Generation System Research Articles

Thermodynamic analysis of power generation thermal management system for heat and cold exergy utilization from liquid hydrogen-fueled turbojet engine

Hydrogen propulsion is generally treated as the ultimate net zero-emission option for aviation, therein liquid hydrogen storage appears to provide the only feasible solution for aircraft with the constraints imposed by aircraft weight and volume. Hydrogen liquefaction consumes a great amount of energy, which significantly boosts the cost of hydrogen as an aviation fuel. Besides the H2 chemical exergy for combustion to provide thrust, the H2 physical exergy in the form of cold energy is also a kind of high-quality clean energy to produce power output, which offers great opportunities to achieve cost-effective use of hydrogen fuel. Thus, this paper presents a Rankine cycle and H2 direct expansion cycle (RC-DEC) combined power generation thermal management system for the simultaneous utilization of exhaust gas heat exergy and hydrogen fuel cold exergy from the liquid hydrogen-fueled turbojet engine. In the Rankine cycle, the transcritical mode is applied on the hot side while the liquid separation condensation concept is adopted on the cold side to achieve better thermal matchings with heat and cold sources. The hydrocarbon/inert gas binary mixture is proposed as the working fluid of the Rankine cycle. The effects of key thermodynamic parameters and the influence of Para-Ortho hydrogen conversion on system performance are discussed, then a comparison of the mixture working fluid is conducted. Results show that there exists an optimal separation temperature ratio and condensation pressure of RC to obtain maximum total net power output. As the DEC expander inlet pressure increases, the total net power output first increases and then levels off. The introduction of the Para-Ortho hydrogen conversion has a negligible impact on net power output but leads to a significant reduction in the exergy efficiency, which is attributed to the cold energy release nature of Para-Ortho hydrogen conversion. The results of the working fluid comparison indicate that the optimal inert gas retardant for CH4 is Kr, while those for C2H6 and C3H8 are Xe to achieve the maximum net power output and exergy efficiency of the proposed power generation system. Among them, C2H6/Xe(0.6/0.4) obtains the maximum net power output of 2717.9 kW and maximum exergy efficiency of 33.1%, which suggests an opportunity to provide megawatts of electrical power for the aircraft in place of the APU.

Particle swarm optimization of electric power generation via green hydrogen considering the performance of the electrolyzer cell

The replacement of energy generation models, from fossil fuels to carbon neutral ones, requires a significant transformation in the generation and consumption of electricity. This work highlights Green Hydrogen as an essential potential to intensify the energy generation process based on renewable sources. The article presents two studies on energy generation models, via Green Hydrogen: Case (i), study of the behavior of the Electric Activation Voltage with ohmic loss influenced by the control variables Electric Current and Operating Temperature. Case (ii), study of the behavior of the Electric Activation Voltage with ohmic loss influenced by the control variables Electric Current and Operating Pressure. For both cases, a computational model stands out, the Proton Exchange Membrane electrolyzer cells, indicated for the generation of renewable energy, from Green Hydrogen. For both cases, a Bioinspired Computing methodology was applied in order to optimize the process. The Optimization technique means, among the various definitions, determining the best set of results, considering the restrictions of the studied phenomenon. Studies indicate that this strategy is increasingly intrinsic to our reality. This paper advocates Particle Swarm Optimization as a mechanism capable of finding the best set of solutions for mathematical models related to Energy Systems. The Swarm Algorithm can be represented as a set of particles that navigate through a space of solutions, where the main element of this method is the exchange of information between the particles of the population, which allows collective mobilization towards the optimal solution. In this case specifically, the values of Electrical Voltage, Electrical Current, Operating Temperature and Pressure form the Particle Examination. The results were exceptional for the Green Hydrogen energy generation system studied. The Particle Swarm Optimization Algorithm was applied to the objective function of multiple variables and satisfactorily incorporated the restrictions and conditions of the electrolysis system. The measurements obtained highlight that the Optimal Values are lower than the Average Values, for each variable analyzed in energy generation, in an electrolyzer. The solution achieved will be of great applicability in the study of energy efficiency in structures linked to this relevant category of renewable energy generation.

