Power Generation Units Research Articles

Collaborative Control Strategy of Electric–Thermal–Hydrogen-Integrated Energy System Based on Variable-Frequency Division Coefficient

To address the issues of diverse energy supply demands and power fluctuations in integrated energy systems (IESs), this study takes an IES composed of power-generation units, such as wind and photovoltaic units, along with various energy-storage systems, including electrical, thermal, and hydrogen storage, as the research subject. A collaborative control strategy is proposed for the IES, which comprehensively considers the status of diverse energy-storage systems like battery packs, thermal tanks, and hydrogen tanks. First, a mathematical model of the IES is constructed. Then, a dual-layer collaborative control strategy is designed, considering different operating modes of the IES, which includes a multi-energy-storage power allocation control layer based on second-order power-frequency processing and distribution and an adaptive adjustment layer for adjusting power-frequency coefficients based on adaptive fuzzy control. Finally, MATLAB is used to simulate and validate the proposed strategy. The results indicate that the collaborative control strategy based on variable-frequency coefficients optimizes the allocation of fluctuating power among multiple energy-storage systems, enhances the stability of bus voltage, reduces the deep charge and discharge time of battery packs, and extends the service life of battery packs.

Optimal control of grid-connected overvoltage of distributed photovoltaic power generation based on cluster division

To address the overvoltage problem caused by the reverse flow of current when a high proportion of distributed photovoltaic (PV) is connected to the distribution network, this paper proposes a grid-connected voltage regulation control strategy based on the cluster division of the Distributed Model Predictive Control (DMPC) algorithm. Firstly, the overvoltage responsibility of each node is calculated using the Shapley value method. This is combined with k-means clustering to achieve effective cluster division, enabling dynamic adjustment of the active and reactive power of photovoltaic power generation units to stabilize regional voltage. Secondly, a group grid-connected voltage control strategy is introduced. This strategy controls the active and reactive power outputs by integrating real-time power output and voltage information from PV generating units in the region with the DMPC algorithm, ensuring overall voltage stability of the grid-connected system. Finally, actual overvoltage data from a 10 kV distribution line in the Dingxi power grid, Gansu Province, is used to verify that under the proposed control strategy, PV grid-connected overvoltage nodes are maintained within 1.06 p.u. The control effect is improved by a margin of 0.05 compared to traditional control methods. This demonstrates the effectiveness of the grouped grid-connected voltage regulation control strategy, achieving smoother voltage regulation performance in distributed PV grid-connected systems.

Optimizing reserve-constrained economic dispatch: Cheetah optimizer with constraint handling method in Static/Dynamic/Single/ Multi-Area Systems

Managing the power-generating units on the horizon of one-day scheduling considering all practical equality, inequality, and realistic constraints has always been a significant challenge in power systems. The constraints, such as valve-point effects, prohibited operation zones, transmission losses, and ramp rate limits corresponding to dynamic economic dispatch, change the optimization problem to a complex, nonlinear, non-smooth, high-dimensional, and non-convex one. Therefore, an efficient algorithm and a suitable constraint handling method are needed to solve practical constrained dynamic economic dispatch (DED). This paper proposes a newly developed Cheetah optimizer (CO) that coincides with a backward-forward constraint handling method to tackle the optimum operational cost. The CO algorithm’s performance is verified using eight DED and ED test cases from five different systems. The suggested technique is compared with several state-of-the-art optimization algorithms regarding the effectiveness of achieved results. Numerical results evaluate the performances of the CO advantages on the benchmarks and the DED cases where the results of 5-,10- and 30-unit systems are enhanced in different cases. To achieve a higher level of realism in modeling the ED and DED problem, adopting a multi-area DED (MADED) approach has emerged as a promising strategy. In this paper, three distinct cases of MAED and MADED problems are investigated to demonstrate the effectiveness of the proposed method. Specifically, in cases involving DED-10 and 30 units, two-area 40 units ED, and four-area 40 units DED, significantly improved solutions were obtained compared to previous studies.

