Near-Optimal Day-Ahead Scheduling of Energy Storage System in Grid-Connected Microgrid

Teo, T. T., Logenthiran, T., Woo, Wai Lok and Abidi, Khalid (2018) Near-Optimal Day-Ahead Scheduling of Energy Storage System in Grid-Connected Microgrid. In: ISGT Asia 2018 - International Conference on Innovative Smart Grid Technologies, 22nd - 25th May 2018, Singapore.

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This paper proposes a near-optimal day-ahead scheduling of energy storage system based on the mismatch between supply and demand, state-of-charge and real-time electricity price when deciding how much to charge and discharge the energy storage system. An artificial neural network, the extreme learning machine is used for the day-ahead forecast of the mismatch between supply and demand and real-time electricity market price. After the day-ahead forecast is obtained, the scheduling problem is formulated into a mixed-integer linear programming and implemented in AMPL and solved using CPLEX. This paper also considers the impact of forecasting errors in the day-ahead scheduling. Empirical evidence shows that the proposed near-optimal day-ahead scheduling of ESS can achieve lower operating cost and life-cycle.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Energy management system, electricity market, mixed-integer linear programming, renewable source, storage system
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 27 Mar 2019 12:19
Last Modified: 08 Sep 2020 15:17

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