# Online Estimation of Short-Circuit Fault Level in Active Distribution Network
## 3 Implementation and Simulation Results
### Test Case and Results  
The proposed method is validated by hardware-in-loop (HIL) technology. The data processing and the proposed algorithm are implemented in hardware relays. The network and the associated disturbances are simulated in software. The network dynamics and the disturbances produced by simulation in software are converted into real signals imposed on hardware relays. Thereby, the interface between hardware and software is implemented. The network model of the test case is derived from a typical distribution network in the United Kingdom (UK). The model integrates some DGs, as illustrated in Figure 6. Meanwhile, there are three transformers with the ratios of 33 kV/11 kV/11 kV, 66 kV/11 kV/11 kV, and 132 kV/11 kV/11 kV, respectively. Six busbars are divided into three groups and connected to 12 feeders, three of which are DGs and the rest of which are loads. There are four kinds of breakers in the model. The breakers Bi1-Bi6 connect to the main power source, while Bf1-Bf12 are designed for the loads or DGs. The rest of the breakers are used for bus switching. The breaker Bf12 was chosen as the studied breaker, which is connected with different types of loads, including variable impedance load, motors, electric arc furnace, etc. Similar to the relay testing, the proposed algorithm is coded and compiled by MATLAB C-coder module. Then it runs in a real-time hardware simulator and is implemented in relays. On the other hand, the network model is firstly constructed in PSCAD software. Then the voltage and current at the breakers are simulated and stored in the COMTRADE data files. After that, the OMICRON simulator is used to generate the real signals of voltage and current, in accordance with the COMTRADE data files. The real signals generated are imposed on the relays. Thereby, the test scheme of HIL is accomplished. The basic process of the test is shown in Figure 7.  
Figure 5: The diagram of implementing the proposed method. Figure 6: The configuration of the network model to validate the proposed method. The testing scenarios are selected in accordance with the real conditions. The switching of breakers is used to simulate the different states representing the adjustment due to intermittent DGs. The downstream disturbances are generated to simulate the motor starting-up, the normal operation of the electric furnace (using its lashing characteristics), and the sudden/smoothing load change. The fault to compare with and validate the results from the proposed method is obtained by imposing a permanent three-phase short-circuit in PSCAD. The first test is carried out as follows: (1) At the beginning, all of the main-sources are disconnected, i.e., Bi1 to Bi6 are open; (2) at 6 s, Bi1 to Bi3 are closed and half of the main-sources are connected; (3) and at 10 s, Bi4 to Bi6 are closed. The composition load downstream to the studied breaker Bf12 changes randomly. The voltage and the current at the breaker are recorded for 15 s in COMTRADE files. They are shown in Figure 8a,b respectively. The fault currents obtained by the simulation in PSCAD and by the proposed method of fault level estimation (FLE) are both shown in Figure 8c. They are depicted by the dashed and the solid line, respectively. Because the switching operation on the grid side forms different states, the fault current changes dramatically at 6 s and 10 s. The changes are clearly shown in Figure 8c, with the purple dashed line. Because it needs to detect a series of non-trivial load fluctuation to launch the fault level estimation, there is a short delay for results to be updated. However, as soon as the load fluctuation is detected, the predicted estimation result is given and shown in Figure 8c, with the solid yellow line. The errors between the actual short-circuit current and the estimated result are trivial, which validates the feasibility of the proposed method. The other eight disturbances caused by different types of load fluctuations on the feeder are applied to the system. The proposed method is validated in each case.