Abstract
The output power of photovoltaic (PV) power station has strong fluctuation and randomness. Large-scale photovoltaic grid connection will affect the safe operation of power grid. In this paper, the smoothing strategy of PV output fluctuation is designed based on the adaptive moving average algorithm, which combined with the PV power prediction technology. The energy storage system compensates the difference between the grid-connected reference power and the actual generation power in real time, smoothing the grid-connected power of PV power station. Firstly, the relationship between the length of fixed sliding window and smoothness, as well as volatility in the moving average algorithm is explored to provide theoretical basis for subsequent parameter selection. Then, in order to enhance the adaptive performance of the algorithm, an adaptive moving average algorithm is proposed to dynamically adjust the length of the sliding window according to the actual power volatility. The PV power prediction curve is smoothed based on the algorithm so that the grid-connected reference power curve can be obtained. Finally, three typical weather conditions of sunny day, cloudy day and overcast day are taken as examples to simulate. The results show both feasibility and effectiveness of the strategy designed to smooth output fluctuation of PV power station.
Highlights
Affected by climate, geography and other environmental factors, PV power stations are unable to deliver electricity to the grid in a stable manner [1,2,3]
The energy storage system has flexible and fast two-way power regulation capability, which can smooth the PV power generation power according to the energy demand in real time, and reduce the adverse impact on the power grid
* Corresponding author: energystorage@126.com and design the corresponding output fluctuation smoothing strategy based on the PV power generation power prediction curve, so that the energy storage system can absorb or release energy to realize PV power smoothing control according to the demand
Summary
Geography and other environmental factors, PV power stations are unable to deliver electricity to the grid in a stable manner [1,2,3]. PV power has similar or even stronger volatility than wind power, but it is still rare to apply the power prediction technology to the smooth fluctuation of PV output, and the research on the combined application of the moving average algorithm and the power prediction results is even less, which has a good research prospect. On this basis, the paper proposes to use the adaptive moving average algorithm to find the minimum sliding window length that meets the grid-connected standards,. Design the corresponding output fluctuation smoothing strategy based on the PV power generation power prediction curve, so that the energy storage system can absorb or release energy to realize PV power smoothing control according to the demand
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