Hybrid Generation Research Articles

Hydrogen reduction-based energy management strategy of hybrid fuel cell/PV/battery/supercapacitor renewable energy system

Fuel cells can be used in sustainable cities for a variety of purposes, including emergency backup power systems, electric vehicle recharging, and the production of clean, efficient energy for buildings. Additionally, fuel cells can support distributed energy systems, improving energy management, and lowering dependency on conventional energy sources. However, the slow time response of proton exchange membrane fuel cell (PEMFC) during high-level load variation is an issue that needs addressing. To solve this, battery storage and supercapacitor can be integrated with a hybrid generation system including fuel cell, photovoltaic (PV). It's important to have effective energy management strategies (EMSs) to ensure the photovoltaic (PV) array, PEMFC, batteries, and supercapacitors function optimally. An EMS distributes the load demand among these components while maintaining high efficiency and low hydrogen consumption. This paper proposes an effective EMS for a hybrid generating system DC microgrid (MG) having PV, FC, battery, and SC based on recent Harris hawks optimizer (HHO) to manage the energy between the equipment while minimizing the total hydrogen consumption and enhancing the system efficiency. The research work compared several algorithms, including external energy maximization strategy (EEMS), equivalent consumption minimization strategy (ECMS), frequency decoupling and state machine control (FDSMC), proportional integral (PI), Cuckoo search (CS), and grey wolf optimizer (GWO), with the proposed HHO. The EEMS-based HHO algorithm outperformed the others resulting in 18.95 %, 38.77 %, 47.34 %, 34.43 %, 33.9 %, and 20.38 % hydrogen consumption reduction compared to PI, FDSMC, ECMS, EEMS, CS, and GWO, respectively. Moreover, efficiency improved by 7.62 %, 7.77 %, 17.15 %, 11.21 %, 2.17 %, and 5.12 % compared to PI, FDSMC, ECMS, EEMS, CS, and GWO, respectively. The obtained findings demonstrated the robustness and efficacy of the suggested HHO-EMS in obtaining the lowest hydrogen consumption of the DC microgrid that was provided.

Self-driven sensing of acetylene powered by a triboelectric-electromagnetic hybrid generator

A hybrid generator consisting of the direct-current triboelectric nanogenerator (DC-TENG) based on the ternary dielectric triboelectrification effect and the electromagnetic generator (EMG) was designed to provide large output power even at low rotational speeds. At 120 rpm/min, the DC output of the hybrid generator realizes an open-circuit voltage of 3940 V and a short-circuit current of 8 mA, which is capable of powering 1288 light-emitting diodes (LEDs) and a temperature and humidity meter. A ZnO/MXene nanocomposite acetylene sensor has been developed, which can detect trace amounts of acetylene at room temperature. It has a response/recovery speed of 14 s/6 s, a high response of 178%, and long-term stability of more than 30 days for 5 ppm C2H2. In addition, the sensor is highly selective for acetylene, outperforming other gases by more than 100% for the seven characteristic gases in transformer oil. The hybrid generator powered acetylene sensing system was realized to detect the acetylene concentration at room temperature with an excellent response capability, short response recovery time (14 s/9 s), and good linearity and sensitivity.

Roly-poly inspired tribo-electromagnetic energy harvester toward sustainable ocean energy harvesting

