CO2DB is a database containing detailed data on carbon mitigation technologies. The database currently contains approximately 3000 technologies, including detailed technical, economic and environmental characteristics as well as data on innovation, commercialization and diffusion.

Users can add to, select, filter, arrange, and compare CO2DB’s data according to any of the technology characteristics included in each database entry.Users can also make energy chain calculations as well as comparison tables and graphics on the technology and the chain level. IIASA disseminates CO2DB free of charge so that it can be useful to researchers in their individual studies.

In return, they request that users share the data they enter into the database

Compose (Free)

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 in sustainable energy.COMPOSE provides a rapid and powerful basis for comparative energy systems analyses that are consistent with the micro-economic reality of operational scheduling.

EMCAS (contact EMCAS software distributor)

The Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) has been developing EMCAS, the Electricity Market Complex Adaptive System model, in which the diverse participants in the electricity market are represented as “agents.”R

EMCAS Design: An EMCAS simulation runs over six decision levels, ranging from hourly dispatching to long-term planning (see figure above). At each decision level, agents make certain decisions, including determining electricity consumption (customer agents), unit commitment (generation companies), bilateral contracting (generation and demand companies), and unit dispatch (ISO/RTO agent). Agents then apply their own decision rules and evaluate how well these rules meet their objectives.R

EFFECT
(register And download the EFFECT 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.

Energy Costing Tool

In recognition of the critical role that energy plays in reaching the MDGs, UNDP’s Sustainable Energy Programme has developed a set of tools for helping mainstream energy considerations into MDG-based national development strategies.  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. Results of such an assessment can form the basis for developing country-specific strategies to meet the MDGs by 2015.  Moreover, it provides a framework for the transparent budgeting of public expenditures to meet the MDGs.

ENPEP_BALANCE (send an email if you want the latest version)
ENPEP-BALANCE allows users to evaluate the entire energy system (supply and demand sides) and the environmental implications of different energy strategies.

EnergyPLAN

 GEMIS
(Global Emissions Model for integrated Systems) (Download free)
GEMIS performs full life-cycle computations for a variety of fuel chains, calculating emissions, resource use and costs.  The GEMIS database offers information on fuel chains as well as on different technologies.
GEMIS consists of an analysis model to determine energy and material flows (including transports), and a database

 GTMax

The GTMax model helps researchers study complex marketing and system operational issues. With the aid of this comprehensive model, utility operators and managers can maximize the value of the electric system, taking into account not only its limited energy and transmission resources, but also firm contracts, independent power producer (IPP) agreements, and bulk power transaction opportunities on the spot market.
GTMax maximizes net revenues of power systems by finding a solution that increases income while keeping expenses at a minimum. At the same time, the model ensures that market transactions and system operations remain within the physical and institutional limitations of the power system. When multiple systems are simulated, GTMax identifies utilities that can successfully compete in the market by tracking hourly energy transactions, costs, and revenues

HOMER
HOMER Energy Modeling Software
(free for 2 weeks at no cost)
HOMER simplifies the task of evaluating design options for both off-grid and grid-connected power systems for remote, stand-alone, and distributed generation (DG) applications. HOMER’s optimization and sensitivity analysis algorithms can be used to evaluate the economic and technical feasibility of a large number of technology options and to account for variation in technology costs and energy resource availability.HOMER models a wide range of conventional and renewable energy technologies.  Power sources that can be modeled include: solar photovoltaics (PV), wind turbines, run-of-river hydro power, diesel, gasoline, biogas, alternative, co-fired and custom-fueled generators, electric utility grids, microturbines, and fuel cells.  Storage options include: battery banks and hydrogen.

 LEAP
(Licensed users are given a user name and registration)
LEAP, the Long range Energy Alternatives Planning System, is a widely-used software tool for energy policy analysis and climate change mitigation assessment developed at the Stockholm Environment Institute

 MAC Tool 
(MACTool is not available)

The Marginal Abatement Cost Tool (MACTool) provides an easy way to build marginal abatement cost curves and for calculating break-even carbon prices. Its user-friendly interface guides users through a simple data entry process, which generates marginal abatement cost curves. A fully functional version of MACTool is not available. MACTool is undergoing extensive testing. However, the tool can be made available in its Beta version which can be used to further explore the tool for its current capabilities.

