Stochastic Stability Analysis Method of Multi-energy Complementary System Based on Markov Model

An analysis method and a stable technology, applied in the field of multi-energy complementary systems, can solve problems such as difficulty in responding in a timely manner during the charging and discharging process of the energy storage system, and fluctuations in the output of new energy sources.

An analysis method and a stable technology, applied in the field of multi-energy complementary systems, can solve problems such as difficulty in responding in a timely manner during the charging and discharging process of the energy storage system, and fluctuations in the output of new energy sources.

CN107666155BActive Publication Date: 2020-11-20HOHAI UNIV

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  • Stochastic Stability Analysis Method of Multi-energy Complementary System Based on Markov Model
  • Stochastic Stability Analysis Method of Multi-energy Complementary System Based on Markov Model
  • Stochastic Stability Analysis Method of Multi-energy Complementary System Based on Markov Model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0093] Embodiment: a kind of stochastic stability analysis method of multi-energy complementary system based on Markov model, such as figure 1 As shown, the specific steps are as follows:

[0094] 1. Markov modeling of wind speed

[0095] The Markov model can describe the stochastic process of the system state very well. Carry out K-mean value clustering analysis on the existing wind speed data, obtain the wind speed cluster center point m=1, 2,..., s, and establish the Markov chain. Such as figure 2 As shown, the abscissa represents time, the ordinate represents the wind speed, r(t) represents the state corresponding to time t, and according to the clustering results, the wind speed is divided into different states (S1, S2, ..., Ss). The transition rate matrix between each state is obtained through the Bayesian inference process, and the calculation formula is as follows:

[0096]

[0097] In the formula, t represents time, Δt>0 represents time difference, o(Δt) repre...

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Abstract

The invention provides a Markov model-based multi-energy complementary system random stability analysis method. In order to reasonably describe the changing condition of the illumination and the windspeed, existing illumination data, wind speed data and the like are subjected to clustering analysis, and then the center point of each cluster is obtained. The center point of each cluster is adoptedas one Markov state. A transfer rate matrix between all states is obtained through Bayesian reasoning. According to the Kirchhoff voltage and current law, a Markov state space model is built. On theabove basis, a random Lyapunov function is constructed for carrying out the random stability analysis. Moreover, though detecting the current value of a grid connection point, a current controller isdesigned to carry out the in-situ reduction of an adjustable load. According to the fluctuation condition of the new energy power generation, the consumption amount of the load is adjusted. Therefore,the power transmitted to the power grid is guaranteed to be continuous and stable. Finally, the simulation operator test is established and then the effectiveness and the practicability of the methodare verified.

Description

technical field [0001] The invention relates to a multi-energy complementary system, in particular to a method for analyzing the random stability of the multi-energy complementary system. Background technique [0002] With the rapid development of modern industry, people's demand for energy is increasing rapidly. Compared with traditional fossil energy, renewable new energy is clean, renewable and easy to obtain. Especially in view of today's outstanding environmental problems and the depletion of fossil energy, renewable new energy power generation has become the main way of global power generation in the future. At present, the penetration rate of new energy power generation in the power system is gradually increasing. With the planning, construction and operation of large-capacity wind farms and photovoltaic power stations, the proportion of new energy power generation in the power system is gradually increasing. The randomness and nature of new energy The impact of vola...

Claims

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Application Information

Patent Timeline
20 Nov 2020
Publication
CN107666155B
IPC
H02J3/38; H02J3/24
CPC
H02J3/24; H02J3/383; H02J3/386; H02J2203/20; Y02E10/56; Y02E10/76
Inventors
孙永辉; 翟苏巍