|ID||Name||Developer||Scope||Platform||Methodology||Description||Model URL||Cost||Image URL||Long Name||Developer URL|
|3||COMPOSE||EnergiAnalyse, Denmark||Cost-benefit and cost-effectiveness toolbox for private and public decision-makers.||Windows||Accounting/Optimization||
COMPOSE is a parametric linear programming model for designing and evaluating energy options within an energy-economy system. COMPOSE is also a social platform for sharing, comparing, and safe-keeping case studies and solutions about how energy demands, supply processes, and markets interact in the quest for sustainable energy. COMPOSE provides a rapid and powerful basis for comparative energy systems analysis that is consistent with the micro-economic reality of operational scheduling.
|http://www.energianalyse.dk/||Free for academic users. Contact author for other prices.||https://cdn.leap.sei.org/ToolImages/compose.png||Compare Options for Sustainable Energyemail@example.com||http://www.energianalyse.dk/|
|7||EFFECT||World Bank||GHG emissions scenarios.||Excel||Accounting||
EFFECT: the Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) is an open and transparent spreadsheet-based modeling tool used to forecast greenhouse gas (GHG) emissions from a range of development scenarios. It focuses on sectors that contribute to and are expected to experience a rapid growth in emissions. The model was initially developed by the World Bank while working with the Government of India on an analysis of their national energy plan. It has since been used in eleven countries, including Brazil, Poland, Georgia, Macedonia, Nigeria, and Vietnam.
EFFECT forecasts GHG emissions for given development scenarios or policy choices. In addition to forecasting GHG Emissions, it enables consensus building among disparate government departments, and forecasts energy balances and amounts of energy generating/consuming assets in a country or sector. It also produces results for individual sectors such as road transport, agriculture, power, industry, household and non-residential sectors.
Important Note: The World Bank now describes EFFECT as a "Legacy Tool". It is no longer being developed or supported, but may still be downloaded.
|https://esmap.org/node/1363||Free||Energy Forecasting Framework and Emissions Consensus Toolfirstname.lastname@example.org||https://www.esmap.org/|
|10||EnergyPLAN||Aalborg University, Denmark||Simulates and optimizes the operation of an entire national energy system for every hour in a particular year.||Windows||Simulation/Optimization||
EnergyPLAN is a Windows-based tool created to assist in the design of national or regional energy planning strategies. It is a deterministic input/output model. General inputs are demands, renewable energy sources, energy station capacities, costs and a number of optional different regulation strategies emphasizing import/export and excess electricity production. Outputs are energy balances and resulting annual productions, fuel consumption, import/export of electricity, and total costs including income from the exchange of electricity.
EnergyPLAN has been applied in Denmark and a number of other European Countries. It is a deterministic model using hourly simulations of load for a single year. It optimizes the operation of a given system across all fuels as opposed to models which optimize investments in the system. EnergyPLAN is based on analytical programming as opposed to iterations, dynamic programming or advanced mathematical tools.
|13||Energy Costing Tool||UNDP||Estimates the amounts and types of energy investments required to meet the Millennium Development Goals (MDGs)||Excel||Accounting||
A crucial part of developing MDG-based national development strategies is MDG costing, which quantifies the specific financial and human resources needed, as well as infrastructure required, to meet the MDGs.
The Energy Costing Tool has been designed specifically to help government planners and decision makers estimate the amounts and types of energy investments required to meet the MDGs.
The tool is available for download here
|14||LEAP||SEI||Integrated Energy/Environment Analysis||Windows||Accounting/Simulation/Optimization||
LEAP is a integrated scenario-based energy-environment modeling tool that accounts for how energy is consumed, converted and produced in a given energy system under a range of alternative assumptions. LEAP is primarily an accounting system but users can also build econometric, simulation and optimization-based models. Users can mix and match these methodologies as required in a given analysis. For example, a user might create top-down projections of energy demand in one sector based on a few macroeconomic indicators (price, GDP), while creating a detailed bottom-up forecast based on an end-use analysis in other sectors.
LEAP supports both final and useful energy demand analyses as well as detailed stock-turnover modeling for transportation and other analyses. On the supply side LEAP supports a range of simulation and optimization methods for modeling both capacity expansion and plant dispatch. LEAP includes a built-in Technology and Environmental Database (TED) containing data on the costs, performance and emission factors for over 1000 energy technologies. LEAP can be used to calculate the emissions profiles and can also be used to create scenarios of non-energy sector emissions and sinks (e.g. from cement production, land-use change, solid waste, etc.).
|http://www.energycommunity.org||Free to non-profit, academic and government sector organizations based in low and lower-middle income countries. Free to accredited students worldwide. Licensing costs for other institutions.||https://cdn.leap.sei.org/ToolImages/LEAP.PNG||Long-range Energy Alternatives Planning Systememail@example.com||http://www.sei-international.org|
|15||TIMES/MARKAL||ETSAP||Integrated Energy/Environment Analysis||Windows||Optimization||
MARKAL (MARket ALlocation) is a technology-focused energy/economic/environmental model. It was developed in a collaborative effort under the auspices of the International Energy Agency Energy Technology Systems Analysis Programme (ETSAP).
MARKAL is a generic model tailored by the input data to represent the evolution over a period of usually 20 to 50 years of a specific energy-environment system at the national, regional, state or province, or community level. The system is represented as a network, depicting all possible flows of energy from resource extraction, through energy transformation and end-use devices, to demand for useful energy services. Each link in the network is characterized by a set of technical coefficients (e.g., capacity, efficiency), environmental emission coefficients (e.g., CO2, SOx, NOx), and economic coefficients (e.g., capital costs, date of commercialization). Many such energy networks or Reference Energy Systems (RES) are feasible for each time period. MARKAL finds the best RES for each time period by selecting the set of options that minimizes total system cost over the entire planning horizon.
TIMES (The Integrated MARKAL-EFOM System) builds on the best features of MARKAL and the Energy Flow Optimization Model (EFOM). In order to work with MARKAL, you need a number of software elements: MARKAL itself, a user-interface (two are available for Windows: ANSWER and VEDA), GAMS (a high-level modeling system for mathematical programming problems) and an optimizing solver such as MINOS, CPLEX or OSL.
