Changes In Wind Speed Research Articles

On the Mechanisms Driving Latent Heat Flux Variations in the Northwest Tropical Atlantic

AbstractThe Northwest Tropical Atlantic (NWTA) is a region of complex surface ocean circulation. The most prominent feature is the North Brazil Current (NBC) and its retroflection at 8°N, which leads to the formation of numerous mesoscale eddies known as NBC rings. The NWTA also receives the outflow of the Amazon River, generating freshwater plumes that can extend up to 100,000 km2. We show that these two processes influence the spatial variability of the region's surface latent heat flux (LHF). On the one hand, the presence of surface freshwater modifies the vertical stratification of the ocean, the mixed layer heat budget, and thus the air‐sea heat exchanges. On the other hand, NBC rings create a highly heterogeneous mesoscale sea surface temperature (SST) field that directly influences the near‐surface atmospheric circulation. These effects are illustrated by observations from the ElUcidating the RolE of Cloud‐Circulation Coupling in ClimAte ‐ Ocean Atmosphere (EUREC4A‐OA) and Atlantic Tradewind Ocean‐Atmosphere Interaction Campaign (ATOMIC) experiments, satellite and reanalysis data. We decompose the LHF budget into several terms controlled by different atmospheric and oceanic processes to identify the mechanisms leading to LHF changes. We find LHF variations of up to 160 W m2, of which 100 W m2 are associated with wind speed changes and 40 W m2 with SST variations. Surface currents or heat release associated with stratification changes remain as second‐order contributions with LHF variations of less than 10 W m2 each. This study highlights the importance of considering these three components to properly characterize LHF variability at different spatial scales, although it is limited by the scarcity of collocated observations.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part II: Sensitivity of Surface Wind Speeds to Model Resolution and Physics

Abstract Strong wind events can cause severe economic loss and societal impacts. Peak winds over Wyoming and Colorado occur during the wintertime months, and in the first part of this two-part series, it was shown that the High-Resolution Rapid Refresh (HRRR) model displays large negative biases with respect to strong wind events. In this part of the study, we address two questions: 1) does increasing the horizontal resolution improve the representation of strong wind events over this region, and 2) are the biases in HRRR-forecasted winds related to the selected planetary boundary layer (PBL), surface layer (SL), and/or land surface model (LSM) parameterizations? We conduct Weather Research and Forecasting (WRF) Model simulations to address these two main questions. Increasing the horizontal resolution leads to a small improvement in the simulation of strong wind speeds over the complex terrain of Wyoming and Colorado. In general, changes in the PBL, SL, and LSM parameterizations show much larger changes in simulated wind speeds compared to increasing the model resolution alone. Specifically, changing from the Mellor–Yamada–Nakanishi–Niino scheme to the Mellor–Yamada–Janjić PBL and SL schemes results in nearly no change in the r2 values, but there is a decrease in the magnitude of the strong wind speed bias (from −12.52 to −10.16 m s−1). We attribute these differences to differences in the diagnosis of surface wind speeds and mixing in the boundary layer. Further analysis is conducted to determine the value of 1-km forecasts of strong winds compared with wind speed diagnostics commonly used by the National Weather Service. Significance Statement Motivated by prior studies showing low skill in the prediction of strong winds using state-of-the-art weather forecast models, in this study, we aim to investigate two questions: 1) does increasing the horizontal resolution improve the prediction of strong wind events over the complex terrain of Wyoming and Colorado, and 2) are the biases in High-Resolution Rapid Refresh (HRRR) forecasted winds related to the selected planetary boundary layer, surface layer, and/or land surface model parameterizations? We find that increasing the horizontal resolution provides a slight improvement in the prediction of strong winds. Further, considerable improvement in the prediction of strong winds is found for varying boundary layer, surface layer, and land surface parameterizations.

