Power Production Losses Research Articles

Multiscale multiphysics modeling of ammonia-fueled solid oxide fuel cell: Effects of temperature and pre-cracking on reliability and performance of stack and system

Ammonia is a promising carbon-free fuel for solid oxide fuel cells (SOFCs). However, direct feeding of ammonia into the SOFC may lead to serious degradation due to the nitriding. Conversely, the pre-cracking of ammonia introduces complexity to the system design and causes increased power losses in the system. Therefore, it is crucial to explore all these aspects simultaneously. In this context, this study introduces a novel multiscale modeling approach by integrating a 3D multiphysics simulation of the ammonia-fueled SOFC stack with system-level modeling to investigate the reliability and performance of the stack and system. Two different cell technologies developed for low temperature (LT) and high temperature (HT) operation are investigated at LT (600 – 700°C) and HT (700 – 800°C) ranges. The results indicate that fuel inlet temperature should be 55°C and 18°C higher than the minimum temperature in 0% pre-cracking case for HT and LT cases, respectively. The increase in the required air flow rate for cooling in the 100% pre-cracking case compared to the 0% pre-cracking case is around 100% and 216% for the HT and LT cases, respectively. However, stack power production and power losses in the system components are comparable for LT and HT cases which leads to similar system performance. A larger share of the active area is affected by nitriding in LT cases than HT ones. However, a smaller cracking ratio at LT (∼ 82%) compared to HT conditions (∼ 92%) is needed for elimination of nitriding. While the LT and HT cases are comparable in terms of system power production, the lower stack outlet temperatures in LT cases require novel and more expensive catalysts for ammonia pre-cracking and HT cases need more expensive steels.

Persons with Unilateral Transtibial Amputations Modulate Ipsilateral Hip and Contralateral Ankle Joint Work to Accelerate and Decelerate Walking

ABSTRACT Introduction Loss of power production at the ankle joint contributes to many problems people with unilateral transtibial (UTT) amputation experience during walking. Little is known about walking acceleration and deceleration, which is common in daily living and may require substantial compensatory behaviors from the residual lower-limb joints. Objective The aim of this study was to quantify individual lower-limb joint contributions to walking acceleration and deceleration in people with UTT amputations. We hypothesized that joint work on the prosthetic limb would be primarily modulated at the hip, and joint work on the sound limb would be primarily modulated at the ankle. Study Design The study is a repeated-measures design. Methods Six K3 level ambulators with UTT amputations participated. Participants performed a total of 40 walking trials while wearing their own nonarticulated dynamic prosthetic foot and socket. Each trial consisted of walking along a straight walkway. After walking approximately 2 m, participants received a cue instructing them to perform one of three walking conditions: continue walking at a constant average velocity, rapidly accelerate, or rapidly decelerate. We used ground reaction forces and motion capture data to derive joint kinematics and kinetics during the three walking conditions. We used one-way repeated-measures analyses of variance (ANOVAs) to identify significant differences between conditions. Results For the sound limb, positive hip and ankle work was significantly greater during acceleration compared with constant average velocity or deceleration conditions, and negative knee work was significantly greater during acceleration compared with deceleration. For the prosthetic limb, negative ankle work was significantly greater during acceleration compared with deceleration. Conclusions People with UTT amputation who use nonarticulated prostheses primarily modulated joint work on their sound limb to accelerate or decelerate walking speed. Clinical Relevance Characterizing compensatory behaviors of people with a UTT amputation is important for understanding injury mechanisms, informing clinical guidelines, and improving future ankle-foot prosthesis designs.