With the increasing global population, the demand for energy has also risen significantly. However, the utilization of fossil fuels for the purpose of energy production has resulted in the release of carbon emissions, accelerating the global warming. Therefore, the demand for carbon-free and renewable energy sources, which can replace the fossil fuels, is growing. In this study, a roly-poly-structure-inspired hybridized energy generator (RPHG) is demonstrated by combining a roly-poly triboelectric nanogenerator with an electromagnetic generator. By utilizing the RPHG, multiple vibrations can be induced from an external force due to the recovering force originated by the roly-poly structure of the RPHG. Consequently, the RPHG is capable of harvesting multiple vibrations from a single input vibration. To optimize the electrical performance of the RPHG, the effects of the substrate shape and the number of polytetrafluoroethylene balls into the electrical output is investigated. Also, the effect of the center of gravity on the electrical output generated from the RPHG is theoretically and experimentally confirmed. As a result, the average vibration number is increased from 2.6 to 25.1 with the 20 polytetrafluoroethylene balls when the tilted substrate with a tilted angle of 170° is applied to the RPHG, compared to the electrical output is generated from the RPHG with a flat substrate. The synergistic effect of the hybridization is demonstrated by comparing the charging speeds of a capacitor and the RPHG shows the fastest speed for charging the capacitor. Furthermore, our RPHG generates 2.45 and 19.29 times higher electrical output than the roly-poly triboelectric nanogenerator (RP-TENG) and electromagnetic generator, respectively. The proposed RPHG demonstrates the 195% higher conversion efficiency in terms of energy compared to the power owing to its unique structure. Also, although the RP-TENG and TENG without roly-poly structure (NRP-TENG) generate similar electrical power, the RP-TENG generates 242% higher electrical energy than NRP-TENG, showing the great potential to harvest the mechanical energy due to the roly-poly structure. As an application, a self-powered ocean wave monitoring system is implemented using the RPHG and it successfully detects strong, calm, and gentle waves. These results show the great potential of the RPHG to harvest vibration and ocean wave energy. Hence, we expect our RPHG to be a promising energy-harvesting solution for generating carbon-free energy.

Five-Port Isolated Bidirectional DC-DC Converter for Interfacing a Hybrid Photovoltaic–Fuel Cell–Battery System with Bipolar DC Microgrids

This paper introduces a novel five-port, three-input, dual-output isolated bidirectional dc-dc converter (FPIBC) topology with an effective controller for power-sharing and voltage-balancing in bipolar dc microgrids (BPDCMGs). The proposed converter acts as the interface for the integration of a hybrid generation system comprising a solid oxide fuel cell (SOFC), a photovoltaic (PV) system, and a battery into BPDCMGs. It employs a reduced number of circuit elements compared with similar multiport converter topologies suggested for BPDCMG applications. Symmetrical bipolar output voltages are ensured by a voltage-balancing circuit composed of a fully controlled switch and four diodes. The FPIBC is equipped with different controllers for output voltage regulation and balancing, power sharing, maximum power point tracking of the PV, the optimum operating region of the SOFC, and constant-current, constant-voltage charging of the battery. To verify the viability and effectiveness of the proposed system, a simulation model was developed with a 4.2 kW SOFC, a 3.7 kW PV, and a 140 V 10.8 Ah battery in MATLAB/Simulink. The performance of the FPIBC was evaluated through extensive case studies with different operational modes, including battery charge/discharge states and SOFC and PV parameter changes under varying load conditions. In addition, the proposed system was examined using a daily dynamic load profile. According to the simulation results, a peak efficiency of 97.28% is achieved and the voltage imbalance between the output ports is maintained below 0.5%. It is shown that the FPIBC has advantages over previous converters in terms of the number of ports, number of circuit elements, bipolar output voltage, bidirectional power flow, and efficiency.

Magnetic Field Analysis and Development of Disk Axial–Radial Hybrid Excitation Generator for Range Extenders in Extended-Range Electric Vehicles

Magnetic Field Analysis and Development of Disk Axial–Radial Hybrid Excitation Generator for Range Extenders in Extended-Range Electric Vehicles

Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles

Key messageWe validated the efficiency of genomic predictions calibrated on sparse factorial training sets to predict the next generation of hybrids and tested different strategies for updating predictions along generations.Genomic selection offers new prospects for revisiting hybrid breeding schemes by replacing extensive phenotyping of individuals with genomic predictions. Finding the ideal design for training genomic prediction models is still an open question. Previous studies have shown promising predictive abilities using sparse factorial instead of tester-based training sets to predict single-cross hybrids from the same generation. This study aims to further investigate the use of factorials and their optimization to predict line general combining abilities (GCAs) and hybrid values across breeding cycles. It relies on two breeding cycles of a maize reciprocal genomic selection scheme involving multiparental connected reciprocal populations from flint and dent complementary heterotic groups selected for silage performances. Selection based on genomic predictions trained on a factorial design resulted in a significant genetic gain for dry matter yield in the new generation. Results confirmed the efficiency of sparse factorial training sets to predict candidate line GCAs and hybrid values across breeding cycles. Compared to a previous study based on the first generation, the advantage of factorial over tester training sets appeared lower across generations. Updating factorial training sets by adding single-cross hybrids between selected lines from the previous generation or a random subset of hybrids from the new generation both improved predictive abilities. The CDmean criterion helped determine the set of single-crosses to phenotype to update the training set efficiently. Our results validated the efficiency of sparse factorial designs for calibrating hybrid genomic prediction experimentally and showed the benefit of updating it along generations.

Development of a Series Hybrid Multirotor

Hybrid-electric power is an appealing technology for multirotor platforms due to its ability to enhance the range of the vehicle while providing low emissions and the precise thrust control required for vehicle stability. The development of a multirotor utilizing hybrid propulsion is an essential step for CfAR as it will be the basis of research on this technology in flight. The designed multirotor, MIMIQ (Modular Inertia Matching Quadcopter), is a 32kg quadcopter with a motor-to-motor diameter of 2.7m which will require a total of 3,700W of power to hover. This demand is primarily met by the series hybrid generator onboard which requires the battery to only supplement a portion of that power. At peak thrust however, the motors will demand 12,000W from the system. During these rapid bursts of energy the battery plays a critical roll in providing an immediate response to the power demand which the generator would not be able to provide otherwise.This multirotor is designed to accommodate a wide range of propulsion configurations to optimize performance. In addition, the mechanical characteristics are also intended to be easily adjustable. Parameters such as center of mass, inertia, and motor distance can be adjusted to mimic characteristics of future flight vehicles that implement hybrid systems. Before integration, ground tests were performed on various off-the-shelf hybrid generators in order to evaluate their performance and reliability to ensure that they are well suited for the MIMIQ. To characterize the different modes of operation an extensive performance map was pursued. A number of parameters were measured over time with the most important being load, power, and fuel consumption. It has been proven that at low loads the generator can provide power to the propulsion system while charging the onboard batteries. However, at higher loads both the generator and the battery pack are required to provide power. The tests demonstrated that the integration of a hybrid system into MIMIQ is possible. It was also verified that when the engine is integrated into MIMIQ, both the generator and batteries have to provide power simultaneously in all flight phases.

Cable Cross‐Tie Triboelectric‐Electromagnetic Hybrid Generator Triggered by Vibrations in Bridge Cables

AbstractBridge cables exhibit low damping characteristics and are susceptible to external excitations, leading to random vibrations. Therefore, a cable cross‐tie triboelectric‐electromagnetic hybrid generator triggered by vibrations in bridge cables (CCT‐TEHG) is proposed. The CCT‐TEHG enhances the natural frequency of the cables by connecting adjacent cables, thereby preventing low‐frequency resonance. The device connects adjacent bridge cables to increase the natural frequency, preventing low‐frequency resonance. Comprising triboelectric nanogenerators (TENGs) and electromagnetic generators (EMG), the CCT‐TEHG effectively broadens the frequency range for energy harvesting, capturing vibrational energy from bridge cables in cable‐stayed bridges. The TENG module in CCT‐TEHG features a soft‐contact design, incorporating rabbit fur to supplement charges and enhance output density. This design also avoids direct material contact between generator units, improving operational durability. The experimental results show that the maximum output voltage and current of the TENG and EMG modules can respectively reach up to 270 V, 13 V, and 5.2 µA, 18 mA, and peak power to 2.04 mW, 10 mW. The CCT‐TEHG can function as a power source, sufficient to power 303 light‐emitting diodes (LEDs) or a 20 mW temperature and humidity sensor. Therefore, CCT‐TEHG has good application prospects in the field of bridge cable vibration energy harvest.

