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Optimization of battery–supercapacitor hybrid energy storage station in wind solar generation system
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OPTIMIZATION OF BATTERY–SUPERCAPACITOR HYBRID ENERGY STORAGE
STATION IN WIND SOLAR GENERATION SYSTEM
ABSTRACT:
In capacity optimization of hybrid energy storage station (HESS) inwind/solar generation
system, how tomake full use of wind and solar energy by effectively reducing the investment and
operation costs based on the load demand through allocating suitable capacity of HESS is an
optimization problem. The optimization objective is to minimize one-time investment and
operation costs in thewholelifecycle,theconstraintsareutilizationrate,andreliability of power
supply. In this paper, mathematical models of wind/solar generation systems, battery, and
supercapacitor are built, the objective optimization function of HESS is proposed, and various
constraints are considered. To solve the optimization problem, improved simulated annealing
particle swarm optimization algorithm is proposedbyintroducingthe
simulatedannealingideaintoparticleswarm algorithm.The newalgorithmenhance the ability to
escape fromlocal optimum and improve the diversity of particle swarm, then help to avoid
prematurity and enhance the global searching ability of the algorithm. With the example system,
the optimization results show that the convergence of new algorithm is faster than the traditional
particle swarm optimization algorithm and its cost optimization is better, which demonstrated the
correctness and validity of the proposed models and algorithms. This method can provide a
reference forthecapacityoptimizationofHESSinwind/solargenerationsystem.
