This paper aims to investigate the techno-economic feasibility analysis of stand-alone diesel system, stand-alone PV/storage system, PV/diesel hybrid system, PV/diesel/storage hybrid system for the Pratas island in Taiwan. The power supply of outlying islands in Taiwan still use fossil fuel generators. The fuel cost is higher than that of on shore of Taiwan, and it has a great impact on the environment. This problem can be mitigated by hybrid energy systems. Through the investigation to know the existing generator set and Photovoltaic (PV) operating status, load consumption, etc., the study collects the required data for statistical meteorological analysis and economic analysis, and uses Hybrid Optimization Models for Energy Resources (HOMER) to simulate techno-economics of the stated hybrid energy systems. The analysis contains the capital cost, net present cost (NPC), cost of energy (COE) and fuel saving in different capacities for each power supply system with different constraints. From the simulation results, the lowest COE is 0.3569 $/kWh that can be found at the PV/diesel hybrid system configuration scheme with a total PV system capacity of 200 kWp, the renewable fraction (RF) is 15.3% and the excess electricity fraction is 2.6%, which is lower than the generally acceptable 5%. Although the COE of PV/diesel/storage hybrid is higher than that of stand-alone diesel system, the annual total CO2 emissions is reduced by 31.63%, which is of great benefit to environmental protection.

Renewable energy sources; which are abundant in nature and climate friendly are the only preferable choice of the world to provide green energy. The limitation of most renewable energy sources specifically wind and solar PV is its intermittent nature which are depend on wind speed and solar irradiance respectively and this leads to power fluctuations. To compensate and protect sensitive loads from being affected by the power distribution side fluctuations and faults, dynamic voltage restorer (DVR) is commonly used. This research work attempts to withstand and secure the effect of voltage fluctuation of grid connected hybrid PV-wind power system. To do so battery and super magnetic energy storage (SMES) based DVR is used as a compensating device in case of voltage sag condition. The compensation method used is a pre-sag compensation which locks the instantaneous real time three phase voltage magnitude and angle in normal condition at the point of common coupling (PCC) and stores independently so that during a disturbance it used for compensation. Symmetrical and asymmetrical voltage sags scenario are considered and compensation is carried out using Power System Computer Aided Design or Electro Magnetic Transient Design and Control (PSCAD/EMTDC) software.

The advancement of power electronic-based sensitive loads drives the power utilities’ devotion to power quality issues. The voltage disturbance could be happening due to fault conditions, switching of loads, energizing of transformers, or integration of highly intermittent energy sources such as PV systems. This research work attempts to enhance the voltage fluctuation of a sensitive load connected to a grid-integrated PV system using a battery-based dynamic voltage restorer (DVR). The proposed battery energy storage-based DVR has two separate controlling stages that are implemented at the DC–DC buck/boost converter of the battery and voltage source converter (VSC) system. Charging and discharging of the battery is operated based on the state-of-charge (SOC) value of the battery and the measured root mean square (RMS) voltage at the point of common coupling (PCC). The VSC of the DVR detection and reference generation control is done appropriately. In the detection control of the VSC, a combination of RMS and dq0 measurement techniques is used, whereas in the reference generation control, pre-fault strategy is implemented to restore both phase jump and magnitude distortions. Symmetrical and asymmetrical voltage sags scenarios are considered and the compensation demonstration is carried out using power system computer-aided design (PSCAD/EMTDC) software.

Contingency analysis (CA) is a vital technique of assessing power system resilience during outages by detecting overloads, voltage issues, and generator faults, strengthening grid security and emergency response planning. For the Ethiopian Electric Power (EEP) network, an N‑1 contingency analysis was conducted on Extra High Voltage (EHV) transmission lines. A dual‑depth Deep Feed Forward Neural Network (DFFNN) was employed on MATLAB/MATPOWER platform to predict bus voltage magnitudes and active power flows across branches. The DFFNN achieved strong training performance, with Mean Square Error (MSE) values of 3.887 x 10^-5 and 7.32 x10^-3, alongside high regression values of 0.99234 and 0.99479, confirming its predictive accuracy. These predictions were used to implement a novel Hybrid Performance Index (PI_hyb), which ranks contingencies according to severity. Results revealed that failure of either circuit of the Dedessa–Holeta 500 kV double-line, sourced from the Great Ethiopian Renaissance Dam (GERD), was the most severe contingency. This event produced a PI_hyb of 1.798, causing voltage instability at 19 buses and severe overloading of the Dedessa–Nekemte 132 kV line. Subsequent critical contingencies were also linked to GERD, with PI_hyb values of 0.473 and 0.321. Corrective and preventive measures are recommended to mitigate these risks, ensuring protection against cascading failures that could ultimately lead to a total blackout.