A number of varations of MARKAL are available including:
|https://iea-etsap.org/index.php/etsap-tools||$3,300-$15,000 depending on type of institution.||https://cdn.leap.sei.org/ToolImages/markal.png||The Integrated MARKAL-EFOM Systemfirstname.lastname@example.org||http://www.iea-etsap.org/web/tools.asp|
|16||OSeMOSYS||KTH, SEI, UCL et al||Long-run energy planning based on Linear Programming optimization techniques.||GLPK: The GNU Linear Programming Kit||Optimization||
OSeMOSYS the Open Source energy MODeling SYStem, is a simple, powerful, transparent, modeling system that can be used for linear programming based energy system optimization modeling. OSeMOSYS is open source and totally free to use. It is built open the GNU Linear Programming Kit (GLPK), an open source mathematical programming language. It has been created by a consortium of organizations lead by KTH, the Royal Institute of Technology in Sweden and including SEI, UNIDO, IAEA, and the UK Energy Research Center. OSeMOSYS is provided as a simple text file written in the GLPK language and it is also embedded within the LEAP energy modeling system.
|http://www.osemosys.org/||Free and Open Source||https://cdn.leap.sei.org/ToolImages/osemosys.png||The Open Source Energy Modeling Systememail@example.com||http://www.osemosys.org/|
|17||RETScreen||NRCAN||Energy production, life-cycle costs and GHG emission reductions for various energy efficient and renewable energy technologies||Excel or Windows (RETScreen Plus)||Accounting||
RETScreen International Clean Energy Project Analysis Software can be used world-wide to evaluate the energy production, life-cycle costs and greenhouse gas emission reductions for various types of energy efficient and renewable energy technologies (RETs). The software also includes product, cost and weather databases, and a detailed online user manual. The RETScreen International Online Product Database provides users access to contact information for more than 1,000 clean energy technology manufacturers around the globe, including direct Website and Internet links from within the RETScreen software and from this Website (Marketplace). In addition, the database provides access to pertinent product performance and specifications data for a number of these manufacturers. These data can be "pasted" to the relevant cells within the RETScreen software. The RETScreen software currently includes modules for evaluating: wind energy, small hydro, solar photovoltaics (PVs), combined heat and power, biomass heating, solar air heating, solar water heating, passive solar heating, ground-source heat pumps, and refrigeration.
|https://www.nrcan.gc.ca/maps-tools-publications/tools/data-analysis-software-modelling/retscreen/7465||Free||https://cdn.leap.sei.org/ToolImages/retscreen.jpg||RETScreen Clean Energy Project Analysis Softwarefirstname.lastname@example.org||http://www.retscreen.net/|
|18||MESSAGE||IAEA and IIASA||Integrated Energy/Environment Analysis||Windows||Optimization||
MESSAGE is used to formulate and evaluate alternative energy supply strategies under different user defined and physical constraints. Examples include: new investment limits, market penetration rates for new technologies, fuel availability and trade, environmental emissions, etc. MESSAGE is extremely flexible and can also be used to analyze energy/electricity markets and climate change issues. It belongs to the same family of models as MARKAL, EFOM and TIMES and relies on a technology rich description of the energy system. It chooses the most cost effective arrangement of technologies and energy carrier use to meet the demands for energy service specified. Unlike many other optimization models, it does not require purchases of GAMS, nor a commercial solver. A free Linear Programming (LP) solver is provided. However depending on the problem complexity more powerful LP and Non-Linear Programming (NLP) solvers, such as CPLEX, can be seamlessly used by the software.
MESSAGE is the subject of a special agreement between IIASA and the International Atomic Energy Agency (IAEA). IAEA distributes a modified version of MESSAGE with a graphical front-end as well as training on how to use it.
|https://www.iaea.org/topics/energy-planning/energy-modelling-tools||Free to public sector, non-profit and research organizations. Requires governmental agreement with IAEA.||https://cdn.leap.sei.org/ToolImages/message.jpg||Model for Energy Supply Strategy Alternatives||PESS.Contact-Point@iaea.org||https://www.iaea.org/OurWork/ST/NE/Pess/capacitybuilding.html|
|19||WEAP||SEI||Software tool for integrated water resources planning. Provides a comprehensive, flexible and user-friendly framework for planning and policy analysis. Can also be used with LEAP for energy-water "nexus" analyses.||Windows||Accounting/Simulation||
Freshwater management challenges are increasingly common. Allocation of limited water resources between agricultural, municipal and environmental uses now requires the full integration of supply, demand, water quality and ecological considerations. WEAP, the Water Evaluation And Planning system is a user-friendly software tool that incorporates these issues into a practical yet robust tool for integrated water resources planning. It provides a comprehensive, flexible and user-friendly framework for planning and policy analysis. WEAP also be used in conjunction with LEAP for energy-water nexus analyses.
|http://www.weap21.org||Free to non-profit, academic and government sector organizations based in low-income and lower-middle-income countries. Licensing costs for other institutions||https://cdn.leap.sei.org/ToolImages/WEAP.GIF||Water Evaluation and Planning Systememail@example.com||http://www.sei-international.org|
|20||TRACE||World Bank||Decision-support to help cities prioritize sectors and actions for energy efficiency interventions.||Windows||Accounting||
The Tool for Rapid Assessment of City Energy (TRACE) is a decision-support tool designed to help cities quickly identify under-performing sectors, evaluate improvement and cost-saving potential, and prioritize sectors and actions for energy efficiency (EE) intervention. It covers six municipal sectors: passenger transport, municipal buildings, water and waste water, public lighting, solid waste, and power and heat.
TRACE consists of three modules: an energy benchmarking module which compares key performance indicators (KPIs) among peer cities, a sector prioritization module which identifies sectors that offer the greatest potential with respect to energy-cost savings, and an intervention selection module which functions like a “playbook” of tried-and-tested EE measures and helps select locally appropriate EE interventions.