LCL-T Module Reduction of Offshore Photovoltaic Power Generation System Based on Current Feedback-routh Approximation Method

The rapid development of offshore photovoltaic power generation has attracted more and more attention. Aiming at the problem of poor output power quality caused by the randomness and intermittentness of offshore photovoltaic power generation, LCL filters and isolation transformers are widely used on the AC side of photovoltaic power generation systems to improve the power quality of Grid-connected. Although this method has a good suppression effect on harmonics and DC components, its higher order will result in a larger amount of calculation, especially in the simulation of large-scale photovoltaic grid-connected systems, the operating speed will be too slow. In order to increase the simulation rate while ensuring the quality of the output power, the high order LCL-T (LCL filter and isolation transformer) module of the photovoltaic power generation system is reduced in order. When the transformer is not saturated, the LCL-T module reduction method based on the weighted current feedback method is adopted, and the purpose of simplification is achieved through the zero-pole cancellation of the transfer function; When the transformer is saturated, the LCL-T module reduction method based on the Routh approximation method is adopted, Use advanced mathematics formulas to reduce the order of high-order system equivalent processing. The PSCAD/EMTDC simulation software verifies the off-grid characteristics and simulation rate of the reduced-order model.

Experimental assessment of a solar vortex engine integrated with sensible TES at different collector configurations

This study presents an experimental investigation of the effect of different solar collector geometrical parameters on the solar vortex engine's (SVE) performance. The first parametric study is concerned with a solar vortex power generation system's diameter, inlet height, and thermal energy storage (TES) extension. The experimental results revealed that extending the TES by 1 m outside the canopy significantly increases thermal efficiency by 62 %. In addition, increasing the diameter of the solar collector from 8.8 m to 10.8 m, with an extra 1 m extended TES area, increased the air temperature rise by 57 %, while the outlet air velocity increased by 32 %. On the other hand, a reduction in the collector inlet height from 0.2 m to 0.15 increased the air temperature rise while decreasing the outlet air velocity and power output potential by mean values of 19 % and 48 %, respectively. The enhancement obtained from the extended area of TES is an important finding, as it increased the air temperature for a larger canopy size without extra cost. Therefore, increasing the absorption area or the TES outside the canopy is recommended. Also, further studies are essential to correlate the inlet height to the system's performance.

Research on Maximum Power Control of Direct-Drive Wave Power Generation Device Based on BP Neural Network PID Method

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability.

A Research Paper on Design & Development of HHO Generator

This abstract encapsulates the essence of the research paper focusing on the design, development, and testing of an HHO (Hydrogen-Hydrogen-Oxygen) generator. The study aims to investigate the feasibility and efficacy of HHO technology in producing hydrogen gas for various applications, including engine decarbonization, renewable energy production, and industrial processes. The research begins with an in-depth exploration of HHO generation principles, electrolysis techniques, and system components. Through systematic design and engineering processes, a prototype HHO generator is developed, integrating innovative features to enhance efficiency, safety, and reliability. Experimental testing is conducted to evaluate the performance of the HHO generator across a range of operating conditions. In this study, we explore the utilization of oxy-hydrogen gas (HHO) as an supplementary source for internal combustion engines. The electrolysis process of water with an electrolyte (such as KaOH) produces HHO gas, which can address fossil fuel shortages and mitigate environmental pollution.

Design and analysis of solitary AC–AC converter using reduced components for efficient power generation system

Considering different applications that require varied power and voltage conversion levels between AC grids and AC loads, AC–AC power conversion between AC grids has become an inevitable technology of energy management systems. An isolated converter for performing AC-to-AC transmission is proposed with minimal components for reduced losses and enhanced system efficiency. Single-phase direct buck-boost AC to AC converter with minimum components constituted with two dual IGBT control units (IGBT 1–IGBT 4), inductor (Lf), and capacitor (Cf) is proposed in this work. The MATLAB/Simulink platform is used to provide in-depth analysis of the circuit and components along with the design guidelines, and simulation outcomes of this proposed model. The voltage gains of G = 2.13, power factor of 0.97, and overall efficiency of 98% are achieved in the proposed system with minimum components of 4 switches, 2 conductors, and 1 capacitor and inductor respectively. The obtained results are compared with existing technology to evaluate the proposed system.

Operational Robustness Assessment of the Hydro-Based Hybrid Generation System under Deep Uncertainties

The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS’s robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS’s robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power.

