研究目的
Investigating the method to calculate the limit access capacity of photovoltaic (PV) source based on the chance constraints of voltage deviation, considering the randomness of PV power and load.
研究成果
The proposed method effectively calculates the limit access capacity of PV by considering the randomness of PV output and load, using chance constrained programming and quantum genetic algorithm. It provides a flexible approach to avoid incorrect calculations due to small probability events and significantly increases the penetration level of PV.
研究不足
The method's efficiency and accuracy depend on the number of Latin hypercube sampling and the convergence of the quantum genetic algorithm. The selection of confidence level affects the penetration level of PV.
1：Experimental Design and Method Selection:
The method involves maximizing the limit access capacity of PV with voltage deviation as the chance constrained condition. It uses LHS and Newton-Raphson for probabilistic load flow calculation and quantum genetic algorithm for solving the model.
2：Sample Selection and Data Sources:
The IEEE 34-bus radial distribution system is used for validation, with irradiance data from Gansu Province and load following normal distribution.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
The process includes initializing the population, measuring individuals, evaluating fitness, and using quantum revolving door for adjustment.
5：Data Analysis Methods:
The statistical properties of node voltage are obtained through probabilistic load flow calculation, and the model is solved using quantum genetic algorithm.
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