Wind Sources Research Articles

Monthly variation and correlation analysis of global temperature and wind resources under climate change

Renewable energy is widely used as an alternative source of energy, and climate change has a significant impact on its variation and harnessing. This study conducted a monthly scale analysis of global temperature and wind-speed variations and their correlations using Theil–Sen’s median linear regression and Mann-Kendall test from 1989 to 2021. The results revealed that the global temperature averagely increased by 0.34 °C/10 a from 1989 to 2021, showing clearly increasing trends in most months but with significant differentiation in each month. The regions of East Europe Plain, Central Siberia, Central Asia, and Greenland showed the most significant increasing temperature trends ranging from 0.17 to 0.49 °C/10 a. Additionally, the regions in the East Europe Plain, Siberia, and North America showed distinctly decreasing temperature trends ranging from 0.27 to 0.51 °C/10 a. The global average wind speed changed slightly, with slopes of −0.026, −0.014, and 0.019 m/(s⋅10 a) for eastward, northward, and synthesis wind, respectively. However, the decreasing trends were relatively evident in regions across central Europe via the south of the Eastern European Plain to the north of Central Asia with slopes ranging from −0.13 to −0.3 m/(s⋅10 a). These monthly variations in eastward, northward, and synthesis wind speeds showed significant correlations with temperature, and the correlation coefficients (CCs) differed significantly for each month. For positive CCs higher than 0.34 and negative CCs lower than −0.35 (p < 0.05), the land coverage areas reached 72.3 million km2, accounting for 48% of the global land area. In addition, the synthesis wind speed showed significant positive and negative CCs with temperature, especially from November to March of the following year. The highly positive CCs of global temperature and synthesis wind speed are primarily distributed across land areas from Europe to Siberia, North America, and North Africa in the Northern Hemisphere. The areas with high negative CCs are distributed across South America, South Africa, and Australia in the Southern Hemisphere. Climate change has a substantial impact on wind-speed variation, which should be considered during wind source harnessing. Monthly variation analysis of global temperature and wind speed and their correlation could provide key scientific support for climate change adaptation and wind resource harnessing.

Prediction and Verification of Parker Solar Probe Solar Wind Sources at 13.3 R⊙

AbstractDrawing connections between heliospheric spacecraft and solar wind sources is a vital step in understanding the evolution of the solar corona into the solar wind and contextualizing in situ timeseries. Furthermore, making advanced predictions of this linkage for ongoing heliospheric missions, such as Parker Solar Probe (Parker), is necessary for achieving useful coordinated remote observations and maximizing scientific return. The general procedure for estimating such connectivity is straightforward (i.e., magnetic field line tracing in a coronal model) but validating the resulting estimates is difficult due to the lack of an independent ground truth and limited model constraints. In its most recent orbits, Parker has reached perihelia of 13.3R⊙ and moreover travels extremely fast prograde relative to the solar surface, covering over 120° longitude in 3 days. Here we present footpoint predictions and subsequent validation efforts for Parker Encounter 10, the first of the 13.3R⊙ orbits, which occurred in November 2021. We show that the longitudinal dependence of in situ plasma data from these novel orbits provides a powerful method of footpoint validation. With reference to other encounters, we also illustrate that the conditions under which source mapping is most accurate for near‐ecliptic spacecraft (such as Parker) occur when solar activity is low, but also require that the heliospheric current sheet is strongly warped by mid‐latitude or equatorial coronal holes. Lastly, we comment on the large‐scale coronal structure implied by the Encounter 10 mapping, highlighting an empirical equatorial cut of the Alfvèn surface consisting of localized protrusions above unipolar magnetic separatrices.