Impact of energy integration on post-combustion CO2 capture: A comparative analysis of chemical absorption and calcium looping technologies in coal-fired and natural gas combined cycle power plants

Chemical absorption (Che) and calcium looping (CaL) have been recognized as the promising technologies for post-combustion CO2 capture (PCC) applied in fossil fuel power plants. However, there is a lack of understanding of how the energy integration affects the performance difference of the two separation technologies employed for the retrofitted coal-fired (CFPP) and natural gas combined cycle (NGCC) power plants. Thus, this study aims to provide a new perspective by investigating power generation fuel and heating fuel from energy conversion and transfer pathways. Results indicate that in the case of CFPP-PCCs, adopting the CaL technology can enhance the initial parameters of the steam cycle and reduce the heat transfer temperature difference for the utilization of heating fuel, where the heat transfer exergy destruction of heating fuel drops from 27.9 % to 15.1 % compared to the Che capture system. Conversely, for NGCC-PCCs, due to the superior performance of the combined cycle, the adoption of the CaL technology undermines the advantages of the heat transfer and power generation units, resulting in inferior performance compared to the Che capture system in most conditions. Results implicate that the degree of difference in energy conversion and transfer pathways between the power generation fuel and the heat supply fuel directly determines the performance of the capture system. Thus, concentration CO2 along with the efficient fuel conversion will be a promising direction for the innovation of capture technologies.

Sustained energy generation from unusable waste steel through microbial assisted fuel cell systems

In the present study, a novel green energy generation process assisted with Microbial Fuel Cell (MFC) principle for generation of electricity from used or wasted steel is explored. Through a unique approach, unused and other steel waste are recast by simple re-melting with a flexible wide composition for generation of green energy. A microbial-assisted electron transfer derived from the degradation of the steel material is utilized for production of green energy in a microbial galvanic reactor system. A. ferrooxidans acts as biocatalysts, facilitating the oxidization of ferrous ion (Fe2+) to ferric ion (Fe3+). The reaction takes place on the biofilm matrix which results in oxidised reactive zones that endorses further degradation or dissolution of Fe anode. This consequently results in achieving the highest power density as high as 4.92 ± 0.03 mW/cm2 at a current density of 0.01 ± 9 mA/cm2. The total cost of the unusable steel anode and other accessories are roughly estimated to be 7.94 $/m2 and 178.54 $/m2 and the gain from unit power generation is estimated to be 3.79 $/W, assuming continuous operation of 4.92 ± 0.03 mW/cm2. The present study presents a potent methodology/strategy for the generation of sustainable bioenergy from low-cost, unusable steel materials, which cannot be anyway used as such in other battery systems, say iron air cells/batteries.

A self-regulated wind energy harvester with automatic mode transition strategy enabled by wind-induced centrifugal force

Abstract Natural wind energy distributes over a wide speed range, but conventional wind turbines with high electrical damping can only work under relatively high wind speeds, whereas breeze harvesters with low electrical damping suffer from limited electric outputs despite their low start-up wind speeds. To solve this dilemma, we report herein an automatic mode transition (AMT) strategy for rotary wind energy harvesters (WEHs) to realize self-regulation of electrical damping according to ambient wind speeds. The superior performance achieved with the AMT strategy has been demonstrated through an AMT-WEH comprising a low-damping as well as a high-damping power generation units. Theoretical analysis and experimental tests reveal that the AMT-WEH not only can work in low-damping single-unit mode to harvest weak wind (≥ 2.6 m/s), but also can switch spontaneously to high-damping dual-unit mode to efficiently capture strong wind. As connected with matched electrical loads, the AMT-WEH can switch to dual-unit mode and generate high average power of 188.2 mW under 8.2 m/s wind, which is more than 11.5-fold increase as compared with that (16.3 mW) of a conventional WEH without the AMT design. This study demonstrates a distinctive AMT strategy for WEHs to effectively exploit wide-speed-range wind energy toward self-contained sensors and electronics.

4E analysis and optimization comparison of solar, biomass, geothermal, and wind power systems for green hydrogen-fueled SOFCs

Integrating renewable energies with hydrogen production via electrolysis and utilizing hydrogen as a fuel for solid oxide fuel cells (SOFCs) presents a synergistic approach towards sustainable energy generation. This coupling offers enhanced flexibility, allowing for efficient energy storage and distribution, thereby addressing intermittency issues associated with renewable sources. Additionally, the utilization of hydrogen in SOFCs enables high-efficiency power generation with reduced emissions, contributing to the transition towards a cleaner energy landscape. In the present study, four types of renewable energies, namely solar, biomass, geothermal, and wind, produce hydrogen by coupling power generation units and a proton exchange membrane electrolyzer (PEME). Then, the produced hydrogen is stored and used for later utilization in an SOFC subsystem. A 4E (energy, exergy, exergy-economic, and environmental) study is conducted for the proposed systems through a sensitivity study and design optimization. In the best output performance mode, the best exergy efficiency is obtained by the biomass-based system, which is equal to 9.40 %, and the lowest values for total cost rate and unit cost of outputs are achievable by the geothermal-based system, with values of 27.72 $/h and 43.23 $/GJ.