Wake measurement of wind turbine under yawed conditions using UAV anemometry system

This study employs a UAV anemometry system to assess the wind field around a yawed wind turbine, particularly focusing on its wake during operational conditions. The research findings reveal that the evolution of wind turbine wakes follows distinct patterns at various downstream distances. Turbulence intensity notably amplifies within regions characterized by significant fluctuations in mean wind speed. Specifically, in yawed conditions, the areas with the highest turbulence generated by the rotor coincide with zones exhibiting pronounced variations in mean wind speed. The heightened turbulence within the wake region to some extent constrains the safety and economic viability of wind farms. Turbulence intensity increases significantly in the region where the average wind speed changes greatly, that is, under the yaw state of the wind turbine, this region is characterized with the strongest turbulence generated by the rotor. The UAV anemometry system's wind speed assessment closely matches predictions from the Y-3DJGF model, accounting for wake experience coefficient adjustments. Furthermore, in yaw conditions, the wind turbine's wake trajectory exhibits some deviation from the incident flow's direction, with an initial increase in slope followed by gradual stabilization. As the downstream distance increases, the trajectory will eventually establish a consistent trend with the incident flow. The cost-effective and flexible UAV anemometry system enhances wind field measurements, offering an innovative approach for wind energy sector research and engineering.

Passive cooling and thermal comfort performance of Passive Downdraught Evaporative Cooling (PDEC) towers in a Saudi library: An on-site study

In the hot arid climate of Saudi Arabia, where air conditioning, primarily fueled by fossil fuels, accounts for a significant portion of energy consumption, the implementation of Passive Downdraught Evaporative Cooling (PDEC) towers presents a sustainable solution. This study conducts an extensive evaluation of PDEC towers in a public library, focusing on their effectiveness in reducing reliance on conventional cooling and enhancing thermal comfort. Through detailed field measurements, the study examines the influence of wind speed on the towers' cooling performance, correlating it with internal environmental conditions. The research extends to a comparative analysis of two prominent thermal comfort models: the Predicted Mean Vote (PMV) and the Adaptive Thermal Comfort (ATC) model. Findings indicate a notable interaction between wind speed and indoor air temperature, where increased wind speeds correspond to higher indoor temperatures. Despite this, the PDEC towers demonstrate a significant reduction in temperature, maintaining cooling effectiveness between 70 % and 75 %. The comparative study of thermal comfort models reveals that the ATC model provides a more relevant assessment of comfort levels in naturally ventilated spaces, with 71 % of the recorded temperatures falling within the comfortable range during the monitoring period. The research highlights the PDEC tower's potential in delivering effective passive cooling, adaptable to wind speed changes, and contributing to a sustainable and energy-efficient building environment in hot arid climates.

The Short-Term Price Elasticity, Temperature Elasticity, and Wind Speed Elasticity of Electricity: A Case Study from Norway

Energy production using hydropower has a 150-year history in Norway. High mountains, lots of rain, and a well-developed technology laid the foundation for low and stable electricity prices. The Norwegian electricity market is unique and different from any other country. Nearly all electricity produced (98.3 percent) comes from renewable energy sources and 75 percent of the energy used for heating is electricity. From autumn 2020, major changes have been observed in the electricity market in Norway. In 2021, Norway opened two transmission cables, one to Germany and one to England. Both cables have a capacity of 1400 MW. The average price per MWh was NOK 263 in southern Norway in the period 2013–2020, which more than quadrupled to NOK 1192 per MWh in the period 2021–2023. We have investigated how the market reacted to the large price increase. We found that price elasticity is low even when the price is very high. It is the temperature that controls the consumption. When it is cold—below zero degrees Celcius—the temperature elasticity is close to zero; the temperature elasticity is not constant. When the temperature is above zero, the temperature elasticity is about −0.7. Price variations or changes in wind speed only lead to minor adjustments in electricity consumption. It is the variations in temperature that result in the observable fluctuations in electricity consumption. Since Norway exports electricity to Sweden, Denmark, Finland, Germany, the Netherlands, and England, knowledge of the Norwegian electricity market is relevant for many market participants. The Norwegian electricity market differs from those in other countries. Therefore, there is a risk that conclusions drawn about the Norwegian electricity market based on research conducted in other countries may be incorrect or inaccurate. Our contribution with this case study is to deepen the knowledge of how the electricity market in Norway operates.

