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## Optimal energy and operation management of microgrids

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In this chapter, an efficient PSO-based approach has been proposed and successfully applied to solve EOM problem in an MG. The Weibull and normal distributions are employed to model the input random variables, namely, the output power of the WT and PV units, the load demand, and the market price. The 2m+1 point estimate method and the Gram-Charlier expansion theory are used to obtain the statistical moments and the PDFs of the EOM results. The proposed approach has been tested and investigated on two grid-connected MGs including different DG units and energy storage. The simulation results show the efficiency of the proposed approach to solve both deterministic and probabilistic EOM problems under different operational scenarios of the MGs. Moreover, the results obtained using the proposed PSO algorithm are either better or comparable to those obtained using other techniques reported in the literature. As such, it can serve as a useful decision-making supporting tool for MG operators and help to find out how the input random variables affect the statistical characteristics of the EOM results.

Chapter Contents:

• 12.1 Introduction
• 12.2 Problem formulation of EOM
• 12.2.1 Objective function
• 12.2.2 Constraints
• 12.2.2.1 Power balance
• 12.2.2.2 Real power generation capacity
• 12.2.2.3 Spinning reserve
• 12.2.2.4 Energy-storage limits
• 12.2.2.5 Calculation of the active power from (to) the utility
• 12.2.3 Distributed generation bids calculation
• 12.2.3.1 Microturbine and fuel cell
• 12.2.3.2 Diesel generator
• 12.2.3.3 Wind turbine and photovoltaic
• 12.3 Solution method
• 12.3.1 Overview of PSO
• 12.3.2 Application of PSO to EOM
• 12.4 Probabilistic EOM of MG
• 12.4.1 Statistical characterization of the input random variables
• 12.4.1.1 Wind-speed modeling
• 12.4.2 Statistical evaluation of the output variables
• 12.4.3 Procedure for solving probabilistic EOM
• 12.5 Simulation results
• 12.5.1 Microgrid MG1
• 12.5.1.1 Deterministic EOM
• 12.5.1.2 Probabilistic EOM
• 12.5.2 Microgrid MG2
• 12.5.3 MATLAB program eom used for deterministic EOM
• 12.6 Conclusion
• References

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