Towards a Net Zero-Emission Electricity Generation System by Optimizing Renewable Energy Sources and Nuclear Power Plant

Towards a Net Zero-Emission Electricity Generation System by Optimizing Renewable Energy Sources and Nuclear Power Plant

Protonated g-C3N4/oxygen-doped g-C3N4 S-scheme homojunction fabricated by electrostatic self-assembly for photocatalytic hydrogen evolution and tetracycline hydrochloride degradation

S-scheme photocatalytic systems with high redox ability and separation efficiency of photoexcited charge carriers supply considerable prospects for environmental optimization and sustainable energy development. However, coupling well-suited reduction and oxidation components for target reactions remains a challenge worth exploring. Herein, an efficient S-scheme system for H2 generation and tetracycline hydrochloride (TCH) photodegradation based on protonated g-C3N4 (PCN) coupling with oxygen-doped g-C3N4 (OCN) is fabricated via a facile electrostatic self-assembly strategy. Intimate interfacial interactions originating from the ultrathin nanostructure and staggered energy band arrangement for the S-scheme charge transfer pathway provide compelling advantages for the highly efficient separation of photoinduced electron-hole pairs in the as-designed PCN/OCN homojunction. The in-situ irradiated X-ray photoelectron spectroscopy (ISI-XPS) techniques and electron paramagnetic resonance (EPR) measurements are applied to confirm the successful construction and the validity of the S-scheme charge transfer pathway. The obtained PCN/OCN composites with optimal ratio achieve a decent H2 generation rate of 6184.7 μmol g−1 h−1 outpacing the single PCN by approximately 4.8-fold, and 90.5 % TCH photodegradation efficiency is also realized within 90 min. This work provides a delicate fresh round of elevation for the exploration of an effective photocatalytic system.

A robust internal model control design for low-quality waste heat power generation systems

Recovering low-quality waste heat using industrial waste heat is challenging, and the reuse technology needs to erupt. Moreover, the gas source of low-quality waste heat is relatively volatile, which makes it challenging to keep the actual working condition of the plant stable. Therefore, it is inspiring to research the robustness of root-waste heat power generation processed measurement and control system to improve the stability of the plant operation. Hence, in this paper, we have applied uncertainty theory to analyze it and formulate the uncertainty model based on the Bode diagram. We also proposed a control method based on the uncertainty model, which combines robust control and internal model control to make the roots waste heat power generation system operate stably under the effect of external disturbances and changes of internal structure or parameters in actual operation. Experimental results show that the robust internal model control method has a speed deviation of no more than 7.9 r/min compared with the PID control method. The adjustment time to track the set value does not exceed 73.1 seconds within the allowed fluctuation range. The fluctuation variance is 30.95% of that of the PID controller. The dynamic performance is better, with strong anti-interference capability and significantly improved tracking performance. It ensures the stability of the roots-type waste heat utilization system, which is essential for future intelligent grid-connected power generation.

Reasonable Energy-Abandonment Operation of a Combined Power Generation System with an Ultra-High Proportion of Renewable Energy

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance.

DESIGNING OF DC GRID SOLAR-WIND HYBRID POWER GENERATION SYSTEM

Our project's main goal is to create a prototype hybrid renewable energy system that mixes solar and wind power. The system's goal is to directly feed energy from the turbine and solar panels into the DC grid. An inverter is also integrated to provide AC power. Our strategy emphasizes efficiency and simplicity by acquiring both AC and DC electricity from the project. Utilizing the complementing qualities of solar and wind energy, we want to develop a dependable and sustainable power generation system. We hope to show that combining renewable energy sources and maximizing energy output for both AC and DC applications is feasible with this creative design. Key Words: Dc grid, solar power generation, wind power generation, batteries, hybrid power generation

Thermo-economic feasibility study to utilize ORC technology for waste heat recovery from Indian nuclear power plants

A feasibility study is essential before installing a power generation system to recover waste heat from nuclear power plants, but not yet been done. Hence, nine possible waste heat locations of Indian nuclear power plants are identified and two feasible cases (case-1 and case-2) are deduced to use the organic Rankine cycle (ORC) as a bottoming cycle. Energy, exergy, economic and environmental performances are evaluated for feasible cases with three working fluids. Capital investment in alternator has been correlated based on market data and applied in economic analysis. The economic study is based on Net present value, Discounted payback period, Levelized cost of energy, Internal rate of return, Profit and per unit build-up cost of ORC to suggest whether the installation is worth to venture or not. The result shows that below 41 °C condenser temperature, case-2 based bottoming ORC should be the priority to install and at the availability of sufficient funds, both cases can be installed, which will cumulatively produce 486.2 kW of electricity from waste energy with a total of 201.14 thousand USD annual profit from the total capital investment of 723.74 thousand USD. In 40 years of the project's lifetime, a total of 1.317 million USD will be used if both cases are employed and the invested cost will be returned in 8.3 years.