Electricity power production, transmission and distribution losses in Ghana: the role of regulatory quality

ABSTRACT Ghana faces annual productivity losses of $320–$924 million due to electricity crises, impacting GDP by 2%-6% and stifling economic growth with over 5% power losses. The study, therefore, utilized time series data to explore the relationship between electricity production, transmission, and distribution losses in Ghana from 1983–2018, specifically focusing on the role of regulatory quality in this relationship. Using statistical tests like Philip-Perron and Augmented Dickey-Fuller, the study confirmed cointegration among the variables. The Autoregressive Distributed Lag model was then employed, analyzing data from 1983 to 2018. The research compared a base model with variables affecting electricity losses to an extended model that incorporated Institutions and their interaction with electricity production. The study reveals that improving regulatory quality and institutional strength significantly reduces electricity losses in Ghana, highlighting the need for strategic policies to enhance efficiency and reliability in the electricity sector. Results also showed that the labor force had a positive impact on losses, while economic growth and electricity production had a negative effect. Foreign direct investment and gross fixed capital formation were not significant. The study’s short-term findings confirmed these relationships. The inclusion of Institutions maintained similar signs and significance in variables except for foreign direct investment. The study recommends enhancing institutional quality, attracting more FDI into the energy sector, and implementing targeted measures to manage the labor force’s impact on electricity demand and losses.

Power Production, Inter- and Intra-Array Wake Losses from the U.S. East Coast Offshore Wind Energy Lease Areas

There is an urgent need to develop accurate predictions of power production, wake losses and array–array interactions from multi-GW offshore wind farms in order to enable developments that maximize power benefits, minimize levelized cost of energy and reduce investment uncertainty. New, climatologically representative simulations with the Weather Research and Forecasting (WRF) model are presented and analyzed to address these research needs with a specific focus on offshore wind energy lease areas along the U.S. east coast. These, uniquely detailed, simulations are designed to quantify important sources of wake-loss projection uncertainty. They sample across different wind turbine deployment scenarios and thus span the range of plausible installed capacity densities (ICDs) and also include two wind farm parameterizations (WFPs; Fitch and explicit wake parameterization (EWP)) and consider the precise WRF model release used. System-wide mean capacity factors for ICDs of 3.5 to 6.0 MWkm−2 range from 39 to 45% based on output from Fitch and 50 to 55% from EWP. Wake losses are 27–37% (Fitch) and 11–19% (EWP). The discrepancy in CF and wake losses from the two WFPs derives from two linked effects. First, EWP generates a weaker ‘deep array effect’ within the largest wind farm cluster (area of 3675 km2), though both parameterizations indicate substantial within-array wake losses. If 15 MW wind turbines are deployed at an ICD of 6 MWkm−2 the most heavily waked wind turbines generate an average of only 32–35% of the power of those that experience the freestream (undisturbed) flow. Nevertheless, there is no evidence for saturation of the resource. The wind power density (electrical power generation per unit of surface area) increases with ICD and lies between 2 and 3 Wm−2. Second, EWP also systematically generates smaller whole wind farm wakes. Sampling across all offshore wind energy lease areas and the range of ICD considered, the whole wind farm wake extent for a velocity deficit of 5% is 1.18 to 1.38 times larger in simulations with Fitch. Over three-quarters of the variability in normalized wake extents is attributable to variations in freestream wind speeds, turbulent kinetic energy and boundary layer depth. These dependencies on meteorological parameters allow for the development of computationally efficient emulators of wake extents from Fitch and EWP.

Low handgrip strength is associated with worse functional outcomes in long COVID

The diagnosis of long COVID is troublesome, even when functional limitations are present. Dynapenia is the loss of muscle strength and power production that is not caused by neurologic or muscular diseases, being mostly associated with changes in neurologic function and/or the intrinsic force-generating properties of skeletal muscle, which altogether, may partially explain the limitations seen in long COVID. This study aimed to identify the distribution and possible associations of dynapenia with functional assessments in patients with long COVID. A total of 113 patients with COVID-19 were evaluated by functional assessment 120 days post-acute severe disease. Body composition, respiratory muscle strength, spirometry, six-minute walk test (6MWT, meters), and hand-grip strength (HGS, Kilogram-force) were assessed. Dynapenia was defined as HGS < 30 Kgf (men), and < 20 Kgf (women). Twenty-five (22%) participants were dynapenic, presenting lower muscle mass (p < 0.001), worse forced expiratory volume in the first second (FEV1) (p = 0.0001), lower forced vital capacity (p < 0.001), and inspiratory (p = 0.007) and expiratory (p = 0.002) peek pressures, as well as worse 6MWT performance (p < 0.001). Dynapenia, independently of age, was associated with worse FEV1, maximal expiratory pressure (MEP), and 6MWT, (p < 0.001) outcomes. Patients with dynapenia had higher intensive care unit (ICU) admission rates (p = 0.01) and need for invasive mechanical ventilation (p = 0.007) during hospitalization. The HGS is a simple, reliable, and low-cost measurement that can be performed in outpatient clinics in low- and middle-income countries. Thus, HGS may be used as a proxy indicator of functional impairment in this population.