Important Note: The World Bank now describes MACTool as a "Legacy Tool". It is no longer being developed or supported, but may still be downloaded.
|https://esmap.org/node/235||Free||https://cdn.leap.sei.org/ToolImages/TRACE.jpg||Tool for Rapid Assessment of City Energyfirstname.lastname@example.org||https://www.esmap.org/|
|21||MAED||IAEA||Energy Demand Modeling||Excel||Accounting||
MAED evaluates future energy demands based on medium- to long-term scenarios of socioeconomic, technological and demographic development. Energy demand is disaggregated into a large number of end-use categories corresponding to different goods and services in different sectors. The influences of social, economic and technological driving factors from a given scenario are estimated. These are combined to give an overall picture of future energy demand growth. Based on efficiencies of end-use appliances, useful energy as well as final energy demand is estimated. MAED is written using a series of excel macros. The tool and the manual is available in English, French and Spanish.
|https://www.iaea.org/topics/energy-planning/energy-modelling-tools||Free to public sector, non-profit and research organizations. Requires governmental agreement with IAEA.||https://cdn.leap.sei.org/ToolImages/maed.jpg||Model for Analysis of Energy Demand||PESS.Contact-Point@iaea.org||https://www.iaea.org/OurWork/ST/NE/Pess/capacitybuilding.html|
|22||GEMIS||IINAS||A life-cycle and material flow analysis model and database.||Windows||Accounting||
GEMIS is a public domain life-cycle and material flow analysis model and database that IINAS provides freely.
GEMIS was first released in 1989, and is continuously updated and extended since then. It is used by many parties in more than 30 countries for environmental, cost and employment analyses of energy, materials and transport systems.
IINAS continues networking with GEMIS users on the international level, and extending and improving the model, and its database.
|http://www.iinas.org/gemis.html||Free and Open Source||https://cdn.leap.sei.org/ToolImages/gemis.jpg||Global Emissions Model for integrated Systemsemail@example.com||http://www.iinas.org/|
|23||HOMER Pro||HOMER Energy LLC||Microgrid planning and optimization software||Windows||Accounting/Optimization||
HOMER Pro is a tool for microgrid planning for systems that can include a combination of renewable power sources, storage, and fossil-based generation (either through a local generator or a power grid). HOMER's optimization and sensitivity analysis algorithms allow you to evaluate the economic and technical feasibility of a large number of technology options and to account for variations in technology costs, electric load, and energy resource availability. Originally designed at the National Renewable Energy Laboratory for the village power program, HOMER is now licensed to HOMER Energy.
HOMER provides chronological simulation and optimization in a model that is relatively simple and easy to use. It is adaptable to a wide variety of projects. For a village or community-scale power system, HOMER can model both the technical and economic factors involved in the project. For larger systems, HOMER can provide an important overview that compares the cost and feasibility of different configurations, so that designers can use more specialized software to model technical performance.
HOMER is accessible to large set of users, including non-technical decision makers. Chronological simulation is essential for modeling variable resources, such as solar and wind power and for combined heat and power applications where the thermal load is variable. HOMER’s sensitivity analysis helps determine the potential impact of uncertain factors such as fuel prices or wind speed on a given system.
HOMER models both conventional and renewable energy technologies, either as a microgrid or as distributed generation within a larger grid.
|http://www.homerenergy.com||$500-$1400/year or $1500-$4200 permanent. (free 30 day trial)||https://cdn.leap.sei.org/ToolImages/HOMER.PNG||Hybrid Optimization Model for Multiple Energy Resourcesfirstname.lastname@example.org||http://www.homerenergy.com/|
|24||MAC Tool||World Bank||Tool for building Marginal Abatement Cost Curves (MACCs)||Excel||Accounting||
The Marginal Abatement Cost Tool (MACTool) provides an easy way for building marginal abatement cost curves, and for calculating break-even carbon prices. The user-friendly interface guides users through a simple data entry process, which simplifies a typically laborious process.
MACTool helps policymakers compare the costs and benefits of emission reduction options that can be used to build low-carbon scenarios at a national or sub-national level. It provides a cost-benefit comparison of these options and an estimate of the incentives needed to make these options attractive for the private sector by calculating break-even carbon prices. It also enables governments to assess the total investment needed to shift towards low carbon growth. MACTool can also be used to test the possibility of a domestic cap and trade system, by exploring which sectors would most likely to respond to a given carbon price.
MACTool builds a reference scenario and low carbon scenarios for each individual low-carbon option. It allows users to schedule investments for low carbon alternatives along the planning period. It calculates the differential in emissions, investments, costs and revenues between the scenarios, and generates customized curves that make it easy to visualize options.
Important Note: The World Bank now describes MACTool as a "Legacy Tool". It is no longer being developed or supported, but may still be downloaded.
|https://esmap.org/sites/esmap.org/files/MACTool_FEB2016.xlsb||Free||https://cdn.leap.sei.org/ToolImages/mactool.png||The Marginal Abatement Cost Toolemail@example.com||https://www.esmap.org/|
|25||ENPEP-BALANCE||Argonne National Lab||Integrated energy systems analysis||Windows||Simulation||
ENPEP-BALANCE is an integrated energy system model that uses a market-based simulation approach to examine how various segments of the energy system will respond to changes in energy prices and demands.
ENPEP-BALANCE is a nonlinear equilibrium model that matches the demand for energy with available resources and technologies. Its market-based simulation approach allows ENPEP-BALANCE to determine the response of various segments of the energy system to changes in energy prices and demand levels. The model relies on a decentralized decision-making process in the energy sector and can be calibrated to the different preferences of energy users and suppliers. Basic input parameters include information on the energy system structure, base-year energy statistics including production, and consumption levels and prices, projected energy demand growth, and any technical and policy constraints.
In this process, an energy network is designed to trace the flow of energy from primary resources to useful energy demands in the end-use sectors. ENPEP-BALANCE networks are constructed by using different nodes and links that represent various energy system components. Nodes in the network represent depletable and renewable resources, various conversion processes, refineries, thermal and hydro power stations, cogeneration units, boilers and furnaces, marketplace competition, taxes and subsidies, and energy demands.
|http://ceeesa.es.anl.gov/projects/Enpepwin.html||Free||https://cdn.leap.sei.org/ToolImages/enpep.png||Energy and Power Evaluation Programfirstname.lastname@example.org||http://ceeesa.es.anl.gov|
|26||SUPER||OLADE||Electricity demand, transmission, capacity expansion and generation model including hydrology for hydro systems, planning under uncertainty, hydro-thermal dispatch, financial, and environmental analysis||Windows||Simulation/Optimization||
The SUPER model is a multi-year generation and power system inter-connection planning studies, considering parameters such as hydro risks, reservoir features, demand growth and hourly characteristics, energy conservation and load management programs, fuel costs, project execution periods, inter-connections, etc. It is used by over 10 countries, by national electric planning entities, power sector regulation and control agencies, consultants, and generation and transmission companies. The model contains the following modules: Energy Demand and Conservation, Hydrology, Planning under Uncertainty, Hydro-thermal Dispatch, Financial, and Environmental analysis.