Variability and trends of near-surface wind speed over the Tibetan Plateau: The role played by the westerly and Asian monsoon

Near-surface wind speed exerts profound impacts on many environmental issues, while the long-term (≥60 years) trend and multidecadal variability in the wind speed and its underlying causes in global high-elevation and mountainous areas (e.g., Tibetan Plateau) remain largely unknown. Here, by examining homogenized wind speed data from 104 meteorological stations over the Tibetan Plateau for 1961–2020 and ERA5 reanalysis datasets, we investigated the variability and long-term trend in the near-surface wind speed and revealed the role played by the westerly and Asian monsoon. The results show that the homogenized annual wind speed displays a decreasing trend (−0.091 m s−1 per decade, p < 0.05), with the strongest in spring (−0.131 m s−1 per decade, p < 0.05), and the weakest in autumn (−0.071 m s−1 per decade, p < 0.05). There is a distinct multidecadal variability of wind speed, which manifested in an prominent increase in 1961–1970, a sustained decrease in 1970–2002, and a consistent increase in 2002–2020. The observed decadal variations are likely linked to large-scale atmospheric circulation, and the correlation analysis unveiled a more important role of westerly and East Asian winter monsoon in modulating near-surface wind changes over the Tibetan Plateau. The potential physical processes associated with westerly and Asian monsoon changes are in concordance with wind speed change, in terms of overall weakened horizontal air flow (i.e., geostrophic wind speed), declined vertical thermal and dynamic momentum transfer (i.e., atmospheric stratification thermal instability and vertical wind shear), and varied Tibetan Plateau vortices. This indicates that to varying degrees these processes may have contributed to the changes in near-surface wind speed over the Tibetan Plateau. This study has implications for wind power production and soil wind erosion prevention in the Tibetan Plateau.

Effects of wind-induced static angle of attack on flutter performance of long-span bridges using 2D bimodal and 3D multimodal analysis

Flutter performance of long span bridges is directly affected by winds featured with large angles of attack (AoAs) in typhon climates and mountainous areas. Flutter critical wind speed and flutter derivatives (FDs) of a streamlined closed-box girder under various initial AoAs are obtained by free and forced vibration wind tunnel tests of a section model, based on which the two-dimensional(2D) and three-dimensional (3D) flutter performance and evolution mechanisms are further investigated. The results indicate that FDs identified at small vibration amplitudes through different forced vibration control methods, i.e., fixing wind speed or vibration frequency, in wind axis or body axis are almost identical. The flutter performance of the closed-box girder is susceptible to the AoA. The flutter critical wind speed changes significantly with the initial AoA due to the nonlinear variation of some typical FDs. The sign of A2* shifts from negative to positive and the reduced wind speed associated with the sign change becomes lower as the initial AoA increases, which worsens the flutter performance. The flutter critical wind speed would significantly decrease because of the consideration of the static additional AoA in the range of positive initial AoA. In addition, the participation of multi modes and different longitudinal distribution of static additional AoA are taken into consideration in 3D numerical analysis, which have little influence on the flutter critical wind speed of long span bridges between the 2D and 3D numerical analysis.

Attribution of Terrestrial Near‐Surface Wind Speed Changes Across China at a Centennial Scale

AbstractNear‐surface wind speed (NSWS) over China shows multiple time‐scale changes at a centennial scale, but the contributions of internal variability (IV), anthropogenic forcing (ANT), and natural forcing (NAT) to those changes remain unknown. This study investigated the contributions of IV, ANT, and NAT to NSWS changes at a centennial scale. Results show that the NSWS changes were attributed mainly to IV. IV not only modulated the interannual changes in NSWS but also determined the interdecadal transition in NSWS. The relative contributions of IV to the interannual and decadal NSWS exceeded 75.0%. ANT contributed particularly to the long‐term reduction in NSWS; especially, it has contributed 55.0% of the reduction in NSWS since 1957, serving as the major contributor to the reduction in NSWS. NAT had a small‐to‐negligible effect on China's NSWS throughout the study period. This study enhances our understanding of NSWS changes at different time scales.