Diasporic Consciousness: A Study of Identity Crisis in Jhumpa Lahiri’s “Unaccustomed Earth”

This paper explores the creative work of renowned diasporic Indian writer Jhumpa Lahari in her collection of eight short stories entitled "Unaccustomed Earth" where, she has explored the tug of war between the traditional-cultural values sustained by the immigrant parents but were curtailed by their precocious young American teenagers. The oscillation of permanent settlement in the new land and an overwhelming nostalgia for the homeland is a persistent theme of diasporic writers. In the introductory part of the research paper diaspora is defined and elucidated. The dispersion of Indian people across the globe and their vivid experiences and suffrages is discussed in the second part of the paper. The central themes of the diasporic writer and Indian diasporic writers and their closeness and corelation to celebrated diasporic writer Jhumpa Lahiri is discussed in the subsequent paragraphs. Diasporic terms like assimilation, adaptation, hybridity, host culture, ethnic and culture conflicts have been discussed in the light of the ‘Unaccustomed Earth’ by Lahiri. Irresistible past of the immigrants for their land of origin is a perennial source of study among diasporic writers. This paper explores the tug of war between the first-generation migrants who have the sense of rootlessness, alienation, and nostalgic homesickness on one hand and the hybrid and multicultural third generation and its synthesis of the past and the modern leading to socio-cultural, linguistic, and psychological transfusion widening new dimensions for the next generation in Lahiri’s stories.

Cytonuclear interplay in auto- and allopolyploids: amultifaceted perspective from the Festuca-Lolium complex.

Restoring cytonuclear stoichiometry is necessary after whole-genome duplication (WGD) and interspecific/intergeneric hybridization in plants. We investigated this phenomenon in auto- and allopolyploids of the Festuca-Lolium complex providing insights into the mechanisms governing cytonuclear interactions in early polyploid and hybrid generations. Our study examined the main processes potentially involved in restoring the cytonuclear balance after WGD comparing diploids and new and well-established autopolyploids. We uncovered that both the number of chloroplasts and the number of chloroplast genome copies were significantly higher in the newly established autopolyploids and grew further in more established autopolyploids. The increase in the copy number of the chloroplast genome exceeded the rise in the number of chloroplasts and fully compensated for the doubling of the nuclear genome. In addition, changes in nuclear and organelle gene expression were insignificant. Allopolyploid Festuca × Lolium hybrids displayed potential structural conflicts in parental protein variants within the cytonuclear complexes. While biased maternal allele expression has been observed in numerous hybrids, our results suggest that its role in cytonuclear stabilization in the Festuca × Lolium hybrids is limited. This study provides insights into the restoration of the cytonuclear stoichiometry, yet it emphasizes the need for future research to explore post-transcriptional regulation and its impact on cytonuclear gene expression stoichiometry. Our findings may enhance the understanding of polyploid plant evolution, with broader implications for the study of cytonuclear interactions in diverse biological contexts.

Key candidate genes for male sterility in peppers unveiled via transcriptomic and proteomic analyses.

This study aimed to enhance the use of male sterility in pepper to select superior hybrid generations. Transcriptomic and proteomic analyses of fertile line 1933A and nucleic male sterility line 1933B of Capsicum annuum L. were performed to identify male sterility-related proteins and genes. The phylogenetic tree, physical and chemical characteristics, gene structure characteristics, collinearity and expression characteristics of candidate genes were analyzed. The study identified 2,357 differentially expressed genes, of which 1,145 and 229 were enriched in the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, respectively. A total of 7,628 quantifiable proteins were identified and 29 important proteins and genes were identified. It is worth noting that the existence of CaPRX genes has been found in both proteomics and transcriptomics, and 3 CaPRX genes have been identified through association analysis. A total of 66 CaPRX genes have been identified at the genome level, which are divided into 13 subfamilies, all containing typical CaPRX gene conformal domains. It is unevenly distributed across 12 chromosomes (including the virtual chromosome Chr00). Salt stress and co-expression analysis show that male sterility genes are expressed to varying degrees, and multiple transcription factors are co-expressed with CaPRXs, suggesting that they are involved in the induction of pepper salt stress. The study findings provide a theoretical foundation for genetic breeding by identifying genes, metabolic pathways, and molecular mechanisms involved in male sterility in pepper.