Techno-economic analysis of green energy resources for power generation & direct use by preserving near-wellbore geothermal gradient

Closed-loop fluid circulation in wellbores has gained considerable attention for harnessing the earth's thermal energy. Recent studies with analytical and numerical models show that geothermal gradient and well depth constitute the two most consequential variables in fluid output temperature at the surface. This study presents a new strategy for managing geothermal-gradient cooling to ensure more prolonged operation by adopting another energy source, such as solar or wind, with a day/night cycle over the years. In other words, the fluid circulation will occur at night, while the solar or wind source will operate in the daytime. Well-depth and geothermal gradients dictate which geographic area provides the best opportunity for power generation or hot water production to meet various industrial needs. Economic tools, such as Net Present Value and Levelized Cost of Electricity, helped gauge their strengths and limitations, thereby offering business decisions objectively.Considering a 20-year power generation period, this study provides some pragmatic lessons. For example, retaining the near-wellbore geothermal gradient is essential for assuring about 130 °C for the binary cycle. We can attain this objective with a 12-h fluid-circulation cycle by juxtaposing a second well or a solar/wind source for a day/night cycle. Also, besides being a safety net, a power grid can aid the economic value proposition in this energy-transition phase. The generation of hot water for direct industrial usage for low-geothermal prospects also becomes economically viable, particularly in repurposing abandoned wells. These industries include food and agriculture, requiring 60 to 85 °C.

Hybrid Energy Generation System with Brushless Generators

Technical and economic problems are connected with the capacity extension of the grid to remote areas. The discovery and usage of interconnected power production using alternative power supply sources has been promoted. This article proposes a fulfillment with the use of Voltage Source Converter (VSC) and brushless generators with a standalone micro grid topology. With numerous Renewable Energy Sources (RES), including solar PV and wind the micro grid device is energized. However, to ensure the system's stability, a Diesel Generator (DG) collection and a Battery Energy Storage System (BESS) are also used. The topology suggested has the benefit of less number of switches and easy power. The structure applied has been fixed as an AC supply by DG. The wind and PV sources are DC sources related to the VSC DC connection. At the DC connection, the BESS is often used to promote the instantaneous equilibrium of power under complex conditions. The VSC further has the potential to alleviate power quality challenges such as harmonics, voltage control and load balancing, in addition to system integration. To illustrate all the capabilities of the proposed method, a good range of Matlab/Simulink yield outcomes are conferred.

Anion Exchange Membrane Water Electrolysis: The Future of Green Hydrogen

Hydrogen-derived power is one of the most promising components of a fossil fuel-independent future when deployed with green and renewable primary energy sources. Energy from the sun, wind, waves/tidal, and other emissions-free sources can power water electrolyzers (WEs), devices that can produce green hydrogen without carbon emissions. According to recent International Renewable Energy Agency reports, most WEs employed in the industry are currently alkaline water electrolyzers and proton-exchange membrane water electrolyzers (PEMWEs), with ∼200 and ∼70 years of commercialization history, respectively. The former suffers from inherently limited current densities due to inevitable gas crossover, operates using corrosive (7 M) alkaline solutions, and requires large installation footprints, while the latter requires expensive and scarce precious metal-based electrocatalysts. An emerging technology, the anion-exchange membrane water electrolyzer (AEMWE), seeks to combine the benefits of both into one device while overcoming the limitations of each. AEMWEs afford higher operating current densities and pressures, similar Faradaic efficiencies when compared to PEMWEs (>90%), rapid ramping/load-following responsiveness, and the use of non-noble metal catalysts and pure water feed. While recent reports show promising device performance, close to 3 A/cm2 for AEMWEs with 1 M KOH or pure water feed, a deeper understanding of the mechanisms that govern device performance and stability is required for the technology to compete and flourish. Herein, we briefly discuss the fundamentals of AEMWEs in terms of device components, catalysts, membranes, and long-term stability/durability. We provide our perspective on where the field is going and offer our opinion on how specific performance and stability tests should be performed to facilitate the development of the field.

