4.7 Article

Risk-Aware Operating Regions for PV-Rich Distribution Networks Considering Irradiance Variability

期刊

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 14, 期 4, 页码 2092-2108

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2023.3281890

关键词

Load modeling; Power distribution networks; Probabilistic logic; Computational modeling; Energy consumption; Stochastic processes; Low-carbon economy; Multivariate copulas; stochastic modeling; load modeling; irradiance modeling; hosting capacity

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This article proposes a framework to identify, visualize, and quantify the risk of over/under voltage due to annual energy consumption and PV generation growth. The stochastic modeling considers power profiles for distribution transformers, as well as solar irradiance profiles for a range of PV generation scenarios. The framework uses multivariate-t copulas to model correlations between random variables, and computes a probabilistic power flow to define critical operating regions. Results show the importance of considering local irradiance conditions and annual energy consumption growth in determining realistic PV installation capacity limits. A sensitivity analysis demonstrates how taking a small overvoltage risk can significantly increase the PV installed capacity limits.
This article proposes a framework to identify, visualize, and quantify risk of potential over/under voltage due to annual energy consumption and PV generation growth. The stochastic modeling considers the following: (i) Active and reactive power profiles for distribution transformers, dependent on annual energy consumption and activity in the serviced areas. (ii) Variable solar irradiance profiles that allow a broader range of PV generation scenarios for sunny, overcast, and cloudy days. The proposed framework uses multivariate-t copulas to model temporal correlations between random variables to generate synthetic scenarios. A probabilistic power flow is computed using the generated scenarios to define critical static operating regions. Results show that classical approaches may underestimate the maximum PV capacity of distribution networks when local irradiance conditions are not considered. Moreover, it is found that including annual energy consumption growth is critical to establishing realistic PV installation capacity limits. Finally, a sensitivity analysis shows that taking a 5% of overvoltage risk could increase up to 15% of the PV installed capacity limits.

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