Important Note: As far as we can tell, SUPER appears to no longer be available.
|http://www.olade.org||US$3,600 with one year of support and updates.||Sistema Unificado de Planificación Eléctrica Regionalemail@example.com||http://www.olade.org/|
|31||CURB||World Bank||Tool to help cities take action on climate by mapping out different action plans and evaluating their cost, feasibility, and impact.||Excel||Accounting||
With the bulk of energy use and GHG emissions emanating from urban areas, cities have a key part to play in combating climate change. By reducing their environmental footprint, cities will not only lower their contribution to global GHG emissions, but can also enjoy significant local benefits such as improved air quality, better health outcomes, local economic development and job creation. CURB is an interactive tool that is designed specifically to help cities take action on climate by allowing them to map out different action plans and evaluate their cost, feasibility, and impact.
CURB’s key features
|http://www.worldbank.org/en/topic/urbandevelopment/brief/the-curb-tool-climate-action-for-urban-sustainability||Free||https://cdn.leap.sei.org/ToolImages/curb.png||Climate Action for Urban Sustainabilityfirstname.lastname@example.org||http://www.worldbank.org/|
|33||PLEXOS||Energy Exemplar||Integrated Energy Planning||Windows||Optimization||
PLEXOS is an integrated energy model that combines mathematical optimisation with the data handling, visualisation and distributed computing methods, to provide a simulation system for electric power, water and gas systems.
|https://www.energyexemplar.com/plexos||For purchase: contact Energy Examplar for costs.||https://cdn.leap.sei.org/ToolImages/plexos2.jpg||PLEXOS Integrated Energy Modeemail@example.com||http://energyexemplar.com/|
|34||GREET||Argonne National Lab||Well-to-wheel full lifecyclevehicle-cycle analysis of emissions from transportation options.||Excel||Accounting||
To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis.
The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. The most recent GREET versions are the GREET1 2015 version for fuel-cycle analysis and GREET2 2015 version for vehicle-cycle analysis.
GREET was developed as a multidimensional spreadsheet model in Microsoft Excel. This public domain model is available free of charge for anyone to use.
|https://greet.es.anl.gov/||Free||https://cdn.leap.sei.org/ToolImages/greet.jpg||The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Modelfirstname.lastname@example.org||http://www.anl.gov/|
|35||MOVES||US EPA||US-focused model for calculating emissions inventories from mobile sources.||Windows||Accounting||
MOVES is the U.S. Environmental Protection Agency's (EPA) Motor Vehicle Emission Simulator. It is used to create emission factors or emission inventories for both onroad motor vehicles and nonroad equipment. The purpose of MOVES is to provide an accurate estimate of emissions from cars, trucks and non-highway mobile sources under a wide range of user-defined conditions.
In the modeling process, the user specifies vehicle types, time periods, geographical areas, pollutants, vehicle operating characteristics, and road types to be modeled. The model then performs a series of calculations, which have been carefully developed to accurately reflect vehicle operating processes, such as running, starts, or hoteling, and provide estimates oftotal emissions or emission rates per vehicle or unit of activity. Specifying thecharacteristics of the particular scenario to be modeled is done by creating a Run Specification, or RunSpec.
In addition, the MOVES model includes a default database that summarizes emission relevant information for the entire United States. The MOVES team continually works to improve this database, but, for many uses, up-to-date local inputs will be more appropriate, especially for analyses supporting State Implementation Plans (SIPs) and conformitydeterminations.
|https://www.epa.gov/moves||Free||https://cdn.leap.sei.org/ToolImages/moves.png||Motor Vehicle Emission Simulatoremail@example.com||https://www.epa.gov/|
|36||CLEER||US AID||Estimates, tracks, and reports GHG emission reductions for US AID-supported Clean Energy programs.||Excel||Accounting||
The CLEER Tool provides simple, standardized methodologies for calculating emissions reductions from clean energy activities. The tool provides users with a consistent approach for estimating, tracking, and reporting GHG reductions impacts on clean energy programs, which may help users identify high impact activities with cost effective GHG reductions, assess emissions reduction potential of planned activities or alternatives, and measure benefits from indirect clean energy activities.
Clean energy activities covered by the tool include renewable energy (e.g., solar photovoltaic, wind turbines, geothermal, hydroelectric), energy efficiency (building and appliance efficiency), biomass energy, fuel switching, and a list of other technology types that continues to grow.
For USAID-supported projects, CLEER assists implementers in reporting GHG emissions reduced, sequestered, and/or avoided, a required standard indicator for clean energy projects.
|https://www.cleertool.org/||Free||https://cdn.leap.sei.org/ToolImages/cleer.png||Clean Energy Emission Reduction Tool||CLEERHelp@icfi.com||https://www.usaid.gov/|
|37||BALMOREL||Ravn, Hans||International GAMS-based energy system model of electricity and combined heat and power sectors.||GAMS||Optimization||
Balmorel is a model for analysing the electricity and combined heat and power sectors in an international perspective. It is highly versatile and may be applied for long range planning as well as shorter time operational analysis. The model is developed in a model language, and the source code is readily available, thus providing complete documentation of the functionalities. Moreover, the user may modify the model according to specific requirements, making the model suited for any purpose within the focus parts of the energy system.
