Optimization Method for Operation Schedule of Microgrids Considering Uncertainty in Available Data

Hirotaka Takano, Ryota Goto, Ryosuke Hayashi and Hiroshi Asano
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Hirotaka Takano: Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan
Ryota Goto: Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan
Ryosuke Hayashi: Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan
Hiroshi Asano: Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan

Energies, 2021, vol. 14, issue 9, 1-13

Abstract: Operation scheduling in electric power grids is one of the most practical optimization problems as it sets a target for the efficient management of the electric power supply and demand. Advancement of a method to solve this issue is crucially required, especially in microgrids. This is because the operational capability of microgrids is generally lower than that of conventional bulk power grids, and therefore, it is extremely important to develop an appropriate, coordinated operation schedule of the microgrid components. Although various techniques have been developed to solve the problem, there is no established solution. The authors propose a problem framework and a solution method that finds the optimal operation schedule of the microgrid components considering the uncertainty in the available data. In the authors’ proposal, the objective function of the target problem is formulated as the expected cost of the microgrid’s operations. Since the risk of imbalance in the power supply and demand is evaluated as a part of the objective function, the necessary operational reserve power is automatically calculated. The usefulness of the proposed problem framework and its solution method was verified through numerical simulations and the results are discussed.

Keywords: microgrids; operation schedule of microgrids; balance of power supply and demand; unit commitment (UC); economic load dispatch (ELD); particle swarm optimization (PSO); treatment of uncertainty (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: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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