Off-Grid Hybrid Renewable Energy System Operation in Different Scenarios for Household Consumers

Off-grid hybrid renewable energy systems represent the most modern and flexible solutions that can cover a wide range of energy efficiency needs for household consumers. In the current context, these systems must be taken into account by most household consumers, given the fact that the price of energy has increased. This paper proposes an experimental analysis of the behavior of such a system, in real operating conditions, considering two renewable energy sources, wind and photovoltaic sources, using an experimental stand. It can be considered a testing platform for hybrid energy production systems, in that the power installed in the two sources can be scaled up. The platform has the advantage of allowing the implementation of different load and wind curves through a programmable logic controller; in this way, it is possible to evaluate the degree of coverage of the energy consumption produced from renewable sources, in the north-east of Romania, in the Suceava County region. The experimental study also involves an analysis of the storage capacity in relation to the consumption and the electricity produced by the two renewable sources. In this regard, three scenarios differentiated by the state of charge (30%, 50% and 70%) have been established. The results indicate that, for each of the imposed scenarios, the energy required to cover consumption is produced by renewable energy sources (42%, 47% and 53%), to which the energy stored in batteries (39%, 28% and 18%) is added.

Harvesting heat energy using geothermal and hydronic pavements for sustainable cities: A comprehensive review of an emerging idea

To minimize the environmental and ecological impacts of non-renewable energy sources, a massive switch to solar, geothermal, wind, and other renewable energy sources are necessary. Energy harvesting pavements are being widely explored as solar energy is the most abundant source of energy on Earth and 20 to 30% of the urban area is covered by road pavements which are continuously exposed to solar radiation. One of the feasible methods to harvest heat energy from pavements is to collect and transfer heat using a network of fluid pipes embedded in the pavement. It will reduce the pavement temperature during summer and the stored heat energy can be used to melt snow/ice from the pavements during winter. Apart from the conservation of non-renewable energy, these pavements also contribute to urban heat island (UHI) mitigation, extension in pavement life, and provide a smooth riding surface in winter. This paper provides an extensive review of these pipe-pavement energy harvesting systems in terms of the factors affecting their design, impact on thermal performance, construction and economic feasibility of the system. The paper also highlights the scope for further research in this area that will help in improving the efficiency of this system.

Wind Speed Prediction Based on Statistical and Deep Learning Models

Wind is a dominant source of renewable energy with a high sustainability potential. However, the intermittence and unstable nature of wind source affect the efficiency and reliability of wind energy conversion systems. The prediction of the available wind potential is also heavily flawed by its unstable nature. Thus, evaluating the wind energy trough wind speed prevision, is crucial for adapting energy production to load shifting and user demand rates. This work aims to forecast the wind speed using the statistical Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model and the Deep Neural Network model of Long Short-Term Memory (LSTM). In order to shed light on these methods, a comparative analysis is conducted to select the most appropriate model for wind speed prediction. The errors metrics, mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are used to evaluate the effectiveness of each model and are used to select the best prediction model. Overall, the obtained results showed that LSTM model, compared to SARIMA, has shown leading performance with an average of absolute percentage error (MAPE) of 14.05%.

Stochastic Security-Constrained Economic Dispatch of Load-Following and Contingency Reserves Ancillary Service Using a Grid-Connected Microgrid during Uncertainty

In the context of the growing penetration of renewable power sources in power systems causing probabilistic contingency conditions, a suitable economic dispatch model is decisively needed. There is a lack of research in the field of probabilistic mathematical formulation considering the uncertainties due to the stochastic nature of renewables and contingency occurrence, as it is a very complex problem to be solved. The most appropriate model is the stochastic security-constrained economic dispatch (SSCED) model for optimized economic dispatch decisions during uncertainty. However, because of its complexity, it is rarely employed. This paper attempts to solve the complex SSCED problem in the presence of the uncertainty of resources and probabilistic contingency conditions, which is a novel effort in this regard. The SSCED is carried out over multiple periods to provide the load-following or contingency reserves. In the proposed SSCED, the uncertainty problem is addressed by modeling the stochastic wind energy power source by using “probability transition scenarios”. The uncertainty caused by probabilistic contingency conditions in the dispatch schedule is approximated using a “state-specific transition matrix”. The frequency control reserves in contingency conditions are co-optimized with energy, and stochastic security-constrained economic dispatch is achieved. The efforts are put forward to suggest a new market model in the presence of the uncertainty of renewable energy availability. Case studies are examined to show the potential technical and financial advantages of the proposed SSCED through co-optimization. Grid-connected microgrid owners offer frequency control ancillary services by providing load-following ramping reserves in the normal state and contingency reserves in the state of contingency. The probabilistic contingencies considered are generator failure and an underloading condition. A modified “IEEE 30 bus system” is considered a grid-connected microgrid for testing the proposed SSCED. The results show that the greater the flexibility of the resources, the greater the technical and economic benefits. The increase in ramping flexibility of a wind source results in almost an 8.1% reduction in operational costs compared to the base case. The contingency condition analysis shows that the presence of ramping reserves in the system enhances the power system performance, avoiding the cascading effects that ultimately cause a power system failure.

