Optimal Energy Scheduling and Transaction Mechanism for Multiple Microgrids

Boram Kim, Sunghwan Bae and Hongseok Kim
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Boram Kim: Department of Electronic Engineering, Sogang University, Seoul 04107, Korea
Sunghwan Bae: Department of Electronic Engineering, Sogang University, Seoul 04107, Korea
Hongseok Kim: Department of Electronic Engineering, Sogang University, Seoul 04107, Korea

Energies, 2017, vol. 10, issue 4, 1-17

Abstract: In this paper, we propose a framework for optimal energy scheduling combined with a transaction mechanism to enable multiple microgrids to exchange their energy surplus/deficit with others while the distributed networks of microgrids remain secure. Our framework is based on two layers: a distributed network layer and a market layer. In the distributed network layer, we first solve optimal power flow (OPF) using a predictor corrector proximal multiplier algorithm to optimally dispatch diesel generation considering renewable energy and power loss within a microgrid. Then, in the market layer, the agent of microgrid behaves either as a load agent or generator agent so that the auctioneer sets a reasonable transaction price for both agents by using the naive auction-inspired algorithm. Finally, energy surplus/deficit is traded among microgrids at a determined transaction price while the main grid balances the transaction. We implement the proposed mechanism in MATLAB (Matlab Release 15, The MathWorks Inc., Natick, MA, USA) using an optimization solver, CVX. In the case studies, we compare four scenarios depending on whether OPF and/or energy transaction is performed or not. Our results show that the joint consideration of OPF and energy transaction achieves as minimal a cost as the ideal case where all microgrids are combined into a single microgrid (or called grand-microgrid) and OPF is performed. We confirm that, even though microgrids are operated by private owners who are not collaborated, a transaction-based mechanism can mimic the optimal operation of a grand-microgrid in a scalable way.

Keywords: microgrid; optimal power flow; power quality; distributed optimization; energy transaction; the naive auction-inspired algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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