High‐Performance Self‐Powered Flexible Thermoelectric Device for Accelerated Wound Healing

AbstractElectric signal accelerates full‐thickness wound healing in the clinic, which is usually generated by a large power generation system and requires delicate control by authorized personnel. Here, a self‐powered flexible and biocompatible thermoelectric device with exceptionally high power generation efficiency is developed. It generates 10 mV voltage at a temperature gradient of 10 K, outperforming all reported flexible thermoelectric devices. Accordingly, it can directly and efficiently convert the omnipresent heat in the skin to electricity at the microvolt level. The output electricity activates and upregulates the expression of Piezo1‐mediated pathways that are associated with tissue regeneration, accelerating the cell migration and proliferation in vitro and healing the wound 4 days faster in vivo. Importantly, the thermoelectric device fast‐heals the wound without involving any additional electric circuit such as an amplifier. These advantages will revolutionize the designing of self‐powered wearable bioelectronics for diagnosing, monitoring, and treating various pathological conditions employing the skin heat.

PED: a novel predictor-encoder-decoder model for Alzheimer drug molecular generation.

Alzheimer's disease (AD) is a gradually advancing neurodegenerative disorder characterized by a concealed onset. Acetylcholinesterase (AChE) is an efficient hydrolase that catalyzes the hydrolysis of acetylcholine (ACh), which regulates the concentration of ACh at synapses and then terminates ACh-mediated neurotransmission. There are inhibitors to inhibit the activity of AChE currently, but its side effects are inevitable. In various application fields where Al have gained prominence, neural network-based models for molecular design have recently emerged and demonstrate encouraging outcomes. However, in the conditional molecular generation task, most of the current generation models need additional optimization algorithms to generate molecules with intended properties which make molecular generation inefficient. Consequently, we introduce a cognitive-conditional molecular design model, termed PED, which leverages the variational auto-encoder. Its primary function is to adeptly produce a molecular library tailored for specific properties. From this library, we can then identify molecules that inhibit AChE activity without adverse effects. These molecules serve as lead compounds, hastening AD treatment and concurrently enhancing the AI's cognitive abilities. In this study, we aim to fine-tune a VAE model pre-trained on the ZINC database using active compounds of AChE collected from Binding DB. Different from other molecular generation models, the PED can simultaneously perform both property prediction and molecule generation, consequently, it can generate molecules with intended properties without additional optimization process. Experiments of evaluation show that proposed model performs better than other methods benchmarked on the same data sets. The results indicated that the model learns a good representation of potential chemical space, it can well generate molecules with intended properties. Extensive experiments on benchmark datasets confirmed PED's efficiency and efficacy. Furthermore, we also verified the binding ability of molecules to AChE through molecular docking. The results showed that our molecular generation system for AD shows excellent cognitive capacities, the molecules within the molecular library could bind well to AChE and inhibit its activity, thus preventing the hydrolysis of ACh.

A novel full-process test bench for deep-sea in-situ power generation systems

A novel full-process test bench was developed to replace lengthy and costly deep-water experiments. This platform can accurately simulate the dynamic characteristics of hydrokinetic turbines and can be used to evaluate their power-supply capabilities under various conditions. The hydrokinetic turbine power model was established by obtaining discrete performance data through experimentally validated computational fluid dynamics simulations and building surrogate models using the response surface methodology. This approach offers higher accuracy and broader applicability than empirical models. Moreover, a stepper motor platform based on a speed control scheme is proposed for the first time that can achieve high-precision transient simulation with a simplified control mechanism. This platform was employed to assess the power supply capacity of two hydrokinetic turbines under constant and typical deep-sea flow speeds. The ductless Archimedes screw hydrokinetic turbine was found to be more suitable for the deep water application than the high-solidity horizontal axis turbine due to its high self-start capacity and power coefficient. Furthermore, a case study was conducted on the design of a deep-sea in-situ power generation system at Luzon Undercurrent. Results suggest that a ductless Archimedes screw hydrokinetic turbine with a 1000 mm radius can comfortably cater to the energy demands of miniature AUVs.