Experimental and CFD analyses of pollutant dispersion around an isolated cylindrical building

An investigation of the dispersion of pollutants ejected from a chimney around a three-dimensional cylindrical obstacle within a crossflow air stream was conducted in this paper. The dynamic evolution of air seeded with glycerin particles ejected from an elevated jet around the isolated obstacle in a wind tunnel was experimentally studied using the particle image velocimetry technique and under different velocity ratios between the chimney ejection and the wind source. The dispersion of CO2 pollutant around the cylindrical building was numerically predicted based on measured experimental data using the finite volume method and the Reynolds stress model. A good agreement between experimental and computational results was found. Velocity, temperature, and concentration results revealed that the velocity of the wind together with the presence of the isolated building obstacle influenced the flow structure.

Fuzzy logic for renewable energy recommendation and regional consumption forecast using SARIMA and LSTM

The use of renewable energy, notably solar and wind energy, has grown exponentially in Brazil. Consumers can generate their energy using renewable sources, whether interconnected to the distribution system (on-grid) or not (off-grid). In this paper, a fuzzy method is developed for the recommendation of solar and wind sources, for any location in the Brazilian territory. In many aspects, it can be viewed as a representation of human decision-making using sets and inference rules and also can be with vagueness and uncertainty, being very useful to idealize recommendation systems. Georeferenced and historical data were obtained from 2003 to 2019 on solar irradiation and wind speed, and electricity consumption until 2021. With the energy generation data from photovoltaic panels and wind turbines, this method allows us to propose installed areas by each technology and obtain the membership of fuzzy recommendation between solar, wind, both solar and wind, unfeasible or hybrid. In addition, a long short-term memory neural network and the seasonal autoregressive integrated moving average model were used to predict consumption for more than 30 months ahead, allowing the recalculation of fuzzy memberships and updating the installation area by respective technologies. As a result, the recommendation is given as the installed area (m2) of each technology per km2 of consumer units, as a function of the regional consumption density (MWh/km2). It can be concluded that it is possible to plan the viability of the type of renewable energy used, according to regional characteristics for smaller consumer units (farms, cooperatives, industries, consortiums), given the diversity of these factors in the huge Brazilian territory. This methodology is in line with the Brazilian Normative Resolution that authorizes the generation of energy by landowners.

Impacts of Uncertain Geomagnetic Disturbances on Transient Power Angle Stability of DFIG Integrated Power System

When geomagnetic disturbances (GMDs) occur, the reactive power loss (GIC-Q) caused by geomagnetically induced currents (GICs) flowing through transformers can lead to system instability. Previous studies have been focused on the impacts of GMD on the static stability of conventional systems, while transient stability of hybrid systems left unexplored. In this article a hybrid system based on wind and conventional energy sources are proposed as a research object. The wind farm output power and GIC-Q are equivalent to the grounding impedance. Considering the uncertainty of GMD, based on establishing the random fuzzy model of induced geomagnetic fields, the expected value of critical clearing angle and acceleration/deceleration area is calculated by using credibility theory. Then the influence of GMD on the transient stability under the different proportions of wind farm output power is analyzed quantitatively by using transient stability margin. Taking the Mengdong power grid under four operation modes as an example, the results show that no matter which operation mode, the transient stability of the system is reduced when GMDs occur. Under heavy loading conditions in summer and when the proportion of wind farm output power reaches 50%, the transient stability of the system is the lowest. The research results provide a basis for disaster prevention and control of GMDs.

