Simulation of Power Projects

How Simulation Helps to Streamline Power Generation Processes

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As the amount of historic data used in the optimization formulation increases, the risk associated with the optimization outcome decreases. The optimization may be formulated using linear programming, which is beneficial for reducing the computational time of larger-scale problems (refer Figure 3).

Using Simulation to Inform Engineering Decisions

Once the rating of the energy storage device has been determined, a simulation study may be conducted to inform technology selection and the development of appropriate feedback control and supervisory control subsystems for the combined energy storage / variable energy system. Development of the feedback control and supervisory control systems may proceed on a lower fidelity model of the energy storage device. Lower fidelity models execute faster because they omit detailed representations of power electronic devices, enabling faster simulations and faster iterations during design.

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This approach works well because the bandwidth of the feedback control and supervisory control systems will be sufficiently lower than that of the power-electronic switching algorithms, meaning that inclusion of power electronics will have little effect on the RMS operation in the system simulation.

Developing Automated Wind Far Control

The system was simulated using a lower fidelity model of an energy storage device connected to a wind farm model. The test uses a simple supervisory control system that monitors the amount of energy stored. If the energy stored is greater than 10 per cent of the capacity, then the feedback control system regulates active power at the grid Point-of- Connection (POC) to 0.6 per unit.

Once the energy stored drops below 10 per cent of capacity, then the energy storage system is charged to capacity at a fixed rate, before the POC regulation is re-engaged. Figure 4 shows a short term cycling effect caused by insufficient wind power to provide the required level of grid power, demonstrating in this example that regulation to 0.6 per unit involves a higher level of operational risk for lower wind speeds with the chosen energy storage capacity. After the feedback and supervisory control systems have been developed, the simulation model is typically enhanced to include detailed representations of various technologies.

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