Decentralized optimization for multi-microgrid systems via enhanced concurrent alternating direction method of multipliers

Abstract In microgrid systems, the diversity of power sources, limitations in network communication, and the growing emphasis on privacy protection for power generation equipment present significant challenges to traditional centralized dispatch methods. Within a system comprising multiple microgrids, a comprehensive assessment is conducted, taking into account the operational costs of conventional power generation units, the curtailment costs associated with renewable energy generation, and the depreciation costs of energy storage systems. Based on the distribution of power generation units and energy storage devices within the grid, a decentralized dynamic economic dispatch framework is established. Leveraging this groundwork, we have introduced a well-conceived and practical partitioning scheme specifically designed for the multi-microgrid landscape. An improved synchronous computational Alternating Direction Method of Multipliers (ADMM) is proposed, which, by exchanging only voltage phase information between adjacent areas during each iteration, enables parallel economic dispatch calculations across regions. This approach significantly enhances solution efficiency while ensuring overall optimization. Tested on a real-world microgrid case, the results validate the accuracy and practicality of the algorithm.

Self-powered human movement measurement with a unidirectional ratchet driven wearable energy harvester

A large amount of energy is generated during human movement which is mostly not effectively utilized. To collect human movement energy and utilize it rationally, a wearable piezoelectric-electromagnetic energy harvester (WPEEH) driven by a unidirectional ratchet is proposed, which adopts the principle of up-conversion to convert mechanical energy into electrical energy. The electromagnetic power generator unit is used to obtain energy to power the sensing circuit, while piezoelectric generator unit can be used for both energy generation and self-powered sensing. A spring push rod and a ratchet structure are used to convert the swinging of the human limb into the unidirectional rotation of the device to enhance its energy harvesting efficiency. The theoretical model of the WPEEH is established, and the experimental test platform is built. The results show that the WPEEH is able to generate a maximum power of 17.2 mW at an oscillation frequency of 1.5 Hz. In the actual wearable test, the proposed energy harvester is able to supply the harvested energy to the low-power electronic devices through capacitors, and it enables to light up 42 LEDs as well as to drive the digital thermo-hygrometer to work continuously and stably. Apart from having excellent properties of a high output power and low drive frequency, the proposed energy harvester also exhibits a high energy density (7.1 × 10–5 W/cm3). What’s more, the speed of human movement can be predicted and calculated for different individuals by testing the results of the swing frequency with a maximum error of 2.71 %. The investigation proves that the proposed WPEEH can measure human movement and has great potential in the field of power supply for low-power electronic devices.

Addressing thermal challenges in hydrodynamic bearings: A contemporary review of strategies and technologies

Hydrodynamic bearings are integral components in various industrial sectors, including aerospace, defense technologies, and power generation units etc. Advancements in modern technology have driven the evolution of bearings to withstand the high temperatures, increased speeds, and additional load demands of contemporary operations. Some of the prime consequences of high temperatures include thermal deformation, misalignment, viscosity degradation, reduced oil film thickness, reduced load carrying capacity and premature failure due to bearing seizure. Researchers have rigorously addressed the persistent thermal challenges posed to hydrodynamic bearings, achieving significant advancements over the years. Key developments include innovative bearing pad designs, optimal materials, coating technologies, advanced computational software, novel lubrication methods, and efficient monitoring techniques. The introduction of materials with tailored properties such as high heat conductivity, high strength, and low-friction coatings has greatly enhanced bearing performance. Additionally, advanced computational software like ANSYS CFX, Fluent, and COMSOL, adaptive lubrication methods, and real-time temperature sensors have significantly improved the performance of critical systems, including hydro power plants. This review paper summarizes significant developments and investigations carried out to mitigate thermal effects in hydrodynamic bearings, and hence provides a comprehensive in depth details of the subject matter. Even though there has been a lot of progress in the field of hydrodynamic bearings, continuous research is important to tackle issues related to sustainability, industry-specific obstacles, developing technologies, and dynamic operating conditions.