Effect of curtailment scenarios on the loads and lifetime of offshore wind turbine generator support structures

Curtailment is a known phenomenon for wind turbine operators of both onshore and offshore wind turbine generators (WTG). Curtailment refers to the situation in which the power output of all WTG’s within a windfarm is forced below the expected power output at the occurring environmental conditions. A direct consequence of curtailment is the loss of power production. In the present contribution further consequences of curtailment of an offshore wind farm (OWF) are studied from the perspective of the support structure, in specific the foundation. In relation to curtailment a couple of potentially critical operational conditions impacting the fatigue consumption of the support structure can be identified. Besides the standstill during operational windspeed conditions, in specific damaging for the +7MW generation WTG’s, curtailment introduces repeated transitions between operational conditions. Since transitions between operational conditions of a WTG are known to be a cause of high fatigue loads in the structural components of the WTG, their increased occurrence due to curtailment might also have an impact on the fatigue consumption of the support structure. With the growing interest of the industry to quantify and potentially optimize the structural lifetime consumption in view of potential lifetime extension of OWF assets, any potential fatigue damaging operational condition is to be investigated. The present work focusses on the investigation of the impact these transitional load cycles may have on the structural lifetime of the WTG foundation. To assess the impact on lifetime, the assessment of the damage equivalent loads (DEL) derived from structural health monitoring (SHM) data are used as a data-driven alternative for model-based load simulations. In the present work such data-driven lifetime assessment studies the impact of curtailment regimes with different frequency of stop and start cycles on the structural lifetime. The study is performed based on 1 year of SHM data collected from two OWF’s. The assessment demonstrates that the impact of additional transitional load cycles on the structural fatigue life consumption is to be considered when defining a long-term curtailment strategy for an OWF.

Automated Quantification of Wind Turbine Blade Leading Edge Erosion from Field Images

Wind turbine blade leading edge erosion is a major source of power production loss and early detection benefits optimization of repair strategies. Two machine learning (ML) models are developed and evaluated for automated quantification of the areal extent, morphology and nature (deep, shallow) of damage from field images. The supervised ML model employs convolutional neural networks (CNN) and learns features (specific types of damage) present in an annotated set of training images. The unsupervised approach aggregates pixel intensity thresholding with calculation of pixel-by-pixel shadow ratio (PTS) to independently identify features within images. The models are developed and tested using a dataset of 140 field images. The images sample across a range of blade orientation, aspect ratio, lighting and resolution. Each model (CNN v PTS) is applied to quantify the percent area of the visible blade that is damaged and classifies the damage into deep or shallow using only the images as input. Both models successfully identify approximately 65% of total damage area in the independent images, and both perform better at quantifying deep damage. The CNN is more successful at identifying shallow damage and exhibits better performance when applied to the images after they are preprocessed to a common blade orientation.

