Probabilistic Assessment of Hosting Capacity in Radial Distribution Systems

Abad, Mohammad Seydali Seyf; Ma, Jin; Zhang, Diwei; Ahmadyar, Ahmad Shabir; Marzooghi, Hesamoddin

doi:10.1109/tste.2018.2819201

Cited by 105 publications

(68 citation statements)

References 26 publications

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“…In some of the studies [18,41,52,53,56], the number of DER units in the distribution network is set by the authors and is increased from the minimum value to 100% (DER is connected to each potential integration location) while Monte Carlo simulations are performed at each increment. The Monte Carlo simulation is used for different purposes such as, to generate the DER location [17,18,20,22,41,47,50,52,53,56,57,60], size [17,18,20,47,53,56,57], connection phase in the three-phase distribution networks [50,57,60], type [22] and DER generation and load profiles scenarios [56].…”

Section: Stochastic Methodsmentioning

confidence: 99%

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A Review of the Tools and Methods for Distribution Networks’ Hosting Capacity Calculation

2020

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Integration of distributed energy resources (DERs) has numerous advantages as well as some disadvantages. To safely integrate DERs into a given distribution network and to maximize their benefits, it is important to thoroughly analyze the impact of DERs on that particular network. The maximum amount of DERs that a given distribution network can accommodate without causing technical problems or without requiring infrastructure modifications is defined as the hosting capacity (HC). In this work, a review of the recent literature regarding the HC is presented. The major limiting factors of HC are found to be voltage deviation, phase unbalance, thermal overload, power losses, power quality, installation location and protection devices’ miscoordination. The studies are found to employ one of four different methods for HC calculation: (i) deterministic, (ii) stochastic, (iii) optimization-based and (iv) streamlined. Commercially available tools for HC calculation are also presented. The review concludes that the choice of tools and methods for HC calculation depends on the data available and the type of study that is to be performed.

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Section: Stochastic Methodsmentioning

confidence: 99%

“…A probabilistic-based framework based on a two-step algorithm to linearize the HC model has been proposed in [22] to find the HC of DGs in a distribution network. Voltage rise and voltage deviation were considered as the constraints in this analysis.…”

Section: Voltage Deviationmentioning

confidence: 99%

A Review of the Tools and Methods for Distribution Networks’ Hosting Capacity Calculation

2020

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“…The obtained statistical results provide a risk-based guide to determine strategies to deal with increasing PV penetration. Instead of using load flow calculations, Abad et al [27] proposed an optimization model of hosting capacity and embedded this model into the stochastic framework to address the variability of production and consumption.…”

Section: Introductionmentioning

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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“…The HC problem has been studied considering different constraints [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. In [3,4], optimal power flow methods were proposed to solve the HC problem.…”

Section: Introductionmentioning

confidence: 99%

“…That study, however, used the time series simulations to address the uncertainties, which can be time consuming for analyzing large numbers of future grid scenarios. To address the uncertainties associated with DGs and loads, an optimization-based framework was presented in [11], which probabilistically assesses the HC. The study in [12] presented a framework to assess the effects of EVs and photovoltaic (PV) systems on the HC, separately.…”

Section: Introductionmentioning

confidence: 99%

Distributionally Robust Distributed Generation Hosting Capacity Assessment in Distribution Systems

Abad

Ahmadyar

et al. 2018

Energies

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Uncertainties associated with the loads and the output power of distributed generations create challenges in quantifying the integration limits of distributed generations in distribution networks, i.e., hosting capacity. To address this, we propose a distributionally robust optimization-based method to determine the hosting capacity considering the voltage rise, thermal capacity of the feeders and short circuit level constraints. In the proposed method, the uncertain variables are modeled as stochastic variables following ambiguous distributions defined based on the historical data. The distributionally robust optimization model guarantees that the probability of the constraint violation does not exceed a given risk level, which can control robustness of the solution. To solve the distributionally robust optimization model of the hosting capacity, we reformulated it as a joint chance constrained problem, which is solved using the sample average approximation technique. To demonstrate the efficacy of the proposed method, a modified IEEE 33-bus distribution system is used as the test-bed. Simulation results demonstrate how the sample size of historical data affects the hosting capacity. Furthermore, using the proposed method, the impact of electric vehicles aggregated demand and charging stations are investigated on the hosting capacity of different distributed generation technologies.

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Probabilistic Assessment of Hosting Capacity in Radial Distribution Systems

Cited by 105 publications

References 26 publications

A Review of the Tools and Methods for Distribution Networks’ Hosting Capacity Calculation

A Review of the Tools and Methods for Distribution Networks’ Hosting Capacity Calculation

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

Distributionally Robust Distributed Generation Hosting Capacity Assessment in Distribution Systems

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