The Balmorel model has been applied in projects in Denmark, Norway, Estonia, Latvia, Lithuania, Poland, Germany, Austria, Ghana, Mauritius, Canada and China. It has been used for analyses of, i.a., security of electricity supply, the role of flexible electricity demand, hydrogen technologies, wind power development, the role of natural gas, development of international electricity markets, market power, heat transmission and pricing, expansion of electricity transmission, international markets for green certificates and emission trading, electric vehicles in the energy system, environmental policy evaluation.
|http://www.balmorel.com/||Free: requires GAMS||HansRavn@aeblevangen.dk||http://www.balmorel.com/|
|38||META||World Bank||Compares the economic costs of more than 50 electricity generation and delivery technologies including externalities.||Excel||Accounting||
The Model for Electricity Technology Assessment (META) facilitates the comparative assessment of the economic costs of more than 50 electricity generation and delivery technologies, including conventional generation options (thermal, hydroelectric, etc.), nonconventional options (renewables), and emerging options such as power storage and carbon capture and storage (CCS).
META has an option for incorporating the costs associated with externalities in power generation such as local pollution and Green House Gas emissions. The META model can also be used to undertake uncertainty analysis for selected key inputs.
META is populated with default performance and cost data inputs drawn from three representative countries: India, Romania and the USA, which were chosen as proxies for developing, middle-income and developed countries, respectively. Users also have the option of customizing the data for new countries by entering detailed input data directly into model and for as many parameters as they consider necessary.
Important Note: The World Bank now describes META as a "Legacy Tool". It is no longer being developed or supported, but may still be downloaded.
|https://esmap.org/node/3051||Free||https://cdn.leap.sei.org/ToolImages/meta.jpg||Model for Electricity Technologyfirstname.lastname@example.org||https://www.esmap.org/|
|39||SIMPACTS||IAEA||Estimates health and environmental damage costs of different electricity generation technologies||Windows||Accounting||
SIMPACTS estimates and quantifies the health and environmental damage costs of different electricity generation technologies.
SIMPACTS can be used by energy analysts and decision makers forcomparing and ranking various electricity generation options in terms of external costs. SIMPACTS covers the major electricity generation sources and most of the associated impacts on human health and the environment. It provides a simple but accurate tool for estimating externalcosts associated with electricity generation.
|https://www.iaea.org/topics/energy-planning/energy-modelling-tools||Free to public sector, non-profit and research organizations. Requires governmental agreement with IAEA.||Simplified Approach for Estimating Environmental Impacts of Electricity Generation||PESS.Contact-Point@iaea.org||https://www.iaea.org/OurWork/ST/NE/Pess/capacitybuilding.html|
|40||WASP||IAEA||Electric sector long-range capacity expansion planning.||Windows||Optimization||
WASP is the IAEA’s model for analysing expansion plans for electricity generation.
WASP permits the user to find an optimal expansion plan for powergeneration over a long period of time and within the constraints identified.This may include fuel availability, emission restrictions, system reliability,etc. Each sequence of power plants that could be added and which meetsthe constraints, is evaluated by a cost function of capital, fuel, O&M, fuelinventory, salvage value of investments and cost of energy demand not served.
|https://www.iaea.org/topics/energy-planning/energy-modelling-tools||Free to public sector, non-profit and research organizations. Requires governmental agreement with IAEA.||https://cdn.leap.sei.org/ToolImages/wasp.png||Wien Automatic System Planning Package||PESS.Contact-Point@iaea.org||https://www.iaea.org/OurWork/ST/NE/Pess/capacitybuilding.html|
|41||SIELAC||OLADE||Latin American energy statistics database||Web||Database||
SIELAC is an information system containing data on the most important variables of the energy sector in Latin America and the Caribbean from 1970 to present.
SILAC consolidates information from OLADE's 27 member countries from Latin America and the Caribbean for the energy sector amd establishes uniform criteria for standardization, and reliability. It presents historical time series data for the most important variables in the energy sector, from which you can identify key trends, identify the causes of changes in the composition of the energy mix, and the prospect of future behavior of the sector.
SIELAC integrates vital information from across the energy sector including data for the energy balances of Latin American countries.
SIELAC is intended to be used by ministries or departments of energy, public and private entities in the energy sector, universities, consultants and investors.
It includes data on issues related to energy balances, greenhouse gases, economic indicators, energy, supply and demand, prices, reserves, resource potentials, energy infrastructure, energy sector legal and institutional information, and supranational energy-related regulations.
|http://sielac.olade.org/||Free||https://cdn.leap.sei.org/ToolImages/SIELAC.png||Sistema de Información Energética de Latinoamérica y El Caribeemail@example.com||http://www.olade.org/|
|44||CityInSight||Sustainability Solutions Group||City-scale energy, emissions and finance model.||Unknown||Geospatial systems dynamics modeling||
The CityInSight energy, emissions and finance model for cities helps local and regional governments assess the impacts of potential land-use planning actions on GHG emissions, and public and private energy costs. This helps assess housing development impacts, transportation proposals, agriculture and forestry uses, solid and liquid waste approaches, energy delivery strategies, energy efficiency strategies and much more. CityInSight informs decision-makers about the energy and emissions impacts of their decisions, helping them achieve urban design, energy and emissions goals.
|https://www.ssg.coop/tools/||Free and open source||https://cdn.leap.sei.org/ToolImages/cityinsight.jpg||Unknown||http://www.ssg.coop/|
|48||CREST||NREL||Economic cash flow model to assess renewable energy project economics, design cost-based incentives, and evaluate support structures.||Excel||Accounting||
The Cost of Renewable Energy Spreadsheet Tool (CREST) is an economic cash flow model designed to allow policymakers, regulators, and the renewable energy community to assess project economics, design cost-based incentives (e.g., feed-in tariffs), and evaluate the impact of various state and federal support structures. CREST is a suite of four analytic tools, for solar (photovoltaic and solar thermal), wind, geothermal, and anaerobic digestion technologies.
CREST is a product of a 2009-2010 partnership between the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP), and the National Association of Regulatory Utility Commissions (NARUC). The model was developed by Sustainable Energy Advantage (SEA) under the direction of NREL.
|https://www.nrel.gov/analysis/crest.html||Free||https://cdn.leap.sei.org/ToolImages/crest.jpg||Cost of Renewable Energy Spreadsheet Toolfirstname.lastname@example.org||http://www.nrel.gov/|
|49||FINPLAN||IAEA||Calculates the financial implications of an expansion plan for a power generating system||Web||Accounting||
FINPLAN evaluates the financial implications of an expansion planfor a power generating system. The model helps establish financialfeasibility of electricity generation projects by computing importantfinancial indicators while taking into account all costs, financing options,revenues, taxes, etc.