Distributed ADMM power optimal control for standalone hybrid generation systems

With the rapid development and increased demand for renewable energy sources, standalone hybrid generation systems have become an essential energy solution. Power optimization control is thus critical to achieving the efficient operation and stability of this system. The distributed ADMM (alternating direction method of multipliers)-based approach has the full potential to deal with the power optimization problem of standalone hybrid generation systems. This study uses an optimization algorithm with a Gaussian penalty function, ADMM-ρ, to alternately optimize the power reference values of wind, light, and battery-containing power generation subsystems. The local controller regulates the output power of the converter according to this reference value. This ensures that the wind and photovoltaic power generation subsystem work in load-tracking or maximum power-tracking modes so that the optimal operation of hybrid power generation meets the balance of supply and demand while prolonging the service life of the batteries. Simulation experiments show that the distributed ADMM algorithm can reliably address the power optimization challenge of hybrid power generation systems.

Optimal scheduling for wind-solar-hydro hybrid generation system with cascade hydropower considering regulation energy storage requirements

Large-scale integration of renewable energy into the grid can lead to significant changes in the net load, peak-to-valley difference, peak and valley occurrence time of the power system. As a result, the power of hydropower plants must take a rapid adjustment response. Aiming at the coordinated operation of multiple energy sources, such as wind power, solar power, cascade hydropower station and energy storage pumping station, a coordinated scheduling model is proposed which can fully improve the consumption capacity of wind and solar power by aiming at the maximum power generation, minimum net load fluctuation and minimum wind and solar abandonment. Through the configuration of three different pumping station capacities, the influence of energy storage pumping station capacity on the complementary power generation system is analyzed. When the pumping station capacity is large enough, the output of the wind and solar can be completely consumed. The studies show that the cascade power station and pump energy storage regulation have a strong net load filling valley effect, which can effectively reduce the impact of wind and solar access on system operation, maintain the efficient and stable operation of the unit, and ensure the absorption rate of renewable energy.

Recruiting for the hybrid generation. Tips for creating a successful business landscape through mentorship programs

PurposeBryan Otte, Chief Human Resources Officer at MGAC, examines the shifting dynamics of remote and hybrid work models. Addressing challenges in workplace connections, mentorship and trust, Otte advocates a human-centric approach for HR leaders. This study aims to deliver insights and practical strategies, guiding HR professionals in adapting strategies to facilitate meaningful connections, robust mentorship programs and sustained professional growth within the evolving work environment.Design/methodology/approachBryan Otte uses a qualitative approach, leveraging his role as Chief Human Resources Officer at MGAC. The methodology involves a thorough examination of the impacts of remote and hybrid work models on workplace dynamics. Otte integrates real-world examples and insights, offering practical strategies for HR leaders with a focus on a human-centric perspective. This approach combines professional expertise with a nuanced understanding of the evolving workforce, providing concise and valuable guidance for adapting HR strategies to the changing landscape of work.FindingsOtte’s findings reveal challenges in remote and hybrid work, including potential disengagement and trust issues. The absence of a central workplace hub may contribute to feelings of isolation, particularly among younger associates who often derive relationship modeling from the workplace. The study advocates for a human-centric approach, emphasizing the enduring value of intentional team building, mentorship programs and fostering relational bonds. The research underscores the need for HR leaders to adapt strategies, ensuring positive workplace engagement, professional growth and overall well-being in the evolving work landscape.Originality/valueBryan Otte’s article brings originality through his role as Chief Human Resources Officer at MGAC, providing unique insights into challenges posed by remote and hybrid work. The practical strategies proposed, emphasizing a human-centric approach, offer innovative solutions to address issues such as disengagement and trust. The article’s value lies in shaping HR strategies for the evolving workforce, stressing the enduring importance of intentional team building and mentorship programs. Otte's blend of professional expertise and nuanced understanding contributes significantly, offering actionable guidance for HR leaders navigating the changing dynamics of work.

