Distributed energy systems not only make it easier to increase the use of renewable energy sources, they also provide a way to reduce dependence on large, centralized power stations. In order to maximize reliability, power output, and investment returns, these systems must be carefully planned and designed.

Engineers at Shanghai Electric worked with researchers from the Lawrence Berkeley Laboratory at the University of California, Berkeley to develop a distributed energy system planning and design platform that estimates payback periods, cash flows, and internal rates of return based on time-series weather data, energy price trends, available government subsidies, and other factors. Hundreds of users, both inside and outside Shanghai Electric, currently use the platform to identify optimal distributed energy system designs.

In Canada, wind energy has been the largest source of new electricity generation for more than 10 years. Engineers must fully understand how a new wind farm will perform before adding it to the grid. To accurately predict performance, they need to model the control system and power output of a single turbine, the aggregation of dozens of turbines into a wind farm, and the interaction of that wind farm with the larger network.

Engineers at Hydro-Québec built models in Simulink to represent individual turbines as well as entire wind farms. They use these simulations to forecast power output, plan the integration of wind farms into the grid, and ensure reliable operation of the overall power system.

One way to accelerate the adoption of renewable energy sources is to ensure their economic viability. Variations in local wind speeds make wind farm production and financial forecasting challenging.

EDP Renewables North America uses MATLAB to generate accurate revenue predictions and revenue-at-risk projections by combining production estimates with forecasts of power prices on the futures market. Analysts at the company used MATLAB to develop automated systems for price forecasting and for portfolio and risk analysis. These systems are used to assess potential wind farm sites and guide both short-term and long-term business decisions.