Lagrangian Stochastic Model for the Motions of Magnetic Footpoints on the Solar Wind Source Surface and the Path Lengths of Boundary-driven Interplanetary Magnetic Field Lines

In this work, we extend Leighton’s diffusion model describing the turbulent mixing of magnetic footpoints on the solar wind source surface. The present Lagrangian stochastic model is based on the spherical Ornstein–Uhlenbeck process with drift that is controlled by the rotation frequency Ω of the Sun, the Lagrangian integral timescale τ L, and the root-mean-square footpoint velocity V rms. The Lagrangian velocity and the positions of magnetic footpoints on the solar wind source surface are obtained from the solutions of a set of stochastic differential equations, which are solved numerically. The spherical diffusion model of Leighton is recovered in the singular Markov limit when the Lagrangian integral timescale tends to zero while keeping the footpoint diffusivity finite. In contrast to the magnetic field lines driven by standard Brownian processes on the solar wind source surface, the interplanetary magnetic field lines are smooth differentiable functions with finite path lengths in our model. The path lengths of the boundary-driven interplanetary magnetic field lines and their probability distributions at 1 au are computed numerically, and their dependency with respect to the controlling parameters is investigated. The path-length distributions are shown to develop a significant skewness as the width of the distributions increases.

Sustainable energy solutions and climate change: A policy review of emerging trends and global responses

This policy review delves into the intricate nexus between sustainable energy solutions and the imperative to address climate change. As the global community grapples with the escalating challenges posed by environmental degradation, this study critically examines emerging trends and assesses the effectiveness of policy responses at the international level. The analysis spans a comprehensive spectrum, encompassing renewable energy sources, technological innovations, regulatory frameworks, and collaborative initiatives aimed at mitigating climate change impacts. The review first explores the current state of sustainable energy technologies, shedding light on advancements in solar, wind, hydropower, and other renewable sources. It evaluates the feasibility, scalability, and economic viability of these technologies, considering their potential to revolutionize energy production while minimizing ecological footprints. Additionally, the study investigates the role of emerging technologies, such as energy storage systems and smart grids, in optimizing the integration of renewable energy into existing infrastructures. The second dimension of the review focuses on the global policy landscape, scrutinizing international agreements, accords, and collaborative efforts designed to combat climate change. The analysis assesses the effectiveness of existing policies in fostering sustainable energy transitions and reducing greenhouse gas emissions. Special attention is given to cross-border collaborations, funding mechanisms, and policy coherence among nations, highlighting success stories and identifying areas for improvement. Furthermore, the review examines the socio-economic implications of sustainable energy policies, considering their impact on job creation, economic growth, and social equity. By exploring case studies from diverse regions, the study aims to provide insights into the nuanced challenges and opportunities associated with the transition to sustainable energy systems. This policy review synthesizes key findings to offer a holistic understanding of the current landscape of sustainable energy solutions and climate change policies. By critically evaluating emerging trends and global responses, the study aims to inform policymakers, researchers, and stakeholders about effective strategies for navigating the complex terrain of sustainable energy transitions in the face of climate change.

Modeling of an Energy-Diverse Embedded Grid for Microreactor Integration

Microreactors present an opportunity to revolutionize the role of nuclear energy via the development of these technologies in a diverse and distributed energy network for a clean energy future. Because of the limited output of these novel systems, the deployment of microreactors should be focused on high-value applications in order to realize their full potential. This involves understanding the microreactor performance and how it interacts with the preexisting infrastructure. In this work, an energy-diverse embedded grid is modeled using OpenModelica in order to study the impact of microreactor integration under several distinct deployment approaches. The University of Illinois at Urbana-Champaign (UIUC) is used as a prototypic market due to its well-characterized energy ecosystem with available extensive real-time and historical data. The UIUC model recreates the existing chilled-water, steam, and electricity infrastructure, including wind, solar, and cogeneration sources. The infrastructure model simulates the interplay between the three utilities and how different microreactor integration approaches would impact UIUC’s embedded grid. From this study, the deployment of a single microreactor under electric load-conditioning, steam production retrofit, or a hybrid of both is found to be the most appropriate in consideration of their unique advantages toward cost savings and grid resilience. Meanwhile, if grid resiliency is not a main objective, the greatest emissions reduction and cost-savings benefits can be obtained by operating the reactor in a base-loading configuration. This study employed historically low coal and gas prices and provided a conservatively low estimate for the benefits from a microreactor. Given the price volatility of fossil fuels, the benefits of the microreactor are expected to be greater than this estimate. Finally, the modular nature of the modeling framework allows for an extension of the analysis to other similar embedded grids.

