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| Reference | Model | Tool | Objective | Approach | Duration |
|
| Marulanda and Pavas [20] | IEEE 73 test bus feeder (comprehensive test feeder—Kersting) | OpenDSS with MATLAB | Analyze the power flows and voltage profile of the feeder with 10.16% PV generation | Chronological Monte Carlo simulation for distribution systems with PV generation | 24 hours |
| Ahamioje and Krishnaswami [21] | IEEE 13 bus feeder | OpenDSS, MATLAB, and Grid PV with GIS | Design on the model the likely real effects of PV on operations | Quasi-static time series analysis with dynamic volt/var and active power control with Grid PV toolbox integration of geographical information | 180 hours |
| Solanki et al. [22] | 12.47 kV distribution feeders for American electric power (AEP) | OpenDSS | Investigate the effects of high PV penetration with cloud cover scenarios as percentage system loss and voltage variation | Changing the regulator/LTC tap settings, reconductoring distribution lines, changing the placement of capacitor banks, employing storage to efficiently manage the dispatch of PV system | 24 hours |
| Ma et al. [23] | IEEE 13 test bus feeder | OpenDSS with MATLAB (optimization tool) | Optimizing the generation cost to minimize operation cost | Model predictive control | 24 hours |
| Pukhrem [24] | IEEE 55 test bus feeder (European LVDN) | OpenDSS with MATLAB | Alleviate the voltage fluctuation and reduce the overall P/Q network loss against the extreme-case scenarios | Autonomous coordinated voltage control techniques of grid-tied PV inverters | 24 hours (every 5 min) |
| Ramachandran [25] | IEEE 13 node test feeder with PV at the end node | OpenDSS and CYMDIST | Determine optimal bids to maximize its profit and the effects of voltage imbalance and loss of the feeder | Dynamic programming | 24 hours |
| Nowak et al. [26] | IEEE 34 test feeder | OpenDSS and Grid PV toolbox in MATLAB for PV inverters | Simulated on PV bus V, P, and Q based on a) maximum standard deviation via distance from the substation, b) total energy loss (kWh) in the feeder via penetration, and c) size difference of PV inverter for voltage PV based on normalized V | PI-based reactive power control method of PV inverters | 24 hours |
| Liu and Overbye [27] | IEEE 13 node test feeder | OpenDSS and MATLAB | Find an operating point that maximizes energy savings after minimizing the total system loss and system energy consumption | Conservation voltage reduction algorithm from SQP to minimize the deviation from the control voltage level | 4 hours |
| Liu et al. [28] | IEEE 7 node test feeder | MATLAB and OpenDSS | Increase PV hosting capacity with different voltage problems | Voltage/var control and voltage/watt control for a smart inverter | |
| Ammar and Sharaf [29] | IEEE test feeder 17 buses (25 kV) and IEEE test feeder 69 buses (12.66 kV) | MATLAB and OpenDSS | Minimize the deviation of the distribution network voltages | Finding optimal coordinated PV generator reactive power and HV/MV OLTC settings throughout the optimization time frame | |
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