Achieving green mobility: Multi-objective optimization for sustainable electric vehicle charging

This study optimizes and evaluates a Photovoltaic-Wind-Battery/Electric Vehicle Charging Station (PVWB/EVCS) system using four Multi-Objective Optimization (MOO) techniques: MOPSO, NSGAII, NSGAIII, and MOEA/D. The main goals are to minimize the Total Net Present Cost (TNPC) and Loss of Power Supply Probability (LPSP) of the system, which are crucial for sustainable electric vehicle charging. The study analyzes the economic, operational, and sustainability aspects of the optimized system and compares it with HOMER software. The results show that NSGA-II is the best MOO technique for this problem, as it has the best performance and robustness. The Discounted Cash Flow analysis confirms the economic feasibility and sustainability of the optimized system over its lifetime. The technical analysis demonstrates the system's ability to use renewable energy from solar and wind sources, along with efficient energy storage and distribution. The study also conducts a sensitivity analysis to investigate the effects of changes in load, irradiance, wind speed, and component costs on the system performance. The findings reveal the system's resilience and adaptability under different scenarios, thus enhancing its suitability for renewable energy generation and electric vehicle charging. The study showed that the optimized PVWB/EVCS system is a promising solution for reducing reliance on non-renewable sources and promoting a more eco-friendly sustainable future.

Response spectrum-based analysis of airborne radar random vibration and multi-point control improvement

During the flight of a UAV (unmanned aerial vehicle), the LiDAR device undergoes random vibrations due to the changing flight attitude and wind speed conditions of the UAV. It is important to control the frequency and amplitude of the vibrations within a reasonable range by means of a damping structure. As the vibrations caused by various factors during flight are random and non-linear, this paper innovates the analysis principle and damping control means for the random vibrations of airborne optoelectronic devices. The response spectrum analysis theory is used to establish the shock response spectrum, and an optimised and improved recursive digital filtering method is used to fit the frequencies of random vibration to the synthetic shock response. Considering the uncertainty of the vibration excitation signal, a virtual excitation method is used for the first time to simulate the random vibration to which the radar may be subjected in the air, and to simplify the calculation steps. The shock plate structure is designed using a multi-point control method to innovate a passive response to the random excitation. Finally, a modal analysis of the synthesised impact response was carried out. It is verified that the first six modal frequencies are controlled within 220 Hz, realising the frequency reduction. The amplitude of the three x, y, and z directions is controlled to within 0.5 mm, thus achieving vibration damping.

Studies on the Experimental Measurement of the Low-Frequency Aerodynamic Noise of Large Wind Turbines

With the continuous warming of the global climate, expanding the use of renewable energy has become one of the main social responsibilities. However, as the number of installed wind turbines and their physical dimensions continue to increase, the issue of generated noise has become increasingly significant in influencing the acceptance and endorsement of wind power projects by neighboring communities. In this paper, we investigated the noise generated by two wind turbine units with rated powers of 1.5 MW and 4.5 MW and analyzed the variations in low-frequency noise during their operation and shutdown periods. This research shows that the power of a single unit has a significant impact on the low-frequency noise emitted into the environment. Compared with 1.5 MW wind turbines, 4.5 MW wind turbines generate more low-frequency noise when operating at the same wind speed. Further analysis of the narrowband frequency spectra and one-third octave spectra of the measured noise indicates that the low-frequency noise from the 4.5 MW wind turbine increases significantly in the range of approximately 80 Hz to 300 Hz, with more pronounced variations below 250 Hz corresponding to changes in wind speed. However, the overall variations in low-frequency noise with wind speed are not as notable as those observed for the 1.5 MW wind turbine. Due to the relatively weak attenuation of low-frequency noise in the atmosphere, the higher low-frequency content of large wind turbines may cause more distress to residents near wind farms. The result of this study emphasizes that in the planning and design of wind power projects, in addition to considering the efficiency of single-unit power generation and the contribution of renewable energy, it is also necessary to pay full attention to noise emission issues to ensure that the project is widely supported and accepted in the community.