FINPLAN was designed to help energy analysts and decision makers inanalysing the financial implications of a power project. The model treats allexpenditures in a foreign and the local currency. The cash flows for allexpenditures in the respective currencies are maintained and the impact of future exchange rate changes is analysed. The model helps to analyse the impact of assumed future conditions that affect the financial health of a company.
|https://www.iaea.org/topics/energy-planning/energy-modelling-tools||Free to public sector, non-profit and research organizations. Requires governmental agreement with IAEA.||https://cdn.leap.sei.org/ToolImages/finplan.jpg||Financial Analysis of Electric Sector Expansion Plans||PESS.Contact-Point@iaea.org||https://www.iaea.org/OurWork/ST/NE/Pess/capacitybuilding.html|
|56||C-ROADS||Climate Interactive||Simulates climate impacts of policy scenarios to reduce GHG emissions.||Windows and Mac||Systems Dynamics||
C-ROADS is a free computer simulation program that helps people understand the long-term climate impacts of policy scenarios to reduce greenhouse gas emissions. It allows for the rapid summation of national greenhouse gas reduction pledges in order to show the long-term impact on our climate.
|https://www.climateinteractive.org/tools/c-roads/||Free||https://cdn.leap.sei.org/ToolImages/c-roads.png||Climate change policy simulator||https://www.climateinteractive.org|
|58||JEDI||NREL||Jobs and economic impacts of implementing energy sector facilities.||Excel||Economic cost-benfit analysis (economic multipliers)||
The Jobs and Economic Development Impacts (JEDI) International Model allows users to estimate job creation and economic development impacts from international energy sector projects. It includes default information that can be utilized to run a generic impact analysis assuming industry averages. The models have a particular focus on renewable energy technologies.
|59||GAP||IED||Long-run energy generation analysis and planning including technical and economic optimization||Windows||Optimization||
GAP is a software tool for the analysis and planning of energy power systems for a given territory or country. It makes it possible to optimize investments related to energy generation and the development of new power plants and to control the maintenance of networks and the risks of supplying energy on the network following environmental and/or technical hazards. At the heart of GAP is a simulation model of generation scenarios, calculating the technical and economic results of different hypotheses of expansion of the generation system. Various scenarios can be studied and compared in order to identify the most technically and financially optimized options. This tool provides a detailed analysis of technical and economic results and indicators of strategy development.
|https://www.ied-sa.com/en/products/planning/gap-gb.html||$9000-14000||https://cdn.leap.sei.org/ToolImages/gap2.jpg||Generation Analysis and Planningemail@example.com||https://www.ied-sa.com/en/|
|60||DAP||IED||Analyse and forecast the energy demand: software to forecast both the energy demand and the peak load and to prepare demand side management actions (DSM)||Windows||Optimization||
DAP is a software tool designed both to forecast the demand and the peak load, and to prepare actions of Demand Side Management (DSM). DAP has four methods: Simple Trend Forecast, Sector Trend Forecast, Customer Trend Forecast, DSM Forecast.
|https://www.ied-sa.com/en/products/planning/dap-gb.html||$5500-$8000||https://cdn.leap.sei.org/ToolImages/dap4.jpg||Demand Analysis and Planningfirstname.lastname@example.org||https://www.ied-sa.com/en/|
|61||GEOSIM||IED||Geospatial rural electrification planning software for grid extension , mini grids (hydro, biomass, solar, hybrid PV/Wind) and distributed energy planning||Windows||Optimization||
GEOSIM is a GIS based software designed for creating interactive rural electrification planning scenarios. Based on rural electrification planning experiences in several countries, GEOSIM is used by a number of organizations, consulting companies and public institutions in Asia and Africa. It has four main modules: Spatial Analyst, Demand Analyst, Network Options and Distributed Energy
|https://www.ied-sa.com/en/products/planning/geosim-gb.html||$3000-$12000||https://cdn.leap.sei.org/ToolImages/geosim.jpg||Geospatial Rural Electrification Planningemail@example.com||https://www.ied-sa.com/en/|
|62||GACMO||UNEP DTU Partnership||Detailed Accounting for Apx. 100 Mitigation Options as an Abatement Revenue Curve||Excel||Accounting||
GACMO is a spreadsheet-based accounting model that can be used to calculate and track the GHG reduction and economic costs and benefits of about 100 climate mitigation actions across a range of sectors including agriculture, biomass energy, energy efficiency, forestry, geothermal, hydro, solar, wind. Aside from demonstrating detailed and transparent calculations for many different mitigation options, GACMO also contains a wealth of well-sourced default data for many options.
GACMO is useful for Monitoring Reporting and Verification (MRV) and can help to ensure transparency in climate change mitigation actions. GACMO has been widely applied including in Afghanistan, Angola, Antigua and Barbuda, Eritrea, Ghana, Guinea Bissau, Lesotho, Macedonia, Mozambique, North Korea, Sao Tome and Principe, Swaziland, The Maldives, Zambia, Zimbabwe.
The outcome of using GACMO is a table providing an overview of the the cost and abatement potential of different mitigation initiatives, in the form of an Abatement Revenue Curve.
GACMO is pronounced "GAS MO".
|https://unepdtu.org/publications/the-greenhouse-gas-abatement-cost-model-gacmo/||Free||https://cdn.leap.sei.org/ToolImages/gacmo.png||The Greenhouse Gas Abatement Cost Modelfirstname.lastname@example.org||https://unepdtu.org/publications/the-greenhouse-gas-abatement-cost-model-gacmo/|
|63||REexplorer||NREL||RE Explorer provides renewable energy data, analytical tools, and technical assistance to developers, policymakers, and decision makers in developing countries.||Web||GIS/Accounting/Database||
RE Explorer provides renewable energy data, analytical tools, and technical assistance to developers, policymakers, and decision makers in developing countries. RE Explorer enables users to make meaningful decisions that support low-emission development and ultimately reduce greenhouse gas emissions.