The Health Consequences of Power Outages - Electricity Load-Shedding Problem in Country

Electricity powers the economic system. Households need stable electricity since many tasks require it1. Pakistan had frequent power outages for decades. The monopolistic supplier used cyclical load shedding over many hours a day in much of the country to avoid unplanned blackouts and meet power demand due to power production losses. Load shedding occurs when power demand exceeds the supply2. Pakistan's major power resource for heating, cooking, and lighting is electricity, although load shedding's economic impacts are mostly highlighted due to the country's difficult economic circumstances. Health effects and expenses are poorly documented. This is concerning because hospital reports relate blackouts to health effects, such as excessive stress on already overburdened personnel after procedures2. For individuals who try to deal with electricity, unannounced load shedding is worse. Protesters block highways over power cuts. The police have confirmed lots of crime in big cities. Power interruptions disrupt industrial consumers' regular operations. Power failures shuttered tube wells and water pumps, affecting water supply and mills.3 Electrical network breakdowns raise hospitalizations, health problems, and death, while natural calamities and severe weather events which were followed by power outages, damaged the population's overall well-being by increasing emergency admissions4.

Effects of Atmospheric Icing on Performance of Controlled Wind Turbine

Icing deteriorates the performance of wind turbine rotors by changing the blade airfoils’ shapes. It decreases the lift, increases the drag, and subsequently causes power production losses and load increase on turbines’ structures. In the present study, the effects of atmospheric icing on the performance of a controlled large-scale wind turbine is estimated through simulations. To achieve the target, the MS (Mustafa Sahin) Bladed Wind Turbine Simulation Model is used for the analyses of the National Renewable Energy Laboratory (NREL) 5 MW turbine with and without iced blades. Icing modeling is realized based on its main characteristics and its effects on blade aerodynamics. Turbine performance estimations are carried out at various uniform wind speeds between cut-in and cut-out wind speeds and are presented in terms of various turbine parameters such as power, thrust force, blade pitch angle, and rotor speed. Simulation evaluations show that even a light ice accretion along the blades varies the turbine characteristics and dynamics, changes the cut-in and rated wind speeds, and affects the aforementioned turbine parameters differently in the below and above rated regions.

A Survey of the Quasi-3D Modeling of Wind Turbine Icing

Wind turbine icing has been the subject of intensive research over the past two decades, primarily focusing on applying computational fluid dynamics (CFD) to 2D airfoil simulations for parametric analysis. As a result of blades’ airfoils deformation caused by icing, wind turbines experience a considerable decrease in aerodynamic performance resulting in a substantial loss of productivity. Due to the phenomenon’s complexity and high computational costs, a fully 3D simulation of the entire iced-up rotating turbine becomes infeasible, especially when dealing with several scenarios under various operating and weather conditions. The Quasi-3D steady-state simulation is a practical alternative method to assess power loss resulting from ice accretion on wind turbine blades. To some extent, this approach has been employed in several published studies showing a capability to estimate performance degradation throughout the generation of power curves for both clean and iced wind turbines. In this paper, applying the Quasi-3D simulation method on wind turbine icing was subject to a survey and in-depth analysis based on a comprehensive literature review. The review examines the results of the vast majority of recently published studies that have addressed this approach, summarizing the findings and bringing together research in this area to conclude with clear facts and details that enhance research on the estimation of wind turbine annual power production loss due to icing.

Wind plant controls

The development of operational strategies for wind farms as an integrated plant system to achieve a variety of goals from elevating power production to reducing maintenance needs has generated a great deal of interest in recent years. Achieving these operational goals requires an estimate of the energy available and the wind conditions affecting each turbine. The importance of the aerodynamic interaction of wind turbines with the dynamic atmospheric resource means that wakes (the momentum deficit due to power extraction) and their interactions through the farm have the largest influence on the available energy. Predicting the influence of wakes and their interactions, therefore, form the basis of wind farm control strategies to reduce power production losses, track a power signal, mitigate structural loading, or balance the wear and tear on wind turbines to decrease operation and maintenance costs. The articles in the “Advances in Wind Plant Controls: Strategies, Implementation, and Validation” Special Topic in the Journal of Renewable and Sustainable Energy describe the further development and evaluation of wake models and new approaches to wake steering that exploit advances in sensing or estimation to improve control performance.