Deterioration of steel structures due to corrosion considering the global effects of climate change

The randomness of atmospheric conditions is among the key contributing factors that affect the ability to accurately predict the corrosion growth in steel structures. Climate change has the potential to alter the long-term characteristics of these factors over the lifespan of steel structures, both those already existing and those newly built. The impact of climate variability on the stochastic nature of atmospheric variables, which greatly influence corrosion conditions, can add complexity to corrosion predictions in these structures. This paper introduces an integrated framework to quantify the impact of climate change on corrosion rates of steel structures worldwide. It considers the changes in environmental conditions, specifically temperature, relative humidity and wind speed and their effects on atmospheric corrosion. Global Climate Models are employed to evaluate the long-term impacts of climate change on these environmental conditions. An analytical model for predicting corrosion rate is integrated with climate change models to predict alterations in the corrosion rates of steel components relative to historical conditions. This paper also discusses the impact of climate change on the variations of these climatic parameters and offers a comparison between historical data and projected conditions across the globe. The results indicate that the effect of climate change on the corrosion rate depends on the considered region. While regions such as Australia, North America and Europe see an increase, others such as Asia and Africa observe a decline. Notably, all oceans, especially the Antarctic and Arctic, experience a significant increase in corrosion by the end of the century.

Establishing and modeling the causality relationship of hydro-climatic and land cover change variables with water quality over Lake Tana, Ethiopia

Lakes, the most widespread inland water bodies in the globe, are highly susceptible to change in trophic state due to external factors. Changing hydro-climatic conditions and land cover changes (LCC) can cause lake water quality deterioration. This study establishes the quantitative relationship between variability in the water quality index and changes in hydro-climatic and LCC variables. Water quality is represented by the Forel-ule index (FUI) whereas the hydro-climatic variables considered in this study are lake bottom layer temperature (lblt), lake total layer temperature (ltlt), precipitation, runoff, evaporation, lake skin temperature (lskt), surface wind speed and air temperature. The LCC is quantified by lower and higher level leaf area index (Lv-lai and Hv-lai). FUI has a positive relationship with surface wind speed, precipitation, runoff, ltlt, lblt, and LCC and a negative relationship with evaporation, lskt, and air temperature with 95% confidence level over most parts of the Lake. The temporal correlation is also apparent from the long-term trend pattern. A significant decreasing trend is observed in FUI and lake bottom layer temperature (lblt). In contrast, an insignificant increasing trend is observed in air temperature and lake skin temperature (lskt). The changes in LCC, runoff, precipitation, and surface wind speed is insignificant between 2000 and 2020. Moreover, the phase composites of FUI and hydro-climatic and LCC variables derived from multichannel singular spectrum analysis (MSSA) show strong seasonal modulation of water quality by hydro-climatic and LCC variables. The annual cycle represented by the first two eigenmodes (except wind speed which is represented by the second and third eigenmodes) accounts for between 27.41% (wind speed) to 52.32% (precipitation) of the total joint spatiotemporal variability of FUI and the driving variables. The convergent cross-mapping (CCM) analysis shows that cross-map skill (ρ2) is increased with increasing library length (L) and time delay (τ), which suggests significant causal effects of hydro-climatic and LCC variables on FUI and the lagged causation is consistent with maximum values of ρ2. The significant feedback of FUI to changes in hydro-climatic and LCC variables shows the possibility of hindcast/forecast of the historical/future status of water quality from hydro-climatic and LCC variables. As a result, a multivariate nonlinear regression model (MNWQFM) is developed to forecast the lake water quality index from the hydro-climatic and LCC variables. The model has high performance with R2 of 83.6% and root means square error (RMSE) of 0.15 in FUI.

Improving our understanding of future tropical cyclone intensities in the Caribbean using a high-resolution regional climate model

The Caribbean region is prone to the strong winds and low air pressures of tropical cyclones and their corresponding storm surge that driving coastal flooding. To protect coastal communities from the impacts of tropical cyclones, it is important to understand how this impact of tropical cyclones might change towards the future. This study applies the storyline approach to show what tropical cyclones Maria (2017) and Dorian (2019) could look like in a 2 °C and 3.4 °C warmer future climate. These two possible future climates are simulated with a high-resolution regional climate model using the pseudo global warming approach. Using the climate response from these simulations we apply a Delta-quantile mapping technique to derive future changes in wind speed and mean sea level pressure. We apply this Delta technique to tropical cyclones Maria and Dorian’s observed wind and pressure fields to force a hydrodynamic model for simulating storm surge levels under historical and future climate conditions. Results show that the maximum storm surge heights of Maria and Dorian could increase by up to 0.31 m and 0.56 m, respectively. These results clearly show that future changes in storm surge heights are not negligible compared to end-of-the-century sea level rise projections, something that is sometimes overlooked in large-scale assessments of future coastal flood risk.

