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    Öğe
    Strategies for increasing hosting capacity in PV-rich LV feeders via radiality-imposed reconfiguration
    (Elsevier, 2024) Aydin, Muhammed Sait
    With the growing volume of photovoltaic (PV) systems in residential low -voltage (LV) feeders, the voltage rise has become a widespread issue. In order to address this challenge, therefore, this paper proposes extending a radiality-imposed reconfiguration approach, which has proven to be an effective method at the medium voltage (MV) level to the LV level. To cater for the complexity inherent to LV feeders, which typically entail thousands of nodes and almost none switches, two practical and viable strategies for Distribution Network Operators (DNOs) are proposed. The first strategy encompasses leveraging a branch -exchange approach for a feeder with a voltage rise that has neighboring feeders having additional headroom for voltage. The second strategy is, on the other hand, the deployment of a new transformer to address the problem of voltage rise for feeders when neighboring feeders lack additional voltage headroom. In order to realistically quantify the impact of PV systems on LV feeders and assess the effectiveness of the proposed solutions, a Monte -Carlo approach is adopted. The results show that both strategies, considering the existing feeder on -site, are effective for enhancing hosting capacity in the LV feeders. This paper, consequently, provides contributions to the methods that augment hosting capacity in LV feeders with PV systems by proposing practical and effective solutions.
  • [ X ]
    Öğe
    Using OLTC-Fitted Distribution Transformer to Increase Residential PV Hosting Capacity: Decentralized Voltage Management Approach
    (Mdpi, 2022) Aydin, Muhammed Sait; Alnaser, Sahban W.; Althaher, Sereen Z.
    The increasing Photovoltaic (PV) penetration in residential Low Voltage (LV) networks is likely to result in a voltage rise problem. One of the potential solutions to deal with this problem is to adopt a distribution transformer fitted with an On-Load Tap Changer (OLTC). The control of the OLTC in response to local measurements reduces the need for expensive communication channels and remote measuring devices. However, this requires developing an advanced decision-making algorithm to estimate the existence of voltage issues and define the best set point of the OLTC. This paper presents a decentralized data-driven control approach to operate the OLTC using local measurements at a distribution transformer (i.e., active power and voltage at the secondary side of the transformer). To do so, Monte Carlo simulations are utilized offline to produce a comprehensive dataset of power flows throughout the distribution transformer and customers' voltages for different PV penetrations. By the application of the curve-fitting technique to the resulting dataset, models to estimate the maximum and the minimum customers' voltages are defined and embedded into the control logic to manage the OLTC in real time. The application of the approach to a real UK LV feeder shows its effectiveness in improving PV hosting capacity without the need for remote monitoring elements.