High-Fidelity Computational Fluid Dynamics Analysis of In-Serviced Shrouded High-Pressure Turbine Rotor Blades

Abstract In-service deterioration can lead to undesired shape variations on high-pressure turbine rotor blades. This can have a significant impact on efficiency, power generation, and component life. Loss of power production from the high-pressure turbine rotor causes engine over-throttling to compensate for the lower performance. This will in turn worsen the operating conditions and ultimately reduce the life of the component. The aim of this study is to provide a high-fidelity flow simulation of in-serviced shrouded high-pressure turbine (HPT) blades of a modern Jet Engine. Shape variation effects on the aerodynamic performance of several shrouded HPT blades with a different number of in-service hours have been investigated. In order to establish a digital model of the shape variation, a novel reverse-engineering procedure is carried out to come up with a parametrized definition of each blade's variations from nominal including any observable damage. The investigation is conducted by means of an in-house, full 3D steady-state Reynolds-averaged Navier–Stokes (RANS) simulation of the flow around a series of damaged rotor blade geometries, which are obtained through high-resolution optical blue-light “Gesellschaft für Optische Messtechnik” (GOM) scans. The analysis shows that the aerodynamic performance of the HPT rotor blades under investigation is primarily sensitive to shroud damage, which is found to account for efficiency losses often greater than 3%, and for more than 80% of the total performance loss. A secondary role on efficiency is found to be played by the blade shape deviation. A highly linear correlation is found between HPT stage efficiency and a combination of shroud damage parameters.

Design and implementation of Evaporative Cooler Automation system at Erbil/Perdawd Power Plant

The Automation design and implementation of any industrial system are very complex pieces of technology. Many systems and components work simultaneously to fulfil a significant operation and control of the system process. The existing evaporative cooler system panel is based on the conventional relay system and has many drawbacks. It takes time and is difficult for people to reach; it could endanger human life and damage machinery. It operates entirely manually and has little to no remote capabilities. Any harm or failure to the electrical panel, the motors, or the instrumentation results in a system shutdown and a loss of power production without giving the control room any prior notice. An automated control system is the natural next step for such a system to eradicate these problems. The Proposal is to implement an automation system designed and implemented by using S7- 1215C Siemens CPU for controlling and WinCC RT advanced as HMI and SCADA approach for monitoring. The programming software is Totally integrated Automation (TIA) Portal V15 software and is used for monitoring the configuration file. Programming style is the ladder while web-server capabilities are initialized for using the wireless protocol with mobile device App S7 for operating and monitoring the system. This paper proposed an innovative automation design and implementation for the gas turbine evaporative cooler system at Erbil/Perdawd combined cycle power plant. The experimental results show that the proposed embedded automation control system is very flexible and simple for controlling and monitoring the evaporative cooler.

Diurnal impact of atmospheric stability on inter-farm wake and power generation efficiency at neighboring onshore wind farms in complex terrain

Enhancing the power production efficiency of large-scale wind farms is challenging for onshore wind power due to the variability of atmospheric conditions. This work aims to study the impact of atmospheric stability on the inter-farm wake pattern, topographic effect, and power production changes at two neighboring wind farms in Hami City, Xinjiang of China over complex terrain. The results show a discernible diurnal cycle property. At night in a stable layer with hindered mixing, the inter-farm wake persists around 20 km downstream, and the greatest relative wind deficit increases by 8%. However, during the daytime unstable layer with elevated turbulence, shows a limited deficit and recovers about 6 km downstream. Accordingly, a mean relative power production reduction of 17% is subjected to the downwind farm at night, about a factor of 3 greater than that at daytime, when the mean value is only 6%. Interestingly, the largest power production losses are experienced with a larger range between maximum and minimum before dawn and after dusk due to the notable inter-farm wake with a streaky structure related to the large coherent buoyant caused by the tendency of heat flux over the complex terrain. Moreover, the topographic speed-up in the stable layer outperforms that in unstable conditions.

