PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling

García, Emilio José; Moreno-Muñoz, Antonio; Santiago, I.; Moreno-Garcia, Isabel M.; Milanés‐Montero, María Isabel

doi:10.3390/en10101488

Cited by 25 publications

(21 citation statements)

References 31 publications

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“…Therefore, local PV self-consumption is gaining attention in several countries [7,8]. Energy storage is one effective way of allowing a larger fraction of de-mand to be met by PV-generation [9] and recent work has demonstrated that batteries can be used to increase the amount of PV that can be reliably integrated into the distribution network [10]. Other methods of increasing PV penetration include novel curtailment methods [11] and better PV and demand forecasting [12].…”

Section: Introductionmentioning

confidence: 99%

Community energy storage: A smart choice for the smart grid?

et al. 2018

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Energy storage can help integrate local renewable generation, however the best deployment level for storage remains an open question. Using a data-driven approach, this paper simulates 15-minute electricity consumption for households and groups them into local communities of neighbors using real locations and the road network in Cambridge, MA. We then simulate PV for these households and use this framework to study battery economics in a high PV adoption, high electricity cost scenario, in order to demonstrate significant storage adoption. We compare the results of storage adoption at the level of individual households to storage adoption on the community level using the aggregated community demands. Under the simulated conditions, we find that the optimum storage at the community level was 65% of that at the level of individual households and each kWh of community battery installed was 64-94% more effective at reducing exports from the community to the wider network. Therefore, given the current increasing rates of residential battery deployment, our research highlights the need for energy policy to develop market mechanisms which facilitate the deployment of community storage.

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Section: Introductionmentioning

confidence: 99%

Community energy storage: A smart choice for the smart grid?

et al. 2018

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“…The scope of this dynamic data study is only limited to the voltage magnitude issues. Traditionally, stochastic modelling is used for unknown data [39]. However, due to the availability of real-time loading and irradiation data, it was not performed.…”

Section: Results and Discussion: Dynamic Studymentioning

confidence: 99%

A Comparative Study into Enhancing the PV Penetration Limit of a LV CIGRE Residential Network with Distributed Grid-Tied Single-Phase PV Systems

et al. 2019

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Photovoltaic distributed generation (PVDG) has seen tremendous growth in recent years, especially in the residential sector. Among other concerns, the voltage rise in AC networks is considered the most limiting factor in achieving increased PV penetration levels. A steady-state impact study is performed on a CIGRE low-voltage (LV) residential network. This paper compares six techniques to increase the PV penetration limit in the LV residential network, namely single-phase penetration (SPP), Distribution Scheme 1 (DS1), Distribution Scheme 2 (DS2), alternate phase penetration (APP), offline tap adjustment (OTA) and switched on-load tap adjustment (SOLTA). PSCAD software is used for this study. The best results are obtained for the DS2-SOLTA case that gives the minimum voltage magnitude and voltage unbalance in the system. The steady-state results are validated by a dynamic data study using measured solar irradiance and residential load data. A novel approach is also proposed for calculating the worst day from the data set. The obtained results verify the effectiveness of the proposed approach.

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“…This study performs the hosting capacity assessment without considering active network managements (ANMs). ANMs, such as on-load tap changers [39] and energy storage [40,41], are verified to be effective ways for the enhancement of hosting capacity. However, due to the need for the knowledge of the succession of operating states (e.g., state of charge of energy storage), the assessment of enhanced hosting capacity can be more challenging when considering ANMs.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

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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.

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PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling

Cited by 25 publications

References 31 publications

Community energy storage: A smart choice for the smart grid?

Community energy storage: A smart choice for the smart grid?

A Comparative Study into Enhancing the PV Penetration Limit of a LV CIGRE Residential Network with Distributed Grid-Tied Single-Phase PV Systems

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

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