An integrated binary metaheuristic approach in dynamic unit commitment and economic emission dispatch for hybrid energy systems

The current generation portfolio is obligated to incorporate zero-emissions energy sources, predominantly wind and solar, due to the depletion of fossil fuels and the alarming rate of global warming. In the current scenario, power engineers must devise a compromised solution that not only advocates for the adoption of renewable energy sources (RES) but also efficiently schedules all conventional power generation units to balance the increasing load demand while simultaneously minimizing fuel costs and harmful emissions that are currently addressed by Unit Commitment (UC) and Combined Economic Emission Dispatch (CEED) problem solutions. However, the integration of renewable energy resources (RES) further complicates the UC-CEED problem due to their intermittent nature. Recently, metaheuristic algorithms are acquiring momentum in resolving constrained UC-CEED problems due to their improved global solution ability, adaptability, and derivative-free construction. In this research, a computationally efficient binary hybrid version of crow search algorithm and improvised grey wolf optimization is proposed, namely Crow Search Improved Binary Grey Wolf Optimization Algorithm (CS-BIGWO) by inclusion of nonlinear control parameter, weight-based position updating, and mutation approach. Statistical results on standard mathematical functions prove the supremacy of the proposed algorithm over conventional algorithms. Further, a novel optimization strategy is devised by integrating enhanced lambda iteration with the CS-BIGWO algorithm (CS-BIGWO-λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}) to solve a day-ahead UC-CEED problem of the hybrid energy system incorporating cost functions of RES. For the model, a day-ahead forecast of wind power and solar photovoltaic power is obtained by using the Levy-Flight Chaotic Whale Optimization Algorithm optimized Extreme Learning Machines(LCWOA-ELM). The proposed algorithm is tested for the UC-CEED solution of an IEEE-39 bus system with two distinct cases: (1) without RES integration and (2) with RES integration. Several independent trial runs are executed, and the performance of the algorithms is assessed based on optimal UC schedules, fuel cost, emission quantization, convergence curve, and computational time. For case 1, the proposed algorithm resulted in a percentage reduction of 0.1021% in fuel cost and 0.7995% in emission. In contrast, for test case 2, it resulted in a percentage reduction of 0.12896% in fuel cost and 0.772% in emission with the proposed algorithm. The results validate the dominance of the proposed methodology over existing methods in terms of lower fuel costs and emissions.

Harvesting multidirectional wind energy based on flow-induced vibration triboelectric nanogenerator with directional tuning mechanism

Wind-induced vibration (WIV), as low-velocity wind energy utilization technology in agricultural environment, has significant advantages. Nevertheless, there is a mismatch between the variability of wind direction and the work mode of triboelectric nanogenerator (TENG), which leads to a sharp decline in the performance of triboelectric power generation. This work proposes a TENG based on multidirectional WIV (TENG-WIV), which mainly contains triboelectric power generation unit, guide-wing and triboelectric direction sensor. By introducing the directional tuning mechanism based on guide-wing, the TENG-WIV aims to break the constraints of single wind direction response and effectively respond to the wind direction within 360° range, thereby realizing multidirectional wind energy harvesting and sensor power supply. The empirical findings indicate that the output voltage and current of triboelectric power generation unit are in the ranges of 62–241 V and 0.25–1.21 μA, respectively, at the wind velocities of 1.23–5.13 m/s. At a wind velocity of 3.18 m/s, the unit achieves an out-power peak of 0.09 mW. Furthermore, the triboelectric direction sensor can respond to changes in 8 directions and has wind direction monitoring potentiality. The directional tuning mechanism endows flow-induced vibration energy harvesters with an all-around multidirectional sensitivity.

Closing the Loop between Plastic Waste Management and Energy Cogeneration: An Innovative Design for a Flexible Pyrolysis Small-Scale Unit

This study proposes a simplified unit that can be employed in an industrial facility for the utilization of its own abundant plastic waste, primarily from discarded packaging, to achieve full or partial energy autonomy. By converting this waste into synthetic pyrolysis oil equivalent to 91,500 L, the industry can power a combined heat and power generation unit. The proposed unit was designed with a focus on maintaining high temperatures efficiently while minimizing oxygen exposure to protect the integrity of hydrocarbons until they transform into new compounds. Pyrolysis stands as a foundational procedure, paving the way for subsequent thermochemical transformations such as combustion and gasification. This study delves into the factors affecting pyrolysis and presents analytically the mathematical formulations and relevant calculations in order to effectively design and apply a real-life system. On this basis, fuels from plastic waste can be produced, suitable for utilization in typical equipment meant to produce heat, estimated for six months’ operation and 800 MWh of electricity. This study enhances the transition towards a more circular and resource-efficient economy with technologies that unlock the latent energy contained within the discarded matter. Additionally, it demonstrates the feasibility of a moderate investment in a co-generation system for industries utilizing 568 tonnes of plastic waste per year. The design and accurate calculations of this study highlight the theoretical potential of this technology, promoting environmental sustainability and resource conservation.

