables generally requires the PrevYearValue function to access values from a previous year, except when specifying calculated Indicator variables.","ai_generated":true,"unit":"sei-000583#insight-4","date_modified":"2026-10-23"},{"text":"The Expression Elaboration feature provides a dedicated tab in the Analysis View that lists the branches and variables a current expression depends on, as well as which branches, variables, and scenarios depend on the current branch.","ai_generated":true,"unit":"sei-000583#insight-5","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000594","url":"https://climateinsightsdirectory.org/document/sei-000594","title":"Specifying Capacity Data","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Transformation/Specifying_Capacty_Data_in_LEAP.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document outlines four approaches to capacity data in LEAP: ignoring capacity limits, using exogenous capacity for manual control of additions, using endogenous capacity for automatic timing based on reserve margins, and using least-cost optimization for automated selection and timing of capacity. It notes that optimization requires detailed cost data, whereas the other methods do not.","ai_generated":true,"unit":"sei-000594#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP allows users to ignore capacity constraints entirely, which is useful for sectors where capacity limits are not critical, such as informal charcoal making. In this mode, users only specify the share of each process via the Process Share variable.","ai_generated":true,"unit":"sei-000594#insight-1","date_modified":"2026-10-23"},{"text":"Users can manually control capacity additions and timing using the Exogenous Capacity variable, or use a hybrid approach where the Endogenous Capacity variable allows LEAP to determine the timing of additions to maintain a specified Planning Reserve Margin.","ai_generated":true,"unit":"sei-000594#insight-2","date_modified":"2026-10-23"},{"text":"LEAP provides a least-cost optimization methodology that automatically determines both the type and timing of capacity additions, as well as process dispatch. This approach is activated via the Optimize variable at the module level.","ai_generated":true,"unit":"sei-000594#insight-3","date_modified":"2026-10-23"},{"text":"The optimization approach requires more comprehensive data than simulation-based methods, specifically requiring fully defined capital, O&M, and fuel costs for each process, whereas the other three methods can function without cost data.","ai_generated":true,"unit":"sei-000594#insight-4","date_modified":"2026-10-23"}],"climate_tags":["energy modeling"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000595","url":"https://climateinsightsdirectory.org/document/sei-000595","title":"Expression Search Example 2: scenario hierarchy with multiple inheritance","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/help24/Concepts/Expression_Search_Examples/Copy_of_Expression_Search_Example_Two.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","analysis_type"],"summary":{"text":"The document describes how the LEAP software resolves variable expressions in a scenario hierarchy involving multiple inheritance. Using a 'Mitigation' scenario as an example—which inherits from 'industry', 'buildings', and 'transport' scenarios—it outlines a four-step search sequence: first checking the active scenario, then the additional inherited scenarios in order, then walking up the main scenario tree to the 'Baseline' and 'Current Accounts' scenarios, and finally reverting to a default value.","ai_generated":true,"unit":"sei-000595#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"In a scenario hierarchy with multiple inheritance, LEAP follows a specific sequential search order to find a variable expression: it starts with the active scenario, moves to additional scenarios listed in the 'First Inherits From' box, walks up the main scenario tree, and ends with the default value.","ai_generated":true,"unit":"sei-000595#insight-1","date_modified":"2026-10-23"},{"text":"For the specific example provided, the full expression search order is: Mitigation, Industry, Buildings, Transport, Baseline, Current Accounts, Default Value.","ai_generated":true,"unit":"sei-000595#insight-2","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000659","url":"https://climateinsightsdirectory.org/document/sei-000659","title":"Data","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://leap.sei.org/Data","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The document describes the technical interface for the LCDS database, detailing the REST web service queries available to retrieve data sets, country lists, and specific time series data for energy and environment models. It provides specific URL examples for accessing UN Population Prospects, World Development Indicators, IDEES, and IPCC Shared Socioeconomic Pathway GDP projections.","ai_generated":true,"unit":"sei-000659#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The data server provides several query types to retrieve information: 'DataSets' for available sets and update dates, 'List' for a