The reliability and security of power systems may be jeopardized by the increase in the amounts of renewable generation and the uncertainties produced by these devices. In particular, the protection schemes of traditional power systems have been challenged by the integration of distributed generation (DG) resources. Distance relays (DRs), which have been mainly employed to protect transmission systems, are increasingly proposed as one of the solutions to protect distribution systems with a heavy penetration of DGs. However, conventional distance protection faces several drawbacks that might lead to maloperation. One of those challenges is the “infeed effect”, which causes the impedance seen by the distance relay to be larger than the actual positive-sequence line impedance between the fault and relay location. This paper proposes three new methods to estimate the distance to the fault in the presence of infeeds, whether in a radial distribution feeder or the transmission line. Unlike other solution methodologies in the literature that require communication links to estimate the distance to the fault, the proposed methods only need the local measurement (i.e., the voltage and current measurements at the location of the distance relay) to do the same. The performance of the method is demonstrated with a radial distribution system model in PSCAD™/EMTDC™.

This study presents a techno-economic and environmental analysis of hybrid renewable energy systems to identify the optimal configuration for supplying the planned 850 MW renewable energy plant in Yanbu city, Saudi Arabia. Ten grid-connected system designs combining photovoltaic (PV), wind turbine (WT), and battery storage were simulated and optimized using the HOMER Grid software (1.10.2 pro edition). A site suitability analysis was conducted to evaluate potential locations based on climatic, topographic, and infrastructure-related factors. A sensitivity analysis considered variations in solar irradiation, wind speed, temperature, load demand, and economic parameters. The results showed that the PV-only system with an 850 MW capacity achieved the lowest net present cost (NPC) of USD 201 million and levelized cost of energy (LCOE) of 0.0344 USD/kWh, making it the most economically feasible option. However, a hybrid WT–PV configuration of 212.5 MW WT and 637.5 MW PV was also proposed to support local manufacturing. All proposed systems provided over a 91% renewable energy contribution while reducing CO₂ emissions by 53% compared to grid supply only. Up to 1152 jobs are estimated to be created through renewable energy deployment in Yanbu city.

The maritime industry is under increasing pressure to reduce greenhouse gas emissions, especially in countries such as Saudi Arabia that are actively working to transition to cleaner energy. In this paper, a new hybrid shipboard power system, which incorporates wind turbines, solar photovoltaic (PV) panels, proton-exchange membrane fuel cells (PEMFCs), and a battery energy storage system (BESS) together for propulsion and hotel load services, is proposed. A multi-loop Energy Management System (EMS) based on proportional–integral control (PI) is developed to coordinate the interconnections of the power sources in real time. In contrast to the widely reported model predictive or artificial intelligence optimization schemes, the PI-derived EMS achieves similar power stability and hydrogen utilization efficiency with significantly reduced computational overhead and full marine suitability. By taking advantage of the high solar irradiance and coastal wind resources in Saudi Arabia, the proposed configuration provides continuous near-zero-emission operation. Simulation results show that the PEMFC accounts for about 90% of the total energy demand, the BESS (±0.4 MW, 2 MWh) accounts for about 3%, and the stationary renewables account for about 7%, which reduces the demand for hydro-gas to about 160 kg. The DC-bus voltage is kept within ±5% of its nominal value of 750 V, and the battery state of charge (SOC) is kept within 20% to 80%. Sensitivity analyses show that by varying renewable input by ±20%, diesel consumption is ±5%. These results demonstrate the system’s ability to meet International Maritime Organization (IMO) emission targets by delivering stable near-zero-emission operation, while achieving high hydrogen efficiency and grid stability with minimal computational cost. Consequently, the proposed system presents a realistic, certifiable, and regionally optimized roadmap for next-generation hybrid PEMFC–battery–renewable marine power systems in Saudi Arabian coastal operations.

The voltage source converters convert the DC to AC in order to interface distributed generation units with the utility grid, typically using an LCL filter to smooth the modulated wave. However, the LCL filter can introduce resonance, potentially cause instability, and necessitate the use of damping techniques, such as active damping, which utilizes feedback from the current control loop to suppress resonance. This paper presents a comprehensive performance assessment of four current-feedback-based active damping (AD) techniques—converter current feedback (CCF), CCF with capacitor current feedback (CCFAD), grid current feedback (GCF), and GCF with capacitor current feedback (GCFAD)—under a broad range of realistic grid disturbances and low switching frequency conditions. Unlike prior works that often analyze individual feedback strategies in isolation, this study highlights and compares their dynamic behavior, robustness, and total harmonic distortion (THD) in eight operational scenarios. The results reveal the severe instability of GCF in the absence of damping and the superior inherent damping property of CCF while demonstrating the comparable effectiveness of GCFAD. Moreover, a simplified yet robust design methodology for the LCL filter is proposed, enabling the filter to maintain stability and performance even under significant variations in grid impedance. Additionally, a sensitivity analysis of switching frequency variation is included. The findings offer valuable insights into selecting and implementing robust active damping methods for grid-connected converters operating at constrained switching frequencies. The effectiveness of the proposed methods has been validated through both MATLAB/Simulink simulations and hardware-in-the-loop (HIL) testing.

This paper proposes an advanced metering infrastructure (AMI)-informed hierarchical energy management framework for coordinated operation of electric vehicles (EVs), photovoltaic (PV) systems, and battery energy storage systems (BESS) in campus microgrids. The proposed two-layer architecture integrates a soft actor–critic (SAC) deep reinforcement learning (DRL) agent in the upper layer with a receding horizon model predictive control (MPC) optimizer in the lower layer. The key novelty is an AMI-to-control pipeline that transforms historical 15 min smart-meter measurements into operational flexibility features and embeds them into a hierarchical SAC–MPC architecture, where the DRL layer provides adaptive coordination and the MPC layer enforces grid, storage, and EV-service constraints. The proposed framework using the real-world Pecan Street data (15 min resolution) of 73 homes across Austin, Texas and California (2014–2019) achieves a 53.1% cost reduction and a 25.7% peak demand reduction when compared with uncontrolled charging, and the proposed framework outperforms MPC-only (50.9%), DRL-only (−5.2%), and rule-based (5.1%) baselines. The statistically significant contributions of network-aware constraints, demand-response activation, and predictive look-ahead horizon are statistically significant (n = 10 independent runs) contributions (p = 0.001). The state representation informed by AMI offers directional cost improvement (+8.4%, p = 0.055) with 11% faster convergence of training. The zero network constraint violation is observed in all evaluation scenarios and the average MPC solve time is around 150 ms, which is much less than the 15 min sampling period. Sensitivity analyses show that the hierarchical DRL–MPC architecture remains computationally feasible across EV penetration, seasonal, and forecast-uncertainty scenarios. However, BESS provided no net economic benefit under the evaluated energy-only TOU tariff, increasing weekly cost by $15.25 and peak grid demand by 14.2 kW. Break-even analysis indicates that demand charges of approximately $9.9/kW per month are required for BESS to become cost-effective in the proxy system, highlighting that storage value depends strongly on tariff design and peak-demand objective formulation.