Effect of erosion morphology on wind turbine production losses

The impact of wind turbine (WT) blade erosion is still a major issue today because of the associated high maintenance costs and the loss of power production. The erosion process is influenced by many physical phenomena that still need to be understood better. Especially WT manufactures and owners need to know the potential impact of different levels of blade erosion on annual energy production (AEP). The damage produced by erosion modifies the aerofoil shape and therefore its aerodynamic properties, resulting in an AEP drop. In this study, the effect of various morphologies of erosion on AEP was obtained. First, a 3D characterisation of eroded blades using a laser scanner was performed. The erosion damages were grouped into two typologies: Typology 1 covers pits and gouges, and Typology 2 covers extended loss of top coat. Based on this, 2D section geometries were defined to evaluate the effect of erosion on the aerofoil aerodynamic 2D properties, which was done using the CFD code WMB. The aerofoil used as a reference was DU96W180. It was determined that the erosion damage alters the aerodynamic behaviour of the aerofoil by reducing the Cl max and the slope of the Cl- α curve, which resulted in a drop of the aerodynamic efficiency from 40% to 72%. These detrimental effects increased depending on the damage location (i.e., pressure side and closeness to the leading edge), damage size and shape (i.e., sharp transitions from the eroded to non-eroded surfaces). To evaluate the erosion effect on the AEP, the NREL 5 MW WT was selected. All its components were kept except the last 30% outer section of the 61.5 m blade whose NACA64_A17 aerofoil was replaced by a DU96W180. The erosion damages were modelled by extending the 2D eroded geometry along this outer section. The AEP was calculated using BLADED 4.5. It was concluded that erosion resulted in a decrease of the AEP, which can be up to 1% and 6% for damages of Typology 1 and 2, respectively. This study will help to standardize and estimate the effect of the type of erosion on AEP losses for different shapes and erosion typologies.

Effect of blade contamination on power production of wind turbines

Wind turbines suffer from considerable power losses because of contamination on their blades, that can be due to erosion, wear, smog, insect, sand and dust particle impact. Blade contamination, its effects on the flows over the wind turbine blades and consequent power production losses form the main focus of the present study. These effects are mainly due to increased roughness on the blades leading to earlier laminar-turbulent transition and consequently, thicker boundary-layers on the blades. Early laminar-turbulent transition leads to a larger part of the flow over a blade being turbulent, thus increasing skin friction drag. Thicker boundary-layer on a blade results in blade profile being effectively modified, rendering the flow over the blade depart from ideal. In the present study, the effects of blade contamination on power output of contaminated wind turbine blades is investigated numerically using an in-house computational tool. Blade Element Momentum Method (BEM) combined with the Panel Method is used to calculate the local velocity and angle of attack at the blade sections, together with the power produced by the blade. Trajectories of particles causing contamination are calculated using Lagrangian approach, also yielding the impingement pattern of the particles on the blade surface, i.e. particle collection efficiency distribution. The effects of roughness on the boundary-layer flow are investigated by using an Integral Boundary-Layer Method, which yields the characteristics of the boundary-layer, i.e. laminar-turbulent transition location, increased skin-friction and thickening of the boundary-layer. The blade shape is modified due contamination thickness, the local height of which is assumed to be proportional to the local collection efficiency. Also, the roughness height distribution used in the boundary-layer calculations is assumed to be equal to the contamination thickness distribution on the blades. Power production and consequent losses of wind turbines with contaminated wind turbine blades are studied with respect to variations in particle size, wind speed and roughness height.

Failure prediction of turbines using machine learning algorithms

Wind energy has become a significant component of the new trend, with wind turbines being frequently used to generate electricity. In recent decades, a number of big and small wind farms have been built in many nations as a part of the global push to increase the production of hygienic energy from sources of renewable energy. Failure of wind turbines will adversely affect the power production. In recent years, various analysis is conducted to understand the failure of turbines. Here, machine learning model approach is used to guess the failure of wind turbines. This model will help the engineering team to forecast the failure of turbines. Based on that, business activity and planning can be made to prevent power production loss. A model has been designed using Random Forest Algorithm and Extreme Gradient Boost algorithm (XGBOOST). On comparing Bias and Scores in the Receiver Operating Characteristic curve of both the algorithm, Random Forest algorithm gives the best result when compared to XGBoost algorithm.

