Power-Voltage Mapping Method Based on Comprehensive Probability Model and Deep Learning for Smart Grid

Jianyi LI; Peng LI; Xiaochun XU; Ruyu SHI; Pingliang ZENG; Hui XIA

doi:10.12204/j.issn.1000-7229.2022.02.005

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Electric Power Construction ›› 2022, Vol. 43 ›› Issue (2) : 37-44. DOI: 10.12204/j.issn.1000-7229.2022.02.005

Smart Grid

Power-Voltage Mapping Method Based on Comprehensive Probability Model and Deep Learning for Smart Grid

Jianyi LI ¹ ,
Peng LI ¹ ,
Xiaochun XU ² ,
Ruyu SHI ³ ,
Pingliang ZENG ⁴ ,
Hui XIA ¹

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Abstract

With the increase in the penetration rate of new energy based distributed power generation, its characteristics such as strong intermittent and high volatility will have a greater impact on grid voltage fluctuations. How to calculate the steady-state voltage of the power grid with complex distributed power access more quickly is of great significance. In this paper, by sampling a great deal of real output data of photovoltaic and wind power, a comprehensive probability model is improved and generated on the basis of the traditional probability model, and the probability distribution deviation caused by the temporal and spatial characteristics is corrected through the Markov transition probability matrix. Then, taking the actual output data of adjacent photovoltaic and wind power stations in a certain area of southern China as a sample, the steady-state voltage at each node of the distribution network under different scenarios is calculated in the distribution network topology. Finally, the results of the calculation example show that the power grid model generated by the improved method simulation in this paper has high authenticity and applicability, and the calculated voltages have high accuracy rate. Moreover, compared with the traditional power system flow calculation, the calculation time is greatly reduced, so that it has better follow-up in the control effect, and is suitable for the calculation of the steady-state voltage of the complex power system with new energy.

Key words

new energy / comprehensive probability model / Markov chain / Monte Carlo simulation / artificial intelligence

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Jianyi LI , Peng LI , Xiaochun XU , et al . Power-Voltage Mapping Method Based on Comprehensive Probability Model and Deep Learning for Smart Grid[J]. Electric Power Construction. 2022, 43(2): 37-44 https://doi.org/10.12204/j.issn.1000-7229.2022.02.005

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