研究目的
To minimize the cost required to keep the room temperature under the desired level in a microgrid consisting of a distributed generator (DG), a battery energy storage system (BESS), a solar photovoltaic (PV) system, and thermostatically controlled loads (TCLs).
研究成果
The proposed decentralized control scheme significantly outperforms other control algorithms, is computationally efficient, easily scalable, and does not require any significant data communication subsystem. The optimality of the proposed algorithm has been proved in a mathematically rigorous way.
研究不足
The proposed method requires accurate forecasting of solar power and outdoor temperature. The performance of the algorithm can be degraded by delays due to forecasting techniques, data communications, and response time in power electronics.
1：Experimental Design and Method Selection:
A decentralized control strategy involving variable structure controller and dynamic programming is proposed to determine suitable control inputs for the DG and BESS. The model predictive control approach is used for long-term operation with predicted data on solar power and outdoor temperature updated at each control step.
2：Sample Selection and Data Sources:
Solar power data is retrieved from the St. Lucia Concentrating Array located in UQ Photovoltaic Sites, and outdoor temperature data is based on temperature observations of Sydney.
3：List of Experimental Equipment and Materials:
The microgrid consists of a DG, BESS, solar PV system, and TCLs.
4：Experimental Procedures and Operational Workflow:
The control inputs for the DG and BESS are determined based on predicted solar power and outdoor temperature over a forecasting horizon. The receding horizon approach is utilized for long-term operation.
5：Data Analysis Methods:
The additive costs from both DG and BESS over each forecasting horizon is used as the objective function to minimize the overall energy cost.
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