Smoothing ramp events in wind farm based on dynamic programming in energy internet

doi:10.1007/s11708-018-0593-8

Front. Energy

2018, Vol. 12

Issue (4) : 550-559 https://doi.org/10.1007/s11708-018-0593-8

RESEARCH ARTICLE

Smoothing ramp events in wind farm based on dynamic programming in energy internet

Jiang LI(

), Guodong LIU, Shuo ZHANG

School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China

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Abstract

The concept of energy internet has been gradually accepted, which can optimize the consumption of fossil energy and renewable energy resources. When wind power is integrated into the main grid, ramp events caused by stochastic wind power fluctuation may threaten the security of power systems. This paper proposes a dynamic programming method in smoothing ramp events. First, the energy internet model of wind power, pumped storage power station, and gas power station is established. Then, the optimization problem in the energy internet is transformed into a multi-stage dynamic programming problem, and the dynamic programming method proposed is applied to solve the optimization problem. Finally, the evaluation functions are introduced to evaluate pollutant emissions. The results show that the dynamic programming method proposed is effective for smoothing wind power and reducing ramp events in energy internet.

Keywords energy internet wind power ramp events dynamic programming

Corresponding Author(s): Jiang LI

Just Accepted Date: 21 September 2018 Online First Date: 03 December 2018 Issue Date: 21 December 2018

Cite this article:

Jiang LI,Guodong LIU,Shuo ZHANG. Smoothing ramp events in wind farm based on dynamic programming in energy internet[J]. Front. Energy, 2018, 12(4): 550-559.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-018-0593-8
https://academic.hep.com.cn/fie/EN/Y2018/V12/I4/550

Fig.1 System diagram

Fig.2 Solution process

Fig.3 Policy formation process

Fig.4 Flowchart of the algorithm proposed in smoothing wind power fluctuation (p_a(_t₎ is the wind power value by smoothing.)

Fig.5 Test systems

Fig.6 Ramp events and rates in energy internet before using a dynamic programming algorithm to smooth wind power (a) ramp events based on wind power forecasting; (b) ramp rates based on wind power forecasting

Fig.7 Simulation result under no smoothing and smoothing

Fig.8 Storage capacity and output of pumped storage power station

Fig.9 Natural gas consumption of gas power station

Fig.10 Output of gas power station

Tab.1 Comparison of β_w and σ_w

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