Underwater blade-free triboelectric nanogenerator for harvesting current energy in low-speed current

Ocean current energy bears the characteristics of wide distribution and high energy density. Harvesting current energy as the in-situ power for distributed ocean sensors will greatly enhance the sustainability of ocean sensing. In many parts of the ocean, the current speed is not desirable (low or unstable) for conventional current energy harvesting devices. Here, an underwater blade-free triboelectric nanogenerator (UBF-TENG) is developed to effectively utilize the low-speed currents through the flow-induced vibration (FIV). The power generation unit is fully enclosed inside the shell, effectively reducing the direct impact and underwater corrosion. The study demonstrates that within the established experimental parameters space, the optimized UBF-TENG can facilitate a start-up speed as low as 0.14 m/s. The UBF-TENG has achieved a maximum open-circuit voltage output of 250 V and a maximum short-circuit current output of 2.2μA at 0.76 m/s. The charging capacity of the UBF-TENG is tested with various capacitors, demonstrating the application potential of the UBF-TENG as an in-situ power supply underwater.

Fuel-economy-optimal power regulation for a twin-shaft turboshaft engine power generation unit based on high-pressure shaft power injection and variable shaft speed

Due to the high power-to-weight ratio characteristic of turboshaft engines, the power generation unit based on it holds immense potential in the hybrid electric propulsion system (HEPS) of flying cars. To mitigate environmental pollution and reduce fuel consumption, while enhancing the fuel economy of turboshaft engine power generation unit (TEPGU) across the entire power output range, this paper investigates a dual-motor electronic regulation architecture for twin-shaft TEPGU. According to the different variable combinations of TEPGU architecture, two modes and their respective fuel-economy-optimal power regulations are proposed. Initially, by considering the efficiency distribution of motors, we construct an Extended co-working balance model based on the Newton-Raphson method. Subsequently, different operating modes are proposed and discussed, studying the characteristic laws of the power generation unit under each mode. For the variable speed mode and the power split mode, this article proposes a shaft-speed-feature-projective searching (SFPS) method and a multi-dimensions-feature-projective searching (MFPS) method based on characteristic dimensionality reduction projection. Finally, a comparative analysis of the fuel-saving effects of the SFPS and MFPS regulation methods is conducted, and the reasons for enhancing fuel efficiency are discussed. The simulation results show that the model of TEPGU is in good agreement with the experimental data, and the error of specific fuel consumption(SFC) in the full power range is less than 5.7 %. Besides, comparative results indicate that the strategies based on MFPS and SFPS can achieve a maximum instantaneous fuel consumption reduction of 14.38 % and 10.82 %, respectively. The MFPS strategy exhibits a fuel consumption saving of 12.69 % throughout the driving cycle, demonstrating superior performance in fuel economy.

Coordinated planning of thermal power, wind power, and photovoltaic generator units considering capacity electricity price

AbstractWith the implementation of China's carbon reduction policies, the role of thermal power units will transition to a regulating power source. Hence, the electricity market fails to accurately reflect the capacity value of thermal power units, resulting in potential future losses for these units. Therefore, it is imperative to establish a rational capacity compensation mechanism that guarantees the revenue of thermal power units and offers effective investment and construction signals. Therefore, this paper proposes a capacity compensation mechanism for thermal power units based on effective capacity. To achieve this, a two‐layer power source planning model is established. At the upper level of the model, the installed capacity and capacity price of various types of power sources are optimized, while minimizing the operating costs of the planning horizon year under constraints such as annual net profit of units. The lower level focuses on the operation of typical days, optimizing the output of various types of units. Through case analysis, it can be concluded that the proposed model can achieve coordinated planning of capacity and capacity prices for various types of units, effectively ensuring the economic efficiency of the system while safeguarding the revenue of each unit.

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.

