Background:
The high permeability of Distributed Generation (DG) and the development
of DC load represented by electric vehicle Battery Swapping Station (BSS) pose new challenges
to the reliable and economic operation of DC distribution system.
Methods:
In order to improve the wind and solar absorption rate and the reliable operation of DC
distribution network and coordinate the interests and demands of BSS and DC distribution company,
the upper level takes the abandonment rate and the minimum variance of BSS charging and discharging
net load as two objective functions, and the lower level takes the minimum operation cost
of DC distribution network and BSS as the objective function. Secondly, this paper proposes a
method that combines Genetic Algorithm (GA) with Wind-Driven Optimization algorithm (WDO).
CPLEX and hybrid GA-WDO are used to solve the upper and lower models, respectively.
Results:
Finally, an example shows that the proposed optimization model can reduce the operation
cost of DC distribution network with BSS and improve the utilization rate of wind and light, which
shows the rationality and effectiveness of the optimization model.
Conclusion:
In this paper, considering the randomness and uncertainty of wind power generation
and photovoltaic power generation, this paper establishes the upper objective function with the minimum
abandonment rate and load variance and the lower objective function with the minimum operation
cost of DC distribution network and BSS operators.
Two-Stage Stochastic Programming Scheduling Model for Hybrid AC/DC Distribution Network Considering Converters and Energy Storage System