simple set list, 'Info' for data set dimensions, 'Countries' for ISO3 codes and names, and 'Data' for specific data set values based on parameters such as ISO3 codes and dimensions.","ai_generated":true,"unit":"sei-000659#insight-1","date_modified":"2026-10-23"},{"text":"The system supports data from multiple sources, including the U.N. Population Prospects, the World Development Indicators database, the IDEES dataset, and the IPCC's Shared Socioeconomic Pathway database for GDP projections from 1990-2100.","ai_generated":true,"unit":"sei-000659#insight-2","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Ghana","United States","France","People's Republic of China"],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000782","url":"https://climateinsightsdirectory.org/document/sei-000782","title":"Tree Branches","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Screen_Layout/Types_of_Tree_Branches.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes the various branch types used in LEAP to organize data, including Key Assumption, Category, Technology, Fuel, Environmental Loading, and Indicator branches, detailing their specific roles in demand, transformation, and resource analysis.","ai_generated":true,"unit":"sei-000782#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP utilizes several specialized branch types to structure data: Key Assumption branches for independent time-series variables like GDP or population; Category branches for hierarchical organization of sectors and resources; and Technology branches to represent energy-consuming devices or conversion processes.","ai_generated":true,"unit":"sei-000782#insight-1","date_modified":"2026-10-23"},{"text":"Technology branches are further divided into three types based on the calculation method: Activity Level Technologies (activity level multiplied by annual energy intensity), Stock Technologies (turnover of energy-using devices), and Transport Technologies (turnover of vehicles).","ai_generated":true,"unit":"sei-000782#insight-2","date_modified":"2026-10-23"},{"text":"Specific branches handle fuel and environmental data: Fuel branches track output, primary resources, and secondary fuels, while Environmental Loading branches are used to specify pollutant emissions wherever fuel is combusted or in non-energy sectors.","ai_generated":true,"unit":"sei-000782#insight-3","date_modified":"2026-10-23"},{"text":"The software imposes structural restrictions on the tree, prohibiting the movement of branches between the four primary categories—Key Variables, Demand, Transformation, and Resources—and generally preventing the mixing of different branch icons at the same level.","ai_generated":true,"unit":"sei-000782#insight-4","date_modified":"2026-10-23"}],"climate_tags":["energy modeling","greenhouse gas emissions"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide"]},{"id":"sei-000838","url":"https://climateinsightsdirectory.org/document/sei-000838","title":"Visibility of Land-Based Resource Variables","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Land-based_Resource_Calculations/Visibility_of_Land-Based_Resource_Variables.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document provides a step-by-step procedure for activating land-based resource calculations in LEAP, starting with enabling the 'Land-Use Change and Land-Based Resources' option in the Scope & Scale settings. It details the necessity of defining land types and regions, as well as configuring resource properties in the General: Fuels screen. The guide notes that enabling these settings reveals new branches in the main tree for specifying land areas and conversions, and that the available variables under the Resources branch vary depending on whether the user is analyzing wood resources or other renewable energy forms like solar, wind, and biomass.","ai_generated":true,"unit":"sei-000838#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"To activate land-based resource analysis in LEAP, users must first enable the 'Land-Use Change and Land-Based Resources' option in the Scope & Scale tab of the General: Settings screen; otherwise, all related variables are hidden and excluded from calculations.","ai_generated":true,"unit":"sei-000838#insight-1","date_modified":"2026-10-23"},{"text":"Setting up a land-based resource analysis requires creating a list of land types and, because these analyses typically require geographic disaggregation, the authors recommend using a multi-regional model for sizable energy systems such as countries.","ai_generated":true,"unit":"sei-000838#insight-2","date_modified":"2026-10-23"},{"text":"The software provides different levels of detail based on the resource type: wood resources include complex variables for stocks, growth, and demand/supply interactions, whereas other resources (such as solar, wind, and biomass) only consider annual energy productivity.","ai_generated":true,"unit":"sei-000838#insight-3","date_modified":"2026-10-23"}],"climate_tags":["land-use change","biomass","solar energy","wind power","renewable energy","energy modeling"],"geography_discussed":["Freedonia"],"frame_perspective":[],"analysis_type":["technical guide"]}]}