An integrated control and protection scheme based on FBSM-MMC active current limiting strategy for DC distribution network

DC faults can easily lead to overcurrent in DC distribution networks; these faults pose serious threats to the safe operation of the system. The blocking of modular multilevel converters based on the full-bridge sub-modules (FBSM-MMC) is mostly utilized to cut off the fault current. However, the blocking causes short-term blackouts in the entire DC distribution network and there are presently no effective solutions to address this problem. In this study, an integrated control and protection scheme based on the FBSM-MMC active current limiting strategy is proposed. The project includes three stages: first, MMC active current limiting strategy is used to limit the output current of the converter to about 1.2 p.u. after the occurrence of the fault (Stage 1); next, faulty lines are identified based on the asynchronous zero-crossing features of the DC currents of the two ends of the line (Stage 2); then, a fault isolation scheme based on the cooperation of converters, DC circuit breakers, and high-speed switches is proposed to isolate the faulty line (Stage 3). The distribution network can restart quickly via control of the converters. Finally, the simulation of a four-terminal flexible DC distribution network in PSCAD/EMTDC demonstrates the effectiveness of the proposed integrated scheme

Protection Scheme based on Artificial Neural Network for Fault Detection and Classification in Low Voltage PV-Based DC Microgrid

With the expansion of the DC distribution market, protection, and operational concerns for Direct Current (DC) Microgrids have increased. Different systems have been investigated for detecting, finding, and isolating defects utilising a variety of protective mechanisms. It might be difficult to locate high-resistance faults and shorted DC faults on low-voltage DC (LVDC) microgrids. Therefore, in this study, a Field Transform Technique like Short-Time Fourier Transform (STFT) is proposed for detecting the Fault Current (FC). This method detects the faults Pole-ground (PG), pole-pole (PP), and Arc fault are the major fault types in the DC network with PG fault as the most common and less severe. One of the difficulties the DC system faces in the incidence of a malfunction is the protection of essential converters. During this fault, the diodes, being the most vulnerable component of the system, may encounter a substantial surge in current, which can potentially cause damage if the current surpasses double their specified capacity for withstanding. After the Fault detection (FD), a Taguchi-based ANN is presented to classify the detected faults. This method effectively classifies PV-based faults. Then, to safeguard the FC, the Improved Self-Adaptive Solid State Circuit Breaker (I-SSCB) is introduced. It safeguards the FC in the low-voltage PV-based DC microgrid (DCMG) and restricts FC in the DCMG. The suggested approach is evaluated using the Matlab software and the proposed method produces 400A current and 100 KW power during the PV temperature of 25°C. The output current of the ANN is then 1A for a duration of 0.3 to 0.4 seconds. The fault voltage and FC produced in this proposed work are 1900V and 1950A. Therefore, the proposed work's current and voltage values are 21 KV and 0.35 I. Therefore, the proposed method produces more power and limits the FC in the LV-DCMG. In future studies, the improved or modified neural network or machine learning (ML)-based techniques can be utilized which may improve the protection scheme of the work

Real time distribution network protection considering the impact of renewable energy

To achieve the net-zero carbon dioxide emissions goal, the penetration rate of distributed energy resources has been increasing in modern power distribution networks for the past decade. Although these energy resources are environmentally friendly, they raise challenges for distribution network protection. Distribution networks are typically designed based on the single power flow direction principle, where power is flowing from the substation transformer to the load following a tree-like topology. In this way, power lines that are closer to the substation may have higher current flows. For distribution network feeder protection, particularly overcurrent relays, coordination is achieved based on the above principle, such that the downstream power lines closer to the fault have equal or higher level of fault currents compared to the upstream power lines. With distributed energy resources, the distribution network can work in either grid connected mode as is most common or islanded mode as in emerging microgrids. This indicates that the electrical topology of the distribution network can be changed in real time. Moreover, when a fault happens, the downstream relay can see higher level of fault current compared to the upstream relay, causing malfunctions of the relay, such as blinding or sympathetic tripping. The main focus of this thesis is on the development and the implementation of a new current tracing decomposition method to address the above issues. Specifically, a very detailed grid model is proposed, which has sufficient information of the current flows both from each distributed energy source to the power lines and between each distributed energy source and loads. With the results of the current flow information from the current tracing method, this research highlights the implementation of machine learning for fault current identification. Specifically, the current tracing method is taken as the kernel function that can be used to improve the performance of the support vector machine for the detection of low level faults that may be below the sensitivity of conventional overcurrent relays in the presence of DERs. This research also highlights the implementation of the new current tracing method on primary and backup protection schemes in distribution feeders. Specifically, decomposed currents are used as a substitute of the measurement currents to better coordinate the upstream and downstream relays. To demonstrate the effectiveness of the proposed method, the current tracing method is implemented in a Matlab-Simulink platform and imported to EMTP-MATLAB simulation interface. The simulation results show that using the decomposed current can improve the sensitivity and dependability of primary and backup protection in the presence of multiple DERs. It can also address the issue of protection relay blinding caused by the injection of distributed energy resources