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An economic robust programing approach for the design of energy management systems

An economic robust programing approach for the design of energy management systems

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Energy management systems have a key role in the operation of microgrid applications. Due to their importance, several approaches have been reported in the specialized literature. In this chapter, a novel formulation for robust optimizationbased EMS for microgrid applications. The novelty recast in the introduction of transmission constraints and in the avoidance of the use of prediction models for the uncertain variables. In this formulation, a time-variant uncertainty set is used to include the uncertainty in the optimization process. Unlike in the approaches reported in the specialized literature, the sets are previously defined based on the empirical statistics of historical data available. Thus, at each sampling time, the boundaries for the uncertain variables are obtained without using a prediction model. This reduces the complexity of the EMS making possible to compute the solution of the associated optimization problem in the range of the seconds. A modified version of the IEEE 9-bus system benchmark was used as test bench. In the modified version, the hydraulic generation unit (the largest unit in the system) was changed by an equivalent wind power station. The EMS was in charge of assigning the real power and the voltage level of the remaining two generation units.

Chapter Contents:

  • 11.1 Introduction
  • 11.2 Robust programing framework
  • 11.3 Energy management system as a robust programing problem
  • 11.4 Case study and simulation results
  • 11.5 Concluding remarks
  • Acknowledgment
  • References

Inspec keywords: benchmark testing; IEEE standards; energy management systems; power generation economics; distributed power generation

Other keywords: time-variant uncertainty set; economic robust programing; energy management systems; IEEE 9-bus system benchmark; hydraulic generation unit; wind power station; microgrid

Subjects: Distributed power generation; Power system management, operation and economics

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