A Three-Port DC-DC Converter Combined Configuration Method for PV-Battery Power Systems based on Prognostic Anticipating Controller Algorithm

The Photovoltaic (PV) system is renewable energy developed nowadays in the power generation system and it is connected to the grid. This grid-tie PV system is used to generate power and utilize consumer applications, in the grid-tie PV system the output is not efficient because of the saturation of the sunlight in the PV array and it's affected the power quality and stability of this system. In this proposed Prognostic Anticipating Controller Algorithm (PACA) system, a DC synchronization with PV and ESS is proposed to achieve improved power quality and the losses are less to compare the existing method. Due to the concern with energy emergencies, the energy obtained from sunlight is considered the most capable conventional resource. Hence, the maximum power point tracking approach is necessary for obtaining enhanced efficiency from solar panels. In the case of Direct Current (DC) application, the output obtained from the Photovoltaic (PV) array cannot be directly connected to electronic devices. For regulating the output from the PV array, the DC-DC converter is provided in between the load and the array. The converter design plays a significant role in tracking the maximum power point of the solar panel. The PACA logic controller is employed in the generation of optimal control pulse for the DC-DC converter. Moreover, in the solar photovoltaic system, the steady-state operation is performed and the various solar irradiance results are analyzed.

Research on the Technical and Economic Development of Large Megawatt Wind Turbines Based on Medium-Voltage Electrical System

INTRODUCTION: With the advent of the "bidding era" and "parity era" in the wind power market, the competition of the whole machine factory is becoming more and more fierce, and the capacity of the single fan is getting larger and larger, which becomes the key to the design of the fan electrical system of the large-capacity unit (5.XMW or more). At present, the low-voltage wind power system (690V,1140V) is the common solution for wind turbines. However, due to the limitation of the cable section of low-voltage electrical system and the increase of the rated current of the generator, the increase of the capacity of a single machine makes more cables from the generator side to the grid, and the cost also increases.
 OBJECTIVES: Aiming at the future large megawatt wind power market, the medium voltage Doubly-Fed electrical system solution is proposed to increase the higher generation and electricity income of wind farms and reduce the manufacturing cost of wind farms.
 METHODS: The technology and economy of medium voltage and low voltage electrical system are compared.
 RESULTS: With the gradual increase of single capacity, the economy of medium pressure wind power generation system is getting better and better, and the higher the height of the tower, the better the economy. At the same time, the reduction of the rated current of the generator brings about the reduction of line loss and the increase of power generation. The number of cables is greatly reduced, and the construction cost and difficulty of cable laying will be greatly reduced.
 CONCLUSION: In response to the technical trend of large-capacity wind turbines in the future, the medium-voltage wind power generation system has a good application prospect, both from the economic and technical point of view.

Enhanced Heat Transfer in Thermoelectric Generator Heat Exchanger for Sustainable Cold Chain Logistics: Entropy and Exergy Analysis

This study investigates the application of thermoelectric power generation devices in conjunction with cold chain logistics transport vehicles, focusing on their efficiency and performance. Our experimental results highlight the impact of thermoelectric module characteristics, such as thermal conductivity and the filling thickness of copper foam, on the energy utilization efficiency of the system. The specific experimental setup involved a simulated logistics cold chain transport vehicle exhaust waste heat recovery thermoelectric power generation system, consisting of a high-temperature exhaust heat exchanger channel and two side cooling water tanks. Thermoelectric modules (TEMs) were installed between the heat exchanger and the water tanks to use the temperature difference and convert heat energy into electrical energy. The analysis demonstrates that using high-performance thermoelectric modules with a lower thermal conductivity results in better utilization of the temperature difference for power generation. Additionally, the insertion of porous metal copper foam within the heat exchanger channel enhances convective heat transfer, leading to an improved performance. Furthermore, the study examines the concepts of exergy and entropy generation, providing insights into the system energy conversion processes and efficiency. Overall, this research offers valuable insights for optimizing the design and operation of thermoelectric generators in cold chain logistics transport vehicles to enhance energy utilization and sustainability.