研究目的
To design an optimal hybrid energy storage system (ESS) to smooth out short-term PV power fluctuations in a power grid using frequency analysis, considering practical factors like cycle life and capacity loss.
研究成果
The proposed FFT-based method effectively designs a hybrid ESS with lead-acid batteries and EDLCs to smooth PV power fluctuations. Considering cycle life and capacity loss increases system cost but provides a more realistic design. The optimum cut-off frequency was found to be 0.000352 Hz, with a total cost of $9974. Different weather pattern selection methods (average, peak, probability) offer trade-offs between cost and effectiveness.
研究不足
The study is based on data from a specific location (Milwaukee) and a 50-day sample, which may not represent all weather conditions. It assumes certain parameters like 40% capacity loss at end of cycle life, and practical application factors might vary. The cost optimization does not account for all real-world variables such as maintenance or environmental impacts.
1：Experimental Design and Method Selection:
The study uses Fast Fourier Transform (FFT) to analyze PV output power fluctuations in the frequency domain and to select representative weather patterns. It involves dividing the frequency spectrum for hybrid ESDs (lead-acid batteries and EDLCs) based on their response characteristics and optimizing cut-off frequencies to minimize system cost while considering cycle life and capacity loss.
2：Sample Selection and Data Sources:
50 days of PV output data were collected from a small experimental station in Milwaukee at a certain time interval. The data includes daily PV output curves converted into frequency domain with 49261 frequency points per day.
3：List of Experimental Equipment and Materials:
PV system, lead-acid batteries, electric double-layer capacitors (EDLCs), and computational tools for FFT analysis. Specific models or brands are not mentioned.
4：Experimental Procedures and Operational Workflow:
Convert time-domain PV data to frequency domain using FFT; apply three approaches (averaging, peak value, probability) to select representative weather patterns; calculate balancing power based on grid acceptable power; separate frequency components for ESDs; optimize cut-off frequencies; compute ESD capacities and costs considering cycle life and capacity loss.
5：Data Analysis Methods:
FFT and inverse FFT for frequency-time domain conversions; statistical methods for probability analysis; cost optimization algorithms; use of equations for energy and power capacity calculations.
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