The RE Data Explorer is a user-friendly geospatial analysis tool for analyzing renewable energy potential and informing decisions. Developed by the National Renewable Energy Laboratory (NREL) and supported by the U.S. Agency for International Development (USAID), RE Data Explorer performs visualization and analysis of renewable energy potential that can be customized for different scenarios. RE Data Explorer can support prospecting, integrated planning, policymaking, and other decision-making activities to accelerate renewable energy deployment. Capabilities include:
|https://www.re-explorer.org/||Free||https://cdn.leap.sei.org/ToolImages/reexplorer.png||Renewable Energy (RE) Data Explorer,||https://www.nrel.gov/|
|64||PROSPECTS+||New Climate Institute||PROSPECTS+ tracks and projects sectoral GHG emissions trends. Covers all emissions-generating sectors: electricity, heat, buildings, transport, various industrial sectors, waste, and agriculture.||Excel||Accounting||
PROSPECTS+ is a sector-level, bottom-up Excel tool which uses decarbonisation relevant activity and intensity indicators to track and project overall and sectoral GHG emissions trends. PROSPECTS+ covers major emitting sectors: electricity, heat, buildings, transport, various industrial sectors, waste, and agriculture.
Users can construct their own emissions scenarios by adjusting policy-relevant indicators in each sector and the tool provides a dashboard of critical indicators to analyse emissions across time under a range of pathways. PROSPECTS+ can also be used to aggregate outputs from more detailed sectoral modelling efforts or policy analysis. The tool is developed in Excel, making it transparent, user-friendly, and accessible to a wider range of users.
|65||FlexTool||IRENA||An energy system planning tool for analyzing the flexibility of power systems operating with variable power generation.||Excel/GLPK (Windows)||Optimization||
Countries exploring ways to ramp up solar and wind energy on their power grids need to conduct through flexibility assessments. The IRENA FlexTool performs power system flexibility assessments based on national capacity investment plans and forecasts.
FlexTool assessments reflect full power system dispatch and offer a detailed view of flexible generation options, demand flexibility and energy storage, along with sector-coupling technologies like power-to-heat, electric vehicles and hydrogen production through electrolysis.
FlexTool can analyze system operations using a time resolution of an hour or less in the case of variable renewable energy (VRE) sources. It also provides least-cost optimization of the generation mix along with flexibility solutions for grids, storage, demand-side response and sector coupling.
The inputs required for a FlexTool simulation include demand, the generation mix, hydrological data, VRE time series, interconnections and fuel costs. Transmission data can be divided into separate nodes to reflect real-word power system characteristics.
|66||MedPro||ENERDATA||Bottom-up model for long-term energy demand, load curve and greenhouse gas forecasts||Windows||Accounting||
MedPro belongs to the MEDEE models family: it is a bottom-up demand forecasting model that enables users to assess the impact of energy efficiency policies at country-level. MedPro has been used in more than 60 countries, both by public bodies or companies.
It simulates energy demand by type and end-use according to various energy efficiency scenarios, and calculates future energy demand and related CO2 and GHG emissions using the optional MedPro Environment version. It can also be used to develop electricity load forecasts.
MedPro addresses energy demand by main sector (industry, households, service, transport, etc.) and main categories (end-use/appliances/vehicle type). The bottom-up approach enables to assess energy demand use per use, and analyze the impact of different policies thanks to different scenarios and potential sensibility studies.This model is highly flexible and can be easily adapted, depending on objectives and data availability.
|67||EPRI Load Shape Library||EPRI||A load data repository developed EPRI with guidance from U.S. utilities.||Web-based database||Database||
The objective of the Load Shape Library is to facilitate the collection, use and functionality of a library of representative electric load shapes by climate zone, geography or by utility in the USA.
Representative load shapes are a challenge to acquire due to the cost to collect end use level load data. While EPRI and the utility membership work towards acquiring national and regional statistically representative load data, the Load Shape Library serves to provide best-available U.S. end-use load data. The databases in the Load Shape Library include electric end-use data aggregated over NERC regions, whole premise electric data by U.S city, residential efficient electric technology measures end-use load data from the Pacific Northwest and EPRI’s Smart Breaker Project.
EPRI continues to revise and update the platform annually and populate the library with newer load data as available.
|https://loadshape.epri.com/||Free||https://cdn.leap.sei.org/ToolImages/epriloadshapelib.jpeg||EPRI Load Shape Libraryemail@example.com||https://www.epri.com/|
|68||NEMO||SEI||Energy system optimization using LP. Works with multiple solvers. Closely integrated with LEAP.||Windows 64-bit/Julia/Integrated within LEAP||Optimization||
NEMO, the Next Energy Modeling system for Optimization, is a high-performance, open-source energy system optimization tool developed by the Stockholm Environment Institute. It is intended for modelers who seek substantial optimization capabilities without the financial burden of proprietary software or the performance bottlenecks of common open-source alternatives. NEMO is designed to analyze critical questions in contemporary energy policy from the grid integration of variable renewable energy to the role of energy storage, robust planning responses to climate change, and more. It is a full energy system optimization tool that can be run from a command line or with LEAP as a user interface. The combination of LEAP and NEMO puts powerful optimization features within reach of planners, energy analysts, and others who are not full-time modelers. NEMO is used for capacity expansion and power development planning, energy strategies, energy-water-food nexus analyses, and deep decarbonization studies.
Key features of NEMO include:
|https://github.com/sei-international/NemoMod.jl||Free/Open Source||https://cdn.leap.sei.org/ToolImages/nemo.png||Next Energy Modeling system for Optimizationfirstname.lastname@example.org||https://github.com/sei-international/NemoMod.jl|
|69||IBC||SEI||Calculates Health, Ecosystem and Climate Impacts Associated with LEAP Emissions Scenarios. Closely Integrated with LEAP.||Windows/LEAP||Reduced Form atmospheric/geochemistry model combiend with relative risk functions for diseases and other impacts functions.||
IBC can be used to calculate estimates of air pollution-associated health (premature mortality), ecosystem (crop yield loss) and climate (global temperature change) impacts. It is particularly useful for examining the co-benefits of taking action on long-lived and short-lived climate pollutants (SLCPs) and local air pollutants.