Bvp4c approach and duality of hybrid nanofluid over extending and contracting sheet with chemical reaction and cross-diffusion effects

Heat transfer has a major effect on material selection and mechanical efficiency. The importance of peristaltic fluid motion in transmitting heat is obvious in the domains of biomedical research through the processes of metabolic heat generation, blood transportation, capillary dehydration, thermal control, and bio-heat exchange pathways. The present work aims to explore the computational and theoretical evaluation of hybrid nanofluid (HNF)-suspended Cu and Al2O3 nanoparticles in water in the presence of chemical reaction, Lorentz force and ross-diffusion. The fundamental flow system based on Navier-Stokes in terms of partial differential equations is converted to dimensionless nonlinear ordinary differential equations via similarity transformations. The transformed ODEs are computationally solved by bvp4c approach. Dual solutions have been observed for emerging factors, so stability examinations are implemented to find the stable solution. Based on eigenvalues, it is witnessed that smallest positive eigenvalues indicates the stable while negative depicts the unstable solutions. The influences of involved factors on the flow characteristics are depicted through graphs and tables. The confirmation of the present analysis is done with the published study. Decreasing behavior is investigated for both branches of velocity as the M is improved while f′(η) is an increasing function of K. From this analysis it is reported that θ(η) is directly proportional to R, Q and Q1. Increasing phenomena is reported for θη and ϕη profiles as the quantities of Ec are augmented from 0.1 to 1. The conclusions of this theoretical analysis have impending applications in numerous fields such as technological devices, solar cooling and heating systems for cars, surfactants, lubricating qualities, hybrid generators, metallic welding process, and the production of medical equipment.

Self-powered system by a suspension structure-based triboelectric-electromagnetic-piezoelectric hybrid generator for unifying wind energy and vibration harvesting with vibration attenuation function

The large-scale deployment of the floor-mounted wind energy nanogenerator with wind cup structure in the Internet of Things provides a promising solution for the continuous and reliable power supply of distributed sensor systems. However, some wind energy harvesting scenarios have high requirements for placement and fixation of device, thereby the suspension structure-based wind energy harvester is considered to be a potential solution in the suspension scenarios. In this paper, a suspension structure-based triboelectric-electromagnetic-piezoelectric hybrid generator (SS-TEPG) with the innovative strategy appropriately integrates suspension and damping structure for jointly achieving high efficiency wind and vibration energy harvesting with vibration attenuation function, consisting of a wind-driven triboelectric-electromagnetic hybrid generator (WD-TEHG), a vibration-driven piezoelectric energy generator and damper (VD-PEGD), and a spring-based energy dissipation structure. After the structural optimization, the vibration energy harvester delivered the instantaneous load power from 1.9 to 8.2 mW on varied vibration frequencies ranging from 8.3 to 31.2 Hz, the TENG and EMG modules of wind energy harvester delivered the instantaneous load power from 0.6 to 2.1 mW and 0.9 to 73.1 mW on varied wind speeds ranging from 2.9 to 16.2 m s−1, respectively, with a significant electrical energy output. The integrated damping structure by the combination of the vibration energy harvester and spring-based energy dissipation structure achieved a significant breakthrough in vibration attenuation of the self-powered device in the suspension scenarios. Moreover, a self-powered system equipped with a traditional hybridized power management (T-HPM) was demonstrated to co-manage three electrical outputs. A LTC 3588-based hybridized power management (L-HPM) with undervoltage lock function was further proposed to effectively co-manage three electrical outputs and provide the standardized typical output for the Bluetooth sensor, which achieved 94% reduction in power consumption compared with the traditional power management. Finally, it is verified that the self-powered system by a hybrid generator equipped with a LTC 3588-based hybridized power management has the characteristics of fast start-up process, short undervoltage charge accumulation process and high energy conversion efficiency, indicating the large-scale application prospects of unifying the energy harvesting in terms of natural wind and harmful vibration.