Factors controlling the Early-Mid Holocene aeolian sediment accumulation in the Pum Qu catchment and environmental implications for the southern Tibetan Plateau

Aeolian sediments, a sensitive paleoenvironmental archive, are widely distributed in the river valleys of the southern Tibetan Plateau (TP), mainly including the Pum Qu River (PQR) valley and Yarlung Tsangpo River (YTR) valley. However, factors controlling the Early-Mid Holocene aeolian sediments in the PQR catchment and its relationship with the aeolian accumulation in the YTR catchment are poorly understood. Here, we combine Optically Stimulated Luminescence (OSL) dating, magnetic parameters, grain size parameters, color variations and microscopic characteristics to investigate the factors controlling aeolian accumulation in the PQR catchment. The findings indicate that there is a spatial difference in aeolian accumulation in the PQR catchment. The strong accumulation of aeolian sand mainly occurred between ∼11 and 9.3 ka BP, and the paleosol developed between 9.3 and 4.5 ka BP in the PQR catchment during the Early-Mid Holocene. The results of the comparison show that the ages of strong aeolian accumulation in the PQR catchment and YTR catchment are desynchronized. These desynchronized ages of the Holocene strong aeolian accumulation between these two catchments are mostly caused by different controlling factors. In the PQR catchment, aeolian accumulation is dominantly controlled by multiple factors, mainly including changes in local wind force, source supply, vegetation cover and topographic factors. The Early-Mid Holocene strong aeolian accumulation in the PQR catchment is dominantly controlled by the strong local wind force and rich source supply. In the YTR catchment, the Early-Mid Holocene strong aeolian accumulation may record the interplay between Asian Summer Monsoon (ASM), insolation and westerlies. The desynchronized aeolian accumulation and its controlling factors suggest that there is no simple correspondence between aeolian accumulation and climatic and environmental changes in the southern TP.

DEVELOPMENT OF INTELLIGENT CONTROL STRATEGY FOR POWER QUALITY IMPROVEMENT OF HYBRID RES

The major problem in renewable energy system is that the variation in power generation from time to time because of the intermittent nature of the renewable sources. In this paper presents the Artificial Neural Network (ANN) based intelligent control strategy for hybrid standalone microgrid system for varying wind, varying solar irradiation, varying load and symmetrical and asymmetrical fault conditions is presented. A dynamic model of hybrid standalone microgrid consisting wind and solar PV renewable sources with maximum power point tracking control algorithm is developed in MATLAB/Simulink software. A solar PV panel, wind energy conversion system and dynamic model of hybrid energy storage consisting Lithium-ion batteries (Li-Ion) and supercapacitor is connected with the DC Bus. The DC link is connected through the power electronic interfacing circuit and converters connected to a source for a diverse electricity generation. The main objective of this thesis is to improve the power quality of the hybrid microgrid system by solving the voltage sag and swell problem and reduce total harmonics distortion occurring due to various symmetrical and asymmetrical condition. The simulation studies have been carried out to determine system performance with different scenarios of the sources such as typical solar radiation, temperature, wind, battery and supercapacitor charge or discharge conditions The proposed strategy gives better performance characteristics and reduces the harmonics of the system compared to the conventional solution.