Simultaneous Damping and Frequency Control in AC Microgrid Using Coordinated Control Considering Time Delay and Noise

The incorporation of converter-based generating sources in utility-scale microgrids causes frequency instability and low-frequency oscillations (LFOs), which is also a reason for degeneration in system stability. Damping frequency control is an essential part of alternating current (AC) microgrid system operation and control. Sudden changes in load, variations in renewable power outputs due to changes in solar insolation or wind speed, and so on factors cause the system frequency to deviate from the nominal value. Therefore, the role of a frequency controller is to maintain the dynamic stability in an AC microgrid by retaining the system frequency at the nominal value. Again, AC microgrids with high renewable power penetration face even more difficulty in maintaining frequency stability because of their poor inertial response. The research presented here proposes a novel approach for grid-connected AC microgrid oscillation damping and frequency control that simultaneously takes into consideration time delay and noise. To improve the frequency response and dampen LFOs by providing the voltage and frequency within the specified range, a coordinated technique-based control approach is adopted. In the developed hybrid control, the frequency controller relies on active power modulation, while the power oscillation damping controller is dependent on reactive power modulation. To improve stability and reduce communication consequences such as noise and signal latency (time delay), the developed power oscillation damping controller and frequency controller are coordinated along with the robust linear quadratic Gaussian controller. The comparative investigation of the effectiveness of the coordinated control technique is employed in the software of MATLAB/Simulink for grid-connected AC microgrid. The outcome of the simulation illustrates the superior effectiveness of the suggested controller over the traditional droop controller for huge power flows under disturbance with various operating conditions, under/overfrequency events, time delay, and noise. This grid encouragement capability for AC microgrids is anticipated to lead to novel possibilities for generating revenue.

Multiple Evolution Modes of Megaripples in the Qaidam Basin and Implications for Ripple‐Like Aeolian Landforms on Mars

AbstractAeolian landforms provide valuable insights into the planetary surface environment and its evolutionary history. In this study, the formation and evolution of megaripples in the Qaidam Basin and their relationship with the development environment are analyzed. By quantifying the wind environment, morphology, grain‐size distribution, sedimentary structure, and luminescence age of megaripples, we propose for the first time that there are multiple megaripple evolution modes. Investigation revealed that three evolution modes were responsible for forming megaripples in different equilibrium states: transient, stable, and metastable. Well‐sorted coarse sand grains accumulate on ridges and overlay poorly sorted fine sand grains to form transient megaripples. Stable megaripples have alternating sedimentary bedding of coarse and fine sand grains. Metastable megaripples have a secondary ripple formation on the surface. Throughout their formation, coarse and fine sand grains undergo regrouping. The response of coarse grains to the change in wind speed lags behind that of fine grains. This process controls the erosion and accumulation of megaripples and affects their size and sedimentary structures. The evolution mode, scale, and sedimentary structure of megaripples are influenced by the grain‐size range under the same wind conditions. The luminescence ages of the coarse‐grained megaripple sediments are less than 700 years. This study provides a fresh perspective on the coexistence of various sand ripples and transverse aeolian ridges found on Mars.

Informer Model based Wind Power Forecast with Tropical Storms Present

When severe tropical storms pass through, regional wind speeds fluctuate greatly, and the volatility of wind farm output also increases significantly. At the same time, the duration of tropical storms is long, and it is difficult for short-term time series data prediction models to be effective, in which case the unstable output of wind turbines will have a greater impact on power system dispatching. This paper first examines the characteristics of tropical storm movement, namely the change in wind speed, and then uses the Informer long time series data prediction model to predict the total change in wind turbine output in the next 10 days after the storm has passed. The actual case proves that the Informer model is ideal in predicting the long time series of wind power output during a tropical storm.