Reducing the Environmental Impact of Wireless Communication via Probabilistic Machine Learning

Machine learning methods are increasingly adopted in communications problems, particularly those arising in next generation wireless settings. Though seen as a key climate mitigation and societal adaptation enabler, communications related energy consumption is high and is expected to grow in future networks in spite of anticipated efficiency gains in 6G due to exponential communications traffic growth. To make meaningful climate mitigation impact in the communications sector, a mindset shift away from maximizing throughput at all cost and towards prioritizing energy efficiency is needed. Moreover, this must be adopted in both existing (without incurring further embodied carbon costs through equipment replacement) and future network infrastructure, given the long development time of mobile generations. To that end, we present summaries of two such problems, from both current and next generation network specifications, where probabilistic inference methods were used to great effect: using Bayesian parameter tuning we are able to safely reduce the energy consumption of existing hardware on a live communications network by 11% whilst maintaining operator specified performance envelopes; through spatiotemporal Gaussian process surrogate modeling we reduce the overhead in a next generation hybrid beamforming system by over 60%, greatly improving the networks' ability to target highly mobile users such as autonomous vehicles. The Bayesian paradigm is itself helpful in terms of energy usage, since training a Bayesian optimization model can require much less computation than, say, training a deep neural network.

Sizing and Simulation of a Photovoltaic Hybrid Energy System and Generator for the Electricity Supply of the Residence of the Governor of Mamou, Guinea

Sizing and Simulation of a Photovoltaic Hybrid Energy System and Generator for the Electricity Supply of the Residence of the Governor of Mamou, Guinea

Capacity Allocation in Distributed Wind Power Generation Hybrid Energy Storage Systems

Abstract The inherent variability and uncertainty of distributed wind power generation exert profound impact on the stability and equilibrium of power storage systems. In response to this challenge, we present a pioneering methodology for the allocation of capacities in the integration of wind power storage. Firstly, we introduce a meticulously designed uncertainty modeling technique aimed at optimizing wind power forecasting deviations, thus augmenting the controllability of distributed wind power variations. Subsequently, we establish a cutting-edge real-time dynamic optimization model for state of charge, which effectively mitigates the fluctuations associated with grid-connected wind power. Moreover, we employ a state-of-the-art distributed robust optimization algorithm to enhance the stability of the distributed wind power storage system. Through comprehensive simulation testing, our findings unequivocally demonstrate the efficacy of our approach in preserving a harmonious balance between wind power load and output demand, thereby assuring the unwavering operation of the entire system. Notably, our approach attains an exceptional capacity allocation efficiency of 91% in the rigorous wind power grid-smoothing test, outperforming comparable methodologies. Lastly, we proffer essential recommendations pertaining to attenuation optimization at the effective capacity level of the batteries, effectively safeguarding the long-term stability of the energy storage system.

Sizing stand-alone hybrid generation for seasonal irrigation pumping

This paper studies the generation to feed three stand-alone existing pumping systems in the province of Zaragoza (Spain), in the same area but with different consumption and irrigation needs. All of them are used only for half the year. We look for the optimal size of the generation mix, both economically and in reducing emissions. For simulation and optimization the program used is HOGA (Hybrid Optimization by Genetic Algorithms). It is considered diesel generation, photovoltaic and wind as well as storage. As renewable resources are almost identical in the three locations, the magnitude of energy demand and schedule are the distinctive parameters of each facility. We considered how to choose the optimum angle of the PV array, the preference between the solar and wind and the desirability of whether or not the diesel generator. The results show the importance of seasonality and time consumption profile to determine the generation mix and to choose the optimum inclination of the field of photovoltaic conversion. Results also show that most emissions reductions are not always obtained by removing the genset.