Abstract
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.
Highlights
In recent years, integration of renewable-based distributed generations (DGs) has significantly increased in distribution networks
We propose a distributionally robust optimization (DRO)-based method to evaluate the hosting capacity (HC) of distribution networks considering uncertainties associated with loads and DGs’ output powers
The proposed DRO-based method is examined on the IEEE 33-bus system for the four cases as follows:
Summary
Integration of renewable-based distributed generations (DGs) has significantly increased in distribution networks. Financially DGs are one of the most viable options for end users, technically, high penetration of them may introduce many issues such as over-voltage, overloading of the feeders [1], degradation of power quality and even higher losses in some situations [2]. These issues limit the integration of DGs in distribution systems. DSOs can plan the future network augmentation and operation strategies to increase the HC of their system
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