Microgrid capacity allocation optimization method considering risk losses
An optimization method and capacity allocation technology, applied in wind power generation, photovoltaic power generation, single-network parallel feeding arrangement, etc., can solve problems such as difficulty in obtaining a large number of sample point probability models, inaccurate probability model fitting, and inability to reflect application scenarios
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[0107] Such as figure 1 As shown, a microgrid capacity allocation optimization method considering risk loss includes the following steps:
[0108] S1: Obtain the topology, basic parameters, and power generation data of the microgrid, and fit the probability distribution functions of wind power, photovoltaic power, and load power;
[0109] S2: Construct a wind-light-charge uncertainty set of multi-section intervals according to the probability distribution, and calculate the risk power of wind-light-charge;
[0110] S3: Construct a two-stage robust optimization model for power capacity allocation based on risk power;
[0111] S4: Decouple the two-stage robust optimization model of power capacity allocation into a main problem model and a sub-problem model;
[0112] S5: Use the column and constraint generation algorithm to combine the main problem model and the sub-problem model to obtain the optimal configuration of the capacity of the microgrid.
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