Abstract
Currently, using hybrid energy storage system composed of battery and supercapacitor to stabilize DC bus power fluctuation is a hot issue. In low-pass filtering control strategy to suppress the power fluctuation of DC bus, the filtering time constant is fixed, so there are problems such as poor load power fluctuation smoothing effect and over-charge and over-discharge of the battery. In this paper, a two-stage low-pass filter control strategy with variable filter time constant is designed. Firstly, the strategy builds a multi-objective function with minimum load slow target power and DC bus power difference. Using the Improved Particle Swarm Optimisation (IPSO) with compensating coefficient of inertia weight factor to solve the optimal output power by a hybrid energy storage system, and dynamically adjust the first-level filtering time constant, in order to reduce the load power change causing the fluctuation of the DC bus power; secondly, according to the charging state of the supercapacitor and the battery, the fuzzy control method is adapted to dynamically adjust the second-order filtering time constant to optimize the power distribution of the battery and the supercapacitor. The experimental results show that the control strategy can effectively reduce the power fluctuation of DC bus by about 15%, and avoid the over limit phenomenon of the battery state of charge, which has a good prospect of engineering application.
Highlights
When load changes cause DC bus power fluctuation, a single energy storage device cannot better meet the requirements of high power and high energy density at the same time, which will affect the stable and reliable operation of microgrid [1]
The experimental results show that compared with the traditional control strategy, the control strategy can reduce the power fluctuation of DC bus by about 15%, and avoid the phenomenon of over limit of the battery state of charge (SOC)
Improved Particle Swarm Optimisation (IPSO) HYBRID ENERGY STORAGE SYSTEM TO REALIZE POWER STABILIZATION TARGETS To overcome the insufficiency of constant filtering time constant and better adjust the power stabilization of hybrid energy storage system (HESS), this paper constructs a multi-objective function to minimize the fluctuation of load output power and DC bus power
Summary
When load changes cause DC bus power fluctuation, a single energy storage device cannot better meet the requirements of high power and high energy density at the same time, which will affect the stable and reliable operation of microgrid [1]. By building the first level low pass filtering to stabilize the output power and the multi-objective function with the smallest DC bus power load fluctuation It using compensation coefficient inertia weight factor of the IPSO to solve the optimal output power of HESS, dynamically adjust filtering time constant T1, minimize the load power fluctuations. The second-level low-pass filter adopts fuzzy control method to dynamically adjust the filtering time constant T2 according to the supercapacitor and the battery SOC to optimize the power distribution of the battery and the supercapacitor, to avoid the over-limit phenomenon of the battery SOC. IPSO HYBRID ENERGY STORAGE SYSTEM TO REALIZE POWER STABILIZATION TARGETS To overcome the insufficiency of constant filtering time constant and better adjust the power stabilization of HESS, this paper constructs a multi-objective function to minimize the fluctuation of load output power and DC bus power. IPSO algorithm is used to solve the optimal balancing power of the HESS, and the first stage low-pass filtering time constant T1 is dynamically adjusted to stabilize the power fluctuation of the load effectively
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