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Probabilistic Assessment of Hybrid Wind-PV Hosting Capacity in Distribution Systems

doi: 10.3390/su12062183
In recent years, hybrid wind-photovoltaic (PV) systems are flourishing due to their advantages in the utilization of renewable energy. However, the accurate assessment of the maximum integration of hybrid renewable generation is problematic because of the complex uncertainties of source and demand. To address this issue, we develop a stochastic framework for the quantification of hybrid energy hosting capacity. In the proposed framework, historical data sets are adopted to represent the stochastic nature of production and demand. Moreover, extreme combinations of production and demand are introduced to avoid multiple load flow calculations. The proposed framework is conducted in the IEEE 33-bus system to evaluate both single and hybrid energy hosting capacity. The results demonstrate that the stochastic framework can provide accurate evaluations of hosting capacity while significantly reducing the computational burden. This study provides a comprehensive understanding of hybrid wind-PV hosting capacity and verifies the excellent performance of the hybrid energy system in facilitating integration and energy utilization.
- Wuhan University China (People's Republic of)
- Wuhan University China (People's Republic of)
distribution system, Environmental effects of industries and plants, hosting capacity, TJ807-830, wind power, TD194-195, Renewable energy sources, photovoltaic, Environmental sciences, Hybrid energy system, GE1-350, hybrid energy system
distribution system, Environmental effects of industries and plants, hosting capacity, TJ807-830, wind power, TD194-195, Renewable energy sources, photovoltaic, Environmental sciences, Hybrid energy system, GE1-350, hybrid energy system
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
