研究目的
To optimize the output power quantity and quality of hydro-PV-wind hybrid power generation system by maximizing the total output power and minimizing the standard deviation of monthly power output.
研究成果
The modified NSWOA can well solve the optimization problem. Hydropower can well compensate the PV and wind power. The hybrid power generation system can consider the stability and total generation capacity. The propose model can also be token as a reference of actual operation.
研究不足
The study focuses on a long-term optimization model, which may not capture short-term fluctuations and operational challenges. The model's effectiveness is demonstrated in a specific geographical and climatic context, which may limit its generalizability.
1：Experimental Design and Method Selection:
A long term multi-objective optimization model of hydro-photovoltaic(PV)-wind power system is established. A modified version of non-dominated sorting whale optimization algorithm (modified NSWOA) is proposed to solve the model.
2：Sample Selection and Data Sources:
The model is applied to a hydro-PV-wind power generation plan for a watershed located in southwest of China. PV and wind power output is calculated hour by hour. The monthly average power output of them are taken as the boundary condition of the reservoir optimization.
3：List of Experimental Equipment and Materials:
Installed capacity of PV power station, wind power station and hydropower station are 8000 MW, 2500 MW and 14820 MW, respectively.
4：Experimental Procedures and Operational Workflow:
The cascade hydropower system is composed of 5 reservoirs and calculated month by month. Three typical inflows are selected as the model input: wet, normal and dry year.
5：Data Analysis Methods:
The modified NSWOA is adopted to solve this model. The population size is 100, the external archive size is 50, the maximal iterations is 10000 and the polynomial mutation probability is 0.01.
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