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MATLAB and Simulink in the World - Technologies for Clean Energy

To address the world’s needs for clean, reliable energy, engineers develop advanced mathematical models and simulations for evaluating renewable power sources, improving energy transmission and distribution infrastructure, tracking energy markets, and designing energy-efficient products.

Horizon Wind Energy

Making wind energy profitable: forecasting revenue and analyzing risk

Horizon Wind Energy’s risk-forecasting system enables financial analysts to forecast revenue and quantify risk for wind farms across multiple geographic locations. The system factors in historical data, current prices, and forward-looking estimates from expert analysts. MATLAB® algorithms analyze this data to produce monthly price forecasts for the next several years across all Horizon wind-farm sites. Horizon used MATLAB Compiler™ to deploy a version of the system that runs automatically each morning and stores forecast results.

Gas Natural Fenosa

Optimizing energy availability: predicting electricity supply and demand

To determine how best to sell electricity in the wholesale market, Gas Natural Fenosa must accurately predict the next day’s prices and demand as well as the availability of electric power. The company develops optimization and forecasting models that incorporate historical usage patterns, weather forecasts, production costs, and a range of other factors. They use the models to project capacity and demand and optimize their generation asset portfolios. The models also enable the company to rapidly respond to shifting production constraints and requirements, such as European Commission carbon dioxide emission limits.

Plug Power

Advancing alternative energy: developing fuel cell controls

Plug Power develops onsite energy systems based on fuel cells. For optimal performance, the power generation module and reformate processing module are run within strict temperature ranges. Because a change in electric power demand creates a sudden disturbance on the system, control of the entire system is automated. Engineers use MathWorks tools to develop and rapidly test control algorithms. Simulation lets them test multiple sensor configurations for optimal performance and correct errors or inefficiencies before implementing the algorithms on hardware.


Improving energy efficiency: developing a controller for power converters

ABB technologies enable utility companies to improve performance while reducing their environmental impact. The company’s power electronic controller controls high-power rectifiers, frequency converters for microturbines, wind turbines, traction drives, battery energy storage systems, and other power electronic applications. ABB engineers used MATLAB and Simulink® to design algorithms for filtering, current control, grid synchronization, and grid power monitoring, and to calculate power, idle power, and other physical variables. They validated the algorithms by running system simulations in SimPowerSystems™. ANSI C code automatically generated from their Simulink models was used directly in the controller.

Dongfeng Electric Vehicle

Advancing hybrid electric public transport: optimizing battery performance

Dongfeng developed a battery management control system for a hybrid electric city bus that delivers 30% better fuel efficiency than standard city buses while lowering emissions. Engineers modeled, verified, and automatically generated code for the controller. Performing continuous verification and using plant models for closed-loop simulation helped them identify and resolve problems early to meet ISO/TS 16949 quality management guidelines and MISRA® C standards.

General Motors

Optimizing fuel efficiency: developing hybrid powertrain controls

General Motors’ Two-Mode Hybrid powertrain optimizes fuel efficiency for a range of driving conditions, including stop-and-go city driving and steady-state highway driving. A major advance in hybrid technology, the Two-Mode Hybrid combines a conventional engine with two 60 kW electric motors integrated into an automatic transmission. GM used Model-Based Design to develop system models, verify designs using simulation, and generate production code. This approach enabled engineers to explore multiple strategies, accelerate design iterations, and verify the control system before hardware was available. Teams around the world could work on different aspects of the design simultaneously, eliminating integration issues.


Reducing emissions: developing controls for diesel and natural gas engines

Wärtsilä is the world’s first manufacturer to use common rail electronic fuel injection on large combustion engines. The company’s innovative control software reduces emissions, increases performance, and ensures reliability. Working in Simulink, engineers designed and optimized algorithms early in the development process, reducing the number of costly engine tests. Code automatically generated with Real-Time Workshop Embedded Coder™ was more efficient than hand code for RAM, ROM, and execution speed, and 30% smaller. Wärtsilä created a complete component library in Simulink and Stateflow® that became the implementation base for a range of applications, including a speed/load controller.

Published 2010 - 91848v00

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