IBC uses parameterized results from the global atmospheric geochemistry model GEOS-Chem Adjoint, which are applied to the emission estimates developed in LEAP, in order to calculate population-weighted concentrations of fine particulate matter (PM2.5) and ground-level ozone (O3). These concentrations are then combined with standard concentration-response functions to estimate premature mortality associated with PM2.5 and ozone exposure and crop yield losses associated with ozone exposure. Results can be viewed by geographic source (in-country, natural background and rest of the world), by the contribution of emissions of different pollutants to the impact (e.g. the contribution of NOx, black carbon, organic carbon, etc.), by age group (for premature mortality), gender, or by crop type (for crop losses, currently rice, wheat, maize and soy). Health impact functions are based on the standard dose-response functions used in the Global Burden of Disease Study (Burnett et al., 2014). GEOS-Chem Adjoint is a global 3-D chemical transport model for atmospheric composition driven by meteorological input from the Goddard Earth Observing System (GEOS) of NASA and is based on emissions inventories from the EDGAR database. The overall modeling pathway is illustrated here.
IBC is particularly notable for making a complex and highly computing-intensive modeling methodology accessible to planners in the developing world. By first parameterizing the calculations of GEOS-Chem Adjoint (which can take a few days to perform per country, even on super computers), the calculations in LEAP can then be run in just a few seconds. Moreover, LEAP is used for all data management and results visualization, making it readily usable by developing country planners. Previously, such analyses could only be done by highly experienced modelers working in large international institutions.
IBC has been developed in a collaboration between SEI, the US-EPA, and researchers at the University of Colorado. The work has been supported by UNEP and the Climate and Clean Air Coalition (CCAC).
|https://leap.sei.org/default.asp?action=IBC||Integrated within LEAP||https://cdn.leap.sei.org/ToolImages/ibc.jpg||The Integrated Benefits Calculatoremail@example.com||https://www.sei.org|
|70||MoFuSS||UNAM and SEI||GIS-based model that simulates the spatio-temporal impacts of woodfuel harvesting over dynamic landscapes, while accounting for savings in non-renewable woody biomass from reduced consumption.||Web-based/linux/windows||Geospatial analysis and modeling||
MoFuSS was designed to help clean cooking projects estimate the fraction of non-renewable biomass (fNRB) using a sound methodology that integrates most of the complexities associated with woody biomass harvest patterns and natural regrowth. In the aim of not cutting corners, MoFuSS evolved into a complex GIS modeling tool that integrates various drivers of land change, woodfuel demand sources, and end-user technologies.
MoFuSS is an open-source freeware developed by the National Autonomous University of Mexico and the Stockholm Environment Institute. It is a GIS-based model that simulates the spatio-temporal impacts of woodfuel harvesting over dynamic landscapes, while accounting for savings in non-renewable woody biomass from reduced consumption.
|https://www.mofuss.unam.mx/||Free/Open Source||https://cdn.leap.sei.org/ToolImages/MofussLg.jpg||Modeling Fuelwood Savings Scenariosfirstname.lastname@example.org||https://www.mofuss.unam.mx/|
|71||SICA-Bioenergy||Adrian Ghilardi||Shows solid biofuels potential in Central American for any area of interest.||Web||Geospatial modeling and optimization||
SICA-Bioenergy: The Geospatial System for the Evaluation of the Energy Potential of the Biomass Resources of the Central American Integration, is used to show the bioenergy potential in Central American countries (SICA) plus Haiti. The project has been commissioned by the Economic Commission for Latin America and the Caribbean (ECLAC) with the goal of providing advice at the country level.
An improved version for Mexico, that also accounts for harvest to transportation costs, is available here.
|72||MEPSY||CLASP||Appliance and equipment climate impact calculations||Web||Bottom-up accounting calculations based on stock, sales, and energy performance data from in-country market studies, or country-level estimates.||
Mepsy is CLASP's digital tool to model the impacts of energy and carbon reduction policies. Pre-loaded with data from 162 countries, it supports analysis and prioritization for the most energy-intensive appliances and equipment including space heating, air conditioning, refrigeration, motors and lighting.
Mepsy's interface guides researchers and policymakers in identifying efficiency policy opportunities and analyzing their energy and carbon impacts.
Results can be downloaded as a CSV files for further use.
Mepsy calculates product energy use according to a bottom-up accounting approach which factors in the number of appliances in use in a country, the energy performance of representative products, the climate-intensity of the local power grid, and other variables to analyze the electricity use, carbon dioxide emissions, and consumer energy costs associated with a given policy scenario.
Bottom-up accounting calculations are based on stock, sales, and energy performance data from in-country market studies, or country-level estimates. Where country-level data for a particular product are not available, calculations are based on estimates from regional or global averages, accounting for differences in country population, economics, or climate as relevant to a particular appliance. Future and past shipments are extrapolated based on recent trends.
|73||CRANE||Prime Coalition and Rho Impact||Measures emissions reduction potential of different technologies.||Web||Accounting||
CRANE is an open-access software tool that measures emissions reduction potential for early-stage companies.
Its calculations, are based on the Climate Impact Assessment Report written by Prime Coalition and NYSERDA. Additionally, for each Technology Model, users can review the Calculation References tab, which provides step-by-step calculations.
CRANE provides an estimate of the potential emissions reductions of different technologies, i.e. what is the scale and range of potential impact in real physical terms, and given a set of assumptions and preconditions
|https://cranetool.org/||Free/Open Access||https://cdn.leap.sei.org/ToolImages/crane2.jpg||Carbon Reduction Assessment: New Enterprisesemail@example.com|
|74||FABLE||FABLE Consortium||Computes mid-century pathways of the food and land-use systems, and tracks progress towards food security, climate mitigation, and biodiversity conservation.||Excel||Accounting based on three main steps: human food consumption, livestock production and crop production.||
The FABLE Calculator focuses on agriculture as the main driver of land-use change. It represents 88 agricultural raw and processed products from the crop and livestock sectors. For each of these products, the model reports the food, feed, other non-food consumption, losses and waste, imports and exports, and production quantities, and related land and water use for each five years from 2000 to 2050.
The main result indicators are the daily calorie consumption per capita, total and by food group; GHG emissions from agriculture and land use change; and land where natural processes predominate as a proxy for biodiversity.
|https://fableconsortium.org/tools/fablecalculators/||Free||https://cdn.leap.sei.org/ToolImages/fable.png||Food, Agriculture, Biodiversity, Land-Use, and Energyfirstname.lastname@example.org||https://fableconsortium.org/|