Single database
All models work on a single database; the data adapts itself to the time configuration the user defines.
AMEBA
Analysis & Modeling
Energy systems analysis platform
Detailed, comprehensive analysis of energy markets — from the decades-long expansion plan to the hourly operation of highly decarbonized systems.
The platform
One place for the whole power system analysis
AMEBA brings together mathematical models for different challenges in the energy sector, all on a single database: internally, the data adapts to the time configuration the user defines.
Users define the horizon and the granularity of the solution, and run simulations from any computer — no installation, no limit on parallelism.
4
models on a single database
Hourly
resolution over annual horizons
Cloud
parallel simulations, no limit
0
installs: everything in the browser
Capabilities
What makes AMEBA different
AMEBA's capabilities make the platform useful across many areas of the energy sector.
Multiple modules
A range of mathematical models for different challenges in the energy sector.
Flexibility
Users define the study horizon and the granularity of the solution.
Uncertainty
Uncertainty at several levels: hydrology, demand, fuel prices, line capacity.
Web-oriented
Simulations run and display from any computer, with hassle-free updates.
Visualization
Easy-to-use interface. Every module includes an interactive results summary.
Compute-intensive
Cloud computing, no limit on parallel simulations. Faster analysis.
Model extension
Creating and extending models is easy, and predefined formulations can be inherited.
Agile development
Agile development, with constant updates driven by what our clients need.
Who uses AMEBA
ConsultantsGeneration companiesGrid operatorsRegulatorsNational Energy CommissionPrice forecasting agenciesTrade associationsUniversities and research centres
Horizons
A model for every time scale
The four modules span from the intraday operation of a single plant to a decades-long expansion plan, and chain together to gain granularity.
HoursDaysWeeksMonthsYears
MaxHidro
River basin operationShort-term planningHydrothermal coordinationExpansion planning
Click a bar to jump to that module
Uncertainty at multiple levels
Scenarios combine inflows, wind and solar generation, demand and fuel prices. The tree is configured per stage: branches open at different points of the horizon.
Modules
The four models inside AMEBA
Each module answers a different question, on the same database and through the same interface.
Generation & Transmission planning
INVX
Determines the system's optimal investment plan.
It serves both tariff studies and forward-looking projections of how the generation mix will evolve, and targets planners in centralized decision-making, regulators seeking efficient energy policy and investors in competitive markets.
You control simulation precision through intuitive characterization tools. It supports stochastic problems for robust decisions under hydrological uncertainty, demand variations and fuel prices, and solves with MIP techniques or Benders decomposition.
Used by Chile's Ministry of Energy in its Long-Term Energy Planning process between 2018 and 2025.
Summary
- Generation costs
- 1,529.0MMUSD
- Start/stop costs
- 0.21MMUSD
- Generation investment
- 13,860.0MMUSD
- Transmission investment
- 23.05MMUSD
- CO₂ tax costs
- 39.31MMUSD
- Unserved energy cost
- 39.08MMUSD
- Total costs
- 15,500.0MMUSD
- Average expansion cost
- 4.44USD/MWh
- CO₂ emissions
- 8.22MMTon
- CO₂ system factor
- 0.021TonCO₂/MWh
Candidate technologies
- Thermal plants
- Hydro plants (on river networks)
- Wind, photovoltaic and CSP plants
- Storage systems
- Up-powering at reservoir plants
Modelling
- Investment and operating costs vary over time
- Generation projects can be sized (integer or continuous)
- Forced projects can be included
- AC and/or DC candidate transmission lines
It is also possible to represent
- Fuel availability constraints
- Capacity payments or CO₂ emission charges
- Separate definition of 'policy' and 'hydrological' scenarios
- Renewable energy targets (quota system)
- Environmental constraints
Hydrothermal Coordination
CHT
Finds the least-cost operating policy for the hydrothermal system.
It respects the operational constraints of both the power system and the river basins, and also computes economic indicators: the price of dispatched energy at each bus and the value of water.
The reservoir model includes spills and seepage, which removes spillage penalties and fictitious inflows. It allows multiple water paths and turbine-by-turbine detail.
Element parameters
- Hydro type
- Turbinated
- Max Q flow
- 120m³/s
- Min flow
- 8m³/s
- Delay
- 45min
- HC penalty
- 0USD/m³/s
Key features
- Derives the water usage policy (target reservoir volumes) or future cost functions
- Load duration curve and stage-block structure for short-term demand variation
- Stage-block structure for correct peak-shaping at reservoir plants
- Day/night block separation
- Flexible implementation with no maximum number of stages or blocks
Also
- Numerically stable model
- Flexible horizon, combining hydrological scenarios with other stochastic variables (fuels, renewables, demand)
- Chaining of the long-/medium-term solution with a short-term model to gain granularity
- Pumping can be included
Decomposition algorithms
CHT is a large-scale multi-stage stochastic problem: it has to be split into subproblems whose solutions are then coordinated. In AMEBA you choose between two algorithms:
SDDP
Classic parallel decomposition: it uses as many CPUs as the problem has scenarios, also to formulate, process data and write results. It includes several ways of modeling reduced uncertainty (snowmelt) and future cost functions.
Progressive Hedging
Brings short-term aspects — technical minimums, minimum operating times, spinning reserves — into the strategic use of water. It represents non-convexities SDDP does not cover: varying efficiencies, piecewise concave functions and binary irrigation rules.