An efficient MPPT techniques for inter-harmonic reduction in grid connected hybrid wind and solar energy systems

In this work, the operation of photovoltaic system, wind turbine driven doubly fed induction generator along with battery has been observed. Also, a searching space minimization-based artificial bee colony scheme is developed for tracking the maximum power in a doubly fed induction generator-based system. To track maximum power in solar systems, an improved adaptive reference voltage approach has been presented. Several conventional and optimization-based techniques are used by DFIG and photovoltaic systems to get around the non-linearity features in the output parameters. Regarding DFIG, the artificial bee colony method based on searching space minimization can be used to solve the shortcomings of the perturb and observe algorithm. Because of its weather-sensitive nature, it can withstand sudden changes in wind speed. The suggested searching space minimization based artificial bee colony strategy uses a mechanism for determining the range of optimal rotor speed in order to track the maximum power point more quickly. The maximum power point tracking performance of the adaptive reference voltage technique is superior to that of current perturb and observed-based systems. However, a huge processing memory is required in order to track the maximum possible power point. This paper proposes an enhanced maximum power point tracking technique based on adaptive reference voltage that does not require a memory unit. Additionally, despite sudden changes in irradiation conditions, improved adaptive reference voltage can drift-free and reliably monitor the maximum power point. The new adaptive reference voltage technique uses temperature and radiation sensors to identify the region nearest to the maximum power point. This helps the system respond more quickly. The proposed system with searching space minimization based artificial bee colony and improved adaptive reference voltage schemes displays lower inter-harmonic content in grid current compared to perturb and observe scheme. The proposed scheme has been implemented in MATLAB & simulink atmosphere and OPAL-RT displayed satisfactory results.

Understanding the Spatiotemporal Variability of Tropical Orographic Rainfall Using Convective Plume Buoyancy

Abstract Mechanical forcing by orography affects precipitating convection across many tropical regions, but controls on the intensity and horizontal extent of the orographic precipitation peak and rain shadow remain poorly understood. A recent theory explains this control of precipitation as arising from modulation of lower-tropospheric temperature and moisture by orographic mechanical forcing, setting the distribution of convective rainfall by controlling parcel buoyancy. Using satellite and reanalysis data, we evaluate this theory by investigating spatiotemporal precipitation variations in six mountainous tropical regions spanning South and Southeast Asia, and the Maritime Continent. We show that a strong relationship holds in these regions between daily precipitation and a measure of convective plume buoyancy. This measure depends on boundary layer thermodynamic properties and lower-free-tropospheric moisture and temperature. Consistent with the theory, temporal variations in lower-free-tropospheric temperature are primarily modulated by orographic mechanical lifting through changes in cross-slope wind speed. However, winds directed along background horizontal moisture gradients also influence lower-tropospheric moisture variations in some regions. The buoyancy measure is also shown to explain many aspects of the spatial patterns of precipitation. Finally, we present a linear model with two horizontal dimensions that combines mountain wave dynamics with a linearized closure exploiting the relationship between precipitation and plume buoyancy. In some regions, this model skillfully captures the spatial structure and intensity of rainfall; it underestimates rainfall in regions where time-mean ascent in large-scale convergence zones shapes lower-tropospheric humidity. Overall, these results provide new understanding of fundamental processes controlling subseasonal and spatial variations in tropical orographic precipitation.

Climate Risk Management in Cultural Heritage for Inclusive Adaptation Actions in Nigeria

Different regions around the world are experiencing climate risks, including increasing temperatures, rapid changes in rainfall patterns, loss of biodiversity and extreme weather events. Within the last decade, Nigeria has experienced a series of localised and regional drought and flooding events affecting not only arable farmlands but also cultural heritage, including heritage buildings and cultural landscapes. This study assesses climate-related risks affecting cultural heritage using the ABC risk assessment method to understand the impacts of key climate drivers. The assessment method was applied to five cultural heritage sites with different values and functions. The findings revealed that changes in precipitation and wind speed and direction induce most of the sudden-onset impacts, such as bushfires, flooding and physical collapse. A sense of community connection and attachment to the built heritage remain strong but there have been limited efforts to implement actions that address climate risks to the built heritage and its surrounding spaces. The output of the assessment contributes to risk prioritisation and informs decision making for developing the needed adaptive actions. The study demonstrates the need to leverage climate information collected by different national and international organisations not to only assess climate risks to heritage but also to improve the involvement of local communities and non-heritage professionals in developing adaptation actions for built heritage.