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Cooperative Distributed Energy Scheduling in Microgrids

  • Mehdi Rahmani-Andebili
Chapter
Part of the Power Systems book series (POWSYS)

Abstract

This chapter introduces a multi-time scale model predictive control (MPC) approach which is stochastically applied in the cooperative distributed energy scheduling problem of the microgrids (MG). The cooperative distributed approach is preferred, since a centralized one is not applicable in a competitive power market environment because it requires all the data of all the MGs, which is impractical. In this chapter, in order to deal with the variability and uncertainties associated with output power of the renewable energy resources (RES) and load demand, stochastic MPC is applied in distributed energy scheduling problem of MGs. Additionally, considering multi-time scale approach in the stochastic MPC is capable of simultaneously having vast vision for the optimization time horizon and precise resolution for the problem variables. Herein, each MG with a different set of sources is able to transact power with the electricity market and the neighboring MGs. The numerical study demonstrates that cooperation of the MGs in the distributed energy scheduling problem is beneficial, and also the multi-time scale MPC is advantageous compared to the single-time scale MPC in both non-cooperative and cooperative distributed energy scheduling problems.

Keywords

Cooperative distributed energy scheduling Microgrids Multi-time scale approach Stochastic model predictive control (MPC) Renewables 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.The Holcombe Department of Electrical and Computer EngineeringClemson UniversityClemsonUSA

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