Commercial Energy Management Systems with MATLAB, Simulink, and Simscape
Design, model, and simulate energy management systems for data centers, factories, and buildings
With MATLAB and Simulink, you can combine real-world data and simulation models to study and optimize the behavior of complex electrical loads and cooling systems. Develop closed-loop and supervisory energy management systems used in commercial buildings, factories, AI data centers, and fuel cells.
As part of the KOICA-led project and Moroccan Green Technology Research and Development Comprehensive Support Project, we designed and built the entire system configuration of a 300 kW microgrid testbench and built a Model-Based Design SCADA so that local researchers could utilize it.
Modeling and Simulating the Impact of Data Center Energy Needs
MATLAB, Simulink, and Simscape products help engineers model the energy needs of data centers driven by the growth of AI and cloud computing. For hyperscalers, MATLAB and Simscape Electrical, enable them to predict the demand for the gigawatts of power required by the intense compute resources, understand the impact of this complex, variable load on the connected distribution system, and determine how best to cool the data center resources. For the local utilities, Simscape Electrical helps them understand how local power grids must be upgraded to account for the unpredictable loads that cause frequency and voltage fluctuations, as well as introduce unwanted grid harmonics.
Modeling Data Center Power Consumption
You can use MATLAB, Simulink, and Simscape products to model and simulate electricity used by the high performance TPUs and GPUs in the rack servers and calculate the heat generated by systems in the data center or the entire data center and plan for the needed cooling and cooling system power consumption during operation.
Featured Examples
Analyzing the Impact of Data Centers on Power Grid
You can use MATLAB, Simulink, and Simscape Electrical to model and simulate the strain that hyperscale data centers place on local distribution systems by analyzing the steady-state and transient electrical behavior of data centers. With Simscape Electrical, you can model the data center, along with other loads and generators on the grid at different levels of fidelity to perform analyses ranging from long-term power needs to short-term transient upsets caused by the 1000s of power converters that introduce harmonics and reduce the power, affecting homes and businesses that share the power grid. Simscape Electrical lets you add noninvasive faults to the model, helping you better understand the grid’s resilience to unanticipated outages.
Featured Examples
Developing Building Energy Management Systems
With MATLAB and Simulink, you can design smart and efficient building energy management systems (EMS) by implementing dynamic policies, incorporating real-time data, and increasing the level of automation in EMS operations. You can use MATLAB and Simulink for your EMS development workflow, from data access and modeling to optimization and deployment.
- Create forecasting models on electricity demand and generation, electricity price, and weather conditions
- Model, simulate, and design optimal EMS control strategies for scheduling power systems and HVAC systems operations
- Generate code for supervisory controls on edge devices and deploy to embedded controllers
- Deploy operations optimization software to production cloud environments
Building EMS Energy Forecasting
With MATLAB and Simulink, you can perform data-driven forecasts on environmental and techno-economic factors to optimize operations of your building energy management system.
- Access time-series data from files or databases
- Perform data preprocessing, analysis, and visualization in MATLAB with interactive apps and workflow automations
- Choose from prebuilt statistical, econometric, or machine learning and deep learning models
- Train forecasting models in parallel and evaluate model performance
- Directly integrate the trained energy forecasting model in Simulink for simulation with the physical system model
Featured Examples
Building EMS Modeling, Simulation, and Optimization
You can use MATLAB and Simulink as a design environment for electrical system modeling, EMS control design, and EMS optimization.
- Create physics-based models of the building’s electrical system using Power Systems Simulation Onramp and run performance simulations
- Design control strategies, such as Model Predictive Control (MPC), and Reinforcement Learning, for the EMS
- Formulate the optimization problem and solve for optimal system configurations using Optimization Toolbox
- Simulate system-level behavior with different scenarios
- Analyze the techno-economic impact of different system designs
Featured Examples
Building EMS Validation and Deployment
You can validate your building EMS design by generating code from your system model, which lets you move quickly from desktop simulation to real-time simulation. You can deploy controls to the edge and operational management systems to the cloud.
- Generate readable, efficient C/C++ code from the controller model in Simulink for deployment on an embedded processor
- Generate C code for the plant for deployment on a real-time machine
- Run hardware-in-the-loop (HIL) simulations to validate the building energy management strategies against the electrical system
- Deploy supervisory control algorithms on edge devices
- Deploy operations optimization algorithms based on MATLAB to cloud environments using MATLAB Web App Server and MATLAB Production Server
Modeling and Simulating PEM Fuel Cell Systems
With MATLAB, Simulink, and Simscape Electrical, you can:
- Model fuel cells and hydrogen electrolyzers
- Develop fuel cell system architectures
- Implement control systems
- Integrate fuel cells and electrolyzers into larger electrical systems
Modeling PEM Fuel Cells
Simulink and Simscape enable you to model and simulate fuel cells and electrolyzer systems using a physics-based approach with ready-made library components or a data-driven approach with modeling tools.
- Explore different configurations for fuel cell stacks and electrolyzers
- Model multidomain physics effects and balance-of-plant components for regulating hydrogen gas and air flow, water transport, and heat generation
- Assess electrothermal behaviors to support electrical system and thermal management system design
Featured Examples
Implementing Fuel Cell Controls
Control systems play a significant role in ensuring the safe, durable, and efficient operations of fuel cell systems. With Simulink and Simscape, you can rapidly prototype control design and generate code for hardware-in-the-loop (HIL) testing and deployment.
- Design electro-thermal control algorithms for current and voltage regulation, humidity regulation, pressure management, water management, and thermal management
- Generate readable, optimized C/C++ or HDL control code for fuel cell models
- Generate code for the plant model
- Perform real-time HIL testing to avoid costly damage to the fuel cell hardware prototype
- Deploy control code to embedded processors or FPGA/SOC devices
Fuel cell systems need to be reliable and efficient. We accomplish this by using MathWorks tools to rapidly develop and simulate our control algorithms before trying them on a system. We don't have time to investigate our algorithms with C or C++. Fortunately, MATLAB lets us test our ideas with just a few lines of code. It saves a lot of time and moves us toward our goal of creating a commercially viable onsite energy system.
Featured Examples
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