MARKAL/TIMES

  MARKAL/TIMES are general purpose model generators tailored by the input data to represent the evolution over a period of usually 20 to 50 or 100 years, of a specific energy-environment system at the global, multi-regional, national, state/province, or community level. Each annual load duration curve, hence each annual variable can be detailed by as many as desired time slices, which is user-defined at three levels: seasonal (or monthly), week days – weekends, and hour of the day. The entire energy system can be modelled and it is represented as a network, depicting all possible flows of energy (usually as many as reported by the detailed energy balances) from resource extraction, through energy transformation and end-use devices, to demand for useful energy services – as many as desired, in the desired units. For instance the demand for space heating can be specified by as many as desired categories such as single or multifamily, urban or rural, existing or new, etc., and in the desired units such as PJ, number of households, m2 or m3. Each link in the network is characterized by a set of technical characteristics (e.g., capacity in place, availability factors, efficiency), environmental emission coefficients (e.g., CO2, SOx, NOx), and economic factors (e.g., capital and costs). All thermal, renewable, storage and conversion and transportation technologies can be simulated by the model. Many different energy networks or Reference Energy Systems (RES) are feasible for each time period. MARKAL/TIMES finds the “best” RES for each time period by selecting the set of options that minimizes total discounted system cost or the total discounted surplus over the entire planning horizon, within the limits of all imposed policy and physical constraints

Mesap
(Modular Energy System Analysis and Planning Environment) is an energy-system analysis toolbox, and PlaNet (Planning Network) is a linear network module for Mesap that is designed to analyse and simulate energy demand, supply, costs and environmental impacts for local, regional and global energy-systems. It was originally developed by the Institute for Energy Economics and the Rational Use of Energy (IER) at the University of Stuttgart in 1997 [1-3] but it is now maintained by the German company Seven2one Informationssysteme GmbH [4]. In total 15 versions of Mesap PlaNet have been released and it has approximately 20 users. To purchase the model costs at least €۶,۸۰۰ but there is a 30% discount for research groups, and it takes 2 days of training to learn how to use the model, which is not contained in the price and is also not mandatory.

Mesap PlaNet calculates energy and emission balances for any kind of reference energy systems (RES). A detailed cost calculation determines the specific production cost of all commodities in the RES based on the annuity of investment cost and the fixed and variable O&M cost. The model uses a technology-oriented modelling approach where several competitive technologies that supply energy services are represented by parallel processes. All thermal generation, renewable, storage and conversion, and transport technologies are considered in the simulation. The simulation is carried out in a user-specified time-step which ranges from one minute to multiple years, and the total time-period is unlimited.

 
MESSAGE-Access

The MESSAGE-Access model is a dynamic linear optimization model developed at IIASA. It is being used to assess to achieve universal access to modern energy by 2030 by accelerating the transition to clean cooking fuels and rural electrification in the regions of South Asia, Pacific Asia, and sub-Saharan Africa.

 MESSAGE-MACRO

MESSAGE–MACRO is the result of linking a macroeconomic model with a detailed energy supply model. The purpose of the linkage is to consistently reflect the influence of energy supply costs as calculated by the energy supply model in the optimal mix of production factors included in the macroeconomic model. In this article, we describe an automated link of two independently running models. The advantages of this setup over a single, fully integrated model are twofold: First, it is more flexible, leaving the constituent models intact for independent runs, thus making further model development an easier task. Second, the decomposed model solution benefits numerically from having the most non-linearities concentrated in the smaller of the two modules. The emphasis of the paper is on methodology, but we also include an example demonstrating the feedback mechanisms of MESSAGE–MACRO by applying it to two global economic–energy–environment scenarios.The two scenarios are a reference scenario and a scenario that limits the global atmospheric carbon concentration to 550 ppmv.

OSeMOSYS

  RESTScreen

   TRNSYS

TRACE

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.

WASP

The WASP (Wien Automatic System Planning Package) model permits the user to find an optimal expansion plan for a power generating system over a long period and within the constraints defined by the planner, which is maintained by the IAEA (International Atomic Energy Agency) [1]. So far four versions of WASP have been created which has been distributed to several hundred users. The model is freely available to IAEA member states and requires 4 to 6 weeks of training. There is support forum specifically for WASP at [2].R In WASP the optimum expansion plan is defined in terms of minimum discounted total costs. Each possible sequence of power plants that could be added to the system (expansion plan or expansion policy) and that meets the selected constraints, is evaluated by means of a cost function composed of: capital investment costs, fuel costs, operation and maintenance costs, fuel inventory costs, salvage value of investments and cost of energy demand not served.RWASP has previously been used to evaluate the potential of biomass power generation [3], to examine the future role of nuclear power in Korean [4], and to identify the least cost expansion plan for Thailand in order to evaluate its future dependence on natural gas [5].

WEAP

windPRO