Short-term planning
UC
Determines the short-term operation of the hydrothermal system, hour by hour.
It targets detailed studies of price signals and operational aspects: operating constraints, line usage, reserve allocation. It characterizes the generation fleet and the river basin networks in detail.
Through rolling planning, it characterizes operation at hourly resolution over annual horizons in a matter of hours.
Formulation features
- Mixed-integer, multi-reservoir, multi-stage and multi-nodal model
- Minimum and maximum output levels
- Spinning reserve (primary-secondary) and standing reserve for different control areas
- Minimum up and down times
- Start-up and shut-down costs; ramp-up and ramp-down rates
- Fuel availability constraints
- Ability to co-optimize energy and reserve markets
Technologies represented
- Conventional thermal units
- Natural gas combined cycles (2+1, 3+1)
- Storage systems and pumped-storage plants
- CSP
- Renewables: wind, photovoltaic and others
Flexibility and efficiency
- The stochastic model does not formulate non-anticipativity: faster solutions
- Relaxation of unit commitment for faster convergence
- Constraints can easily be enabled or disabled in the formulation
Short-term operation support tool
MaxHidro
Guides operator decisions so that peak-shaping is optimized.
The operator of a plant within a river basin network tends to decide conservatively and cannot exploit the plants' flexibility to maximize revenue. The solution guides those decisions so peak-shaping is optimized during operation.
Benefits
- Higher revenues and increased energy sales
- More efficient process and operational simplicity
- Better use of water resources
- Dispatch guidance for plant operators
Formulation features
- Price-taker model
- Hydraulic network in detail: time delays, environmental flow, irrigation returns and water hammer
- Complex topologies (canals, extractions and others)
- Represents the efficiency curve of each turbine
- Unit commitment constraints
In the cloud
AMEBA in your browser: anywhere!
Use AMEBA from your browser, on any device, anywhere. Cloud servers allow more detailed studies and more scenarios, in less time and at lower cost.
The case manager organizes simulations, simplifies comparison between studies and records the latest changes in a shared log.
Case managerStudy comparisonChange logSimulation queue
- Projects
- Tariff study
- Expansion plan
- Base scenario
- Wet hydrology
- Dry hydrology
- Weekly operation
- Southern basin
Base scenario 2025-2050Optimal
Generators1,240
Busbars312
Loads268
Branches496
Reservoirs21
Simulation info
- Model
- Unit commitment
- Algorithm
- SDDP
- Horizon
- 2025-2050
- Solver
- CPLEX
- GAP
- 0.5 %
- Run time
- 00h:24m:48s
Last processes
| 12:28 | upload for cloud analysis | running |
| 01:06 | optimize | finish |
| 18:59 | preprocess | finish |
| 18:17 | generate time configuration | finish |
Immediate access, no installation
Lower update adoption costs for users.
Collaborative
Share case studies and distribute results; it supports mobility and remote work.
Faster onboarding
Continuous updates to the interface and the computation engine, hassle-free.
Use PLP with AMEBA
AMEBA integrates the PLP model used by the National Electrical Coordinator to determine the strategic value of water. Bring your own license and run it with the full platform: interface, cloud computing and results analysis.
More capabilities
And many more features…
We keep adding options to the platform, driven by what our clients ask us to build in.
Advanced visualizations
Display the electrical and river networks, with views by voltage level, generation technology and other criteria.
Free automatic updates
Immediate access, no installation. Interface and computation engine improve continuously.
Team-oriented
Share case studies and distribute results across multiple platforms. It supports mobility and remote work.
Remote supportBulk data uploadMultiple solversAutomated reportsMulti platformRemote access
Plans
A configuration for every team
AMEBA is configured to what each client needs. The cloud server runs simulations on elastic infrastructure, with several configuration options, all prepaid.
Plan S
Clients seeking to improve the operation of their river basin.
- Optimization horizon
- 1-5 days
- Models
- MaxHidro
- Users
- 1 user
- Compute server
- Cloud
Plan M
Companies and consultants with small teams, without their own hardware or licenses for solving optimization problems.
- Optimization horizon
- Weeks - Years
- Models
- MaxHidroUCCHT
- Users
- 1 user
- Compute server
- Cloud
Plan L
Companies and consultants with collaborative teams that may or may not have their own equipment for solving optimization problems.
- Optimization horizon
- Weeks - Years
- Models
- MaxHidroUCCHTINVX
- Users
- More than 2 users
- Compute server
- Cloud or at client premises
It is cost-efficient and scalable: it solves complex problems within tolerable run times, improves compute server availability, avoids external interruptions and increases system security.
Main supported solvers: Gurobi · FICO Xpress · IBM CPLEX · COIN-OR
Cost control
Keep control of your spending!
An interactive platform to transparently track what using AMEBA costs: the actions executed, the cost of each simulation and the running total.
TransparentInteractive and easy to useEnables real-time collaborationMore efficient training
Period costs
- Compute server
- 52%
- Case storage
- 31%
- Solver licenses
- 17%
- Simulations run
- 128
- Compute hours
- 412h
Shall we talk about your case?
Tell us what you need to analyze and we will show you how AMEBA solves it, with a demo on your own data.