Analysis of the Ventilation Performance of a Solar Chimney Coupled to an Outdoor Wind and Indoor Heat Source

The effects of different solar radiation intensities, heat flow density of indoor heat sources, outdoor wind speed, and the relative location of indoor heat sources on the natural ventilation performance of solar chimneys are investigated through three-dimensional numerical simulations. The mechanism of the mutual coupling of the solar chimney effect with the outdoor wind and indoor heat source heat plume is explored. The results of the study show that when the structural parameters of the solar chimney are the same, the heat flow density on the surface of the indoor heat source, the outdoor wind speed and the solar radiation intensity all have a gaining effect on the ventilation performance of the solar chimney and the effects of the three on the ventilation of the solar chimney promote each other, when the solar radiation intensity is 200 W/m2, the outdoor wind speed is 1.0 m/s, and the indoor heat source heat flow density increases from 0 to 1 500 W/m2, the solar chimney ventilation volume increases from 0.393 m3/s to 0.519 m3/s, the maximum value of the increase is 32.1%. In the other two cases, the maximum increase in solar chimney ventilation is 176.7% and 33.1%, respectively. Under the same conditions, solar chimney ventilation is optimal when the heat source is in the middle of the room. The presence of outdoor wind, however, affects the optimum design parameters of the solar chimney. Compared to the case where no outdoor wind is taken into account, the optimum inlet width of 0.2–0.3 m for the solar chimney no longer applies with outdoor wind, with the optimum value rising to 0.5 m.

Evaluation of Different Optimization Techniques and Control Strategies of Hybrid Microgrid: A Review

Energy consumption is increasing rapidly; hence, the energy demand cannot be fulfilled using traditional power resources only. Power systems based on renewable energy, including solar and wind, are effective and friendly for the environment. Islanded hybrid microgrid systems (IHMS) are relatively new in this industry and combine two or more sustainable sources, such as wind turbines, solar photovoltaic (PV), and other renewable alternatives, ocean, wave, and geothermal energy, etc. While sustainable, long-lasting power sources are the best choice to satisfy the growing energy demands, they are still not yet ready to be used on a large scale due to their stochastic characteristics. Furthermore, integrating these sources into the existing energy system can cause high technical difficulties, due to the stochastic nature of solar and wind in the conventional grid system and common stand-alone framework. A review of research and applications of the effective hybridization of renewable energy sources is therefore essential to address those technical and economic issues and ensure system stability, reliability, and cost-effectiveness. This article discusses the challenges that might arise when a PV plant and a wind power station are combined to produce power for the conventional main grid or in a stand-alone system. In addition, this analysis provides light on optimization approaches for improving power quality and cost-effectiveness in a solar and wind integrated IHMS. Voltage fluctuation, frequency deviation, and the uncertain nature of solar irradiation and wind sources are significant challenges for both grid-connected and standalone hybrid systems. This study then provides an overview of the control strategies which might help enhance the integration of the IHMS in producing electricity for distribution to the grid-connected load and the islanded load. In this study, the possible issues that can hinder the smooth integration of these renewable sources have been discussed. Finally, this study discusses the recent platforms being used in IHMS as well as the potential of dispatch strategies on solar and wind-integrated IHMS.

An Efficient MPC-based Droop Control Strategy for Power Sharing in a Hybrid AC/DC Microgrid Using Renewable Energy Resources

A hybrid microgrid is an efficient technique to integrate renewable energy resources and allow energy exchange between ac and dc subgrids. Pf and QV droop controls are commonly employed in microgrid to deliver power demands while preserving voltage and frequency restrictions via interlinking converter (IC). When a microgrid is powered by renewable energy sources, due to the prevalence of impedance conflict traditional droop techniques offer an inappropriate response in power sharing. This study employs a predictive-based control scheme to ensure appropriate power sharing between both subgrids in the event of imbalancing on either side. Photovoltaic systems, battery storage, and a synchronous generator powered by wind turbines constitute a microgrid, which is connected via an interlinking converter. The MPC MPPT-based control approach dynamically dispatches power generated by wind and solar energy sources to the loads connected throughout the hybrid microgrid. The proposed control technique maintains power exchange between hybrid microgrids within an acceptable range, according to simulation and experimental results.