Aerodynamic shape optimization of wind turbine blades for minimizing power production losses due to icing

Ice formation on a wind turbine alters the airfoil profiles of the blades and causes degradation in the aerodynamic performance of the wind turbine and the resulting power production losses. Since the blade profile plays a significant role in the icing of a blade, power production losses due to icing can be minimized by optimizing the blade profile against icing. In this study, blade profiles are optimized in order to minimize power production losses. A Gradient based aerodynamic shape optimization method is developed together with the Blade Element Momentum method and an ice accretion prediction tool in order to minimize the power production losses of horizontal axis wind turbines under various icing conditions. In an optimization study performed for the Aeolos-H 30 kW and NREL 5 MW wind turbines exposed to icing conditions up to 1 h, the power loss due to icing is reduced by about 4%.

A field study of ice accretion and its effects on the power production of utility-scale wind turbines

A field study was conducted to examine ice accretion on 50-m-long turbine blades and icing-induced power production losses to multi-megawatt wind turbines. An unmanned-aerial-system equipped with a digital camera was deployed to take images of the ice structures on turbine blades after undergoing a 30-hour-long icing event to quantify the ice thickness accreted along blade leading edges. While ice accreted over entire blade spans, more ice was found to accrete on outboard blades with the ice thickness reaching up to 0.3 m near blade tips. Based on the icing similarity concept and blade element momentum theory, a theoretical analysis was performed to predict the ice thickness distributions on turbine blades. The theoretical predictions were found to agree with the field measurements well in general. Turbine operation status during the icing event was monitored by using turbine supervisory control and data acquisition (SCADA) systems. Despite the high wind, iced wind turbines were found to rotate much slower and even shut down frequently during the icing event, with the icing-induced power loss being up to 80%. The present study aims to fill in the knowledge gaps between the fundamental icing physics studies conducted under idealized lab conditions and complex wind turbine icing phenomena under realistic, natural icing conditions.

Peer Review of Renewable Energy-based Adaptive Protection(s) &amp; Relay Coordination Optimization Techniques

Background: Distributed Sustainable Energy Generation (DSEG) has become a leading trend in modern R&amp;D to achieve practical, financial, and environmental benefits. With respect to the power system, the benefits are minimization of power failures, enhancement of energy quality &amp; reliability, congestion relief, and smart/micro grid demand response. The widespread use of modern technologies encourages the use of DSEG for safe power production and power loss reduction. Besides, it also poses new challenges such as optimal placement of relays, protection device settings, and voltage control problems in power systems. : Among various solutions reported in the literature, a widely accepted solution seems to be the deployment of Fault Current Limiter (FCL) to minimize DSEG impacts. However, FCLs are an expensive option to restore relay coordination. The adaptive protection scheme provides benefits to the smart grid's advanced features and serves as an efficient solution to address new DSEG and FCL challenges. Objective: This paper presents an extensive review of the effect of DSEG on distribution systems from the safety point of view, different optimization techniques used for adaptive protections, optimal relay coordination, and merits &amp; demerits of FCL. Methods: The paper discusses various recent optimization and hybrid optimization techniques used for solving the Optimal Relay Coordination model (ORC). Adaptive and FCL based non-adaptive techniques are also discussed to solve this model. An attempt has also been made to present a comparative study of various optimization techniques in tabular form, considering different bus models and their outcomes. Conclusion: Comparative study of these techniques shows that Water cycle optimization, hybrid whale-GWO and GSA-SQP algorithms give better results in solving the ORC problem. FCL based non-adaptive technique was found better as compared with adaptive techniques because a greater number of DGs can be integrated on a grid with less complexity.