A comparative thermodynamic assessment of microwave-assisted and conventional pyrolysis of biomass in poly-generation systems using coupled numerical and process simulations

Biomass is a unique renewable carbon resource that can be flexibly converted into biofuels, chemicals, and biomaterials using pyrolysis technology. Microwave-assisted pyrolysis (MAP) has gained increasing attention due to its faster and more uniform heating characteristics compared to conventional pyrolysis (CP). However, thermodynamic assessments of biomass MAP-based systems that consider detailed pyrolytic product information are lacking. This study simulated biomass-derived poly-generation systems employing MAP with microwave absorbers (MAP-S) and CP with solid heat carriers (CP-S). The proposed systems included pretreatment, pyrolysis, bio-oil rectification, hydrodeoxygenation, and combined cycle power units, producing biofuels, chemicals, and electricity. To obtain operating information that aligns more closely with engineering reality, pilot-scale numerical models integrating reaction kinetics and transport processes were established for the MAP and CP reactors. These models were validated against lab-scale experimental results after scaling down the models’ geometrical sizes. The results of product yields and energy consumption from numerical simulations were used to support the process simulation. Simulation results showed that the energy efficiency and net power generation efficiency of MAP-S were 59.37 % and 17.78 %, respectively, lower than the 67.19 % and 18.22 % of CP-S. In CP-S, the exergy of materials primarily moved towards the chemicals production units with an exergy efficiency (ηex) of 60.0 %, whereas in MAP-S, more exergy flowed towards the power generation units with a lower ηex of 58.46 %. Notably, the exergy destruction rate (Exd) for CP-S was 3.91 MW, higher than the 3.65 MW for MAP-S. Moreover, the CP-S achieves a higher carbon utilization efficiency at 42.32 %, compared to 35.03 % for the MAP-S. For the pyrolysis units, although the CP unit experienced higher heat losses (0.31 MW) compared to the MAP unit (0.1 MW), the ηex for the CP unit was higher due to a lower Exd. Additionally, CP-S consumed more hydrogen in the hydrodeoxygenation units, whereas MAP-S might achieve self-supply of hydrogen by adjusting operation conditions and technology processes.

Directional Adaptive Triboelectric Nanogenerator with Wind-Wave Synergy.

To enhance the adaptability and synergy of the triboelectric nanogenerator (TENG) in a wave environment, this paper introduces a directional adaptive triboelectric nanogenerator (DA-TENG) with wind-water synergistic action for wave energy collection. An innovative design combining a wind vane on the top and fan-shaped blade electrodes internally allows the DA-TENG to adjust its swinging direction adaptively to align with the direction of wave motion. The internal multiple power generation units work in coordination, effectively addressing the issues of low efficiency associated with spherical TENGs in capturing multidirectional wave energy. The DA-TENG demonstrates superior performance under various wind speed conditions, showcasing its practical application potential. Experimental results show that the DA-TENG, equipped with a single tail wind vane and a 700 g mass block, can achieve an output voltage, current, and charge of 374.97 V, 84.77 μA, and 622.69 nC under a mild wind environment. Its peak power density reaches 7.51 W m-3, enabling successful data transmission for a wireless temperature and humidity sensor and powering 248 light-emitting diodes (LEDs). This research expands the possibilities of omnidirectional wave energy collection and the collaborative operation of multiple power generation units, offering an effective method for powering low-power maritime devices.

PENGARUH INOVASI PRODUK DAN STRATEGI PEMASARAN TERHADAP PENDAPATAN PADA KELOMPOK BINAAN INDONESIA POWER DI DESA RANUKLINDUNGAN GRATI PASURUAN

Product innovation and marketing strategy are considered important factors that can increase the competitiveness and income of the target group. Problems that occur in groups assisted by PT. PLN Indonesia Power Generation Unit (PGU) Grati in Ranuklindungan Village is located at an unstable income that even decreases every month. This research aims to analyze the influence of Product Innovation and Marketing Strategy on Income in the Indonesia Power Assisted Group in Ranuklindungan Village, Grati, Pasuruan. The type of research used in this research is quantitative. The population used is members of the Indonesia Power assisted group in Ranuklindungan Grati Pasuruan Village. The sampling technique used a saturated sampling technique using a sample of 37 respondents. The analysis used is research instrument testing in the form of validity and reliability testing, descriptive analysis, classical assumption testing, multiple linear regression analysis, hypothesis testing and determinant coefficient testing. The research results of the Product Innovation variable partially have a significant effect on Income in the Indonesia Power assisted group in Ranuklindungan Grati Pasuruan Village, this means that Product Innovation plays a very important role in Income. And the Marketing Strategy variable partially has a significant effect on Income in the Indonesia Power assisted group in Ranuklindungan Grati Pasuruan Village, this means that the Marketing Strategy variable also plays a very important role in Income. The determinant coefficient (R2) obtained a value of 0.862 which shows that the influence of Product Innovation and Marketing Strategy can influence Revenue by 86.2%. while other variables outside the scope of the research were 13.8%. Keywords: Product Innovation, Marketing Strategy and Opinion.