Stable Power Generation Research Articles

A Novel Algal–Algal Microbial Fuel Cell for Enhanced Chemical Oxygen Demand Removal

To enhance the removal of COD (Chemical Oxygen Demand) by microalgae, this study constructed a novel microalgae–microalgae microbial fuel cell system (AA-MFC). It investigated the coupling relationship between the COD treatment efficiency at the anode and the production of high-value microalgal products at the cathode, as well as explored the effects of different initial inoculum densities and light–dark cycles. The experiment first measured the operational performance of the newly constructed AA-MFC in open-circuit and closed-circuit modes, demonstrating that this novel AA-MFC could start up rapidly within 32 h and operate stably. The results showed that the AA-MFC enhanced the removal of COD and the growth of microalgae biomass at the anode while maintaining stable power generation. When the initial inoculation density of the anode was 1.2 × 108 cell/cm2 and the light–dark cycle time was 18:6 h, the AA-MFC had the most obvious promoting effect on the COD removal of the anode. Compared with normal culture conditions, the COD removal rate increased by 26.0% to 96.1%. These results indicate that the AA-MFC can not only effectively remove pollutants, but also promote the accumulation of high-value microalgae biomass.

Optimizing solar photovoltaic farm-based cogeneration systems with artificial intelligence (AI) and Cascade compressed air energy storage for stable power generation and peak shaving: A Japan-focused case study

This study proposes a novel solar cogeneration system that integrates compressed air energy storage units (CAES) and gas turbines (GT) with a solar farm consisting of photovoltaic panels. The primary objective of this research is to address the instability of solar energy production and help during peak energy consumption by utilizing CAES. The proposed system is modeled using EES software, and its performance is optimized using advanced artificial intelligence (AI) methods, including artificial neural networks and intelligent algorithms. The analysis identifies five critical decision variables that significantly impact system performance: the number of photovoltaic panels, CAES pressure ratio, CAES inlet pressure, gas turbine efficiency, and compressor efficiency. The results demonstrate that the optimized solar cogeneration system can achieve exergy efficiency of 36.44 % and a cost rate of 13.76 $/hour. The exergy analysis of the system indicates that the most significant destruction is related to the solar farm, gas turbine, and compressors. Furthermore, this study investigates the effect of weather in eight Japanese cities on system performance, considering two operating modes: with and without using system electricity (PV mode). The results show that the proposed solar cogeneration system has significant potential for clean electricity generation and CAES applications to overcome the instability of the solar system and help during peak energy consumption throughout the year. The study's findings highlight the attractive potential of integrating CAES and AI technologies in solar photovoltaic systems for stable and efficient power generation in Japan.

Research on supply-demand balance in China’s five southern provinces amidst fluctuations in regional wind and solar power generation and transmission faults

To investigate the supply-demand balance of regional power systems under extreme scenarios, this study employs the high-resolution power optimization model SWITCH-China to simulate the regional heterogeneity and randomness of extreme weather events in detail. Focusing on the five southern provinces, this study explores various impacts on the power generation side and the grid side under scenarios of reduced wind and solar power output, transmission line failures, and combined scenarios, proposing strategies for constructing a new power system. The main conclusions are: the reduction in wind and solar power output significantly affects provinces with a high proportion of these installations, like Guizhou, necessitating other stable power generation forms to compensate. Transmission line failures notably impact provinces like Guangdong, which rely heavily on imported electricity, requiring increased investment in new wind and solar installations and more self-generated power to offset the reduction in imported electricity. The combination of these factors amplifies their individual impacts, leading to the highest carbon reduction and electricity costs. The simulation results of this study are valuable for China’s five southern provinces in coping with extreme scenarios. As these provinces work on building a new power system and gradually retire fossil fuel units, they should expand the number and capacity of inter-provincial high-voltage transmission lines while considering system economics. Additionally, accelerating the deployment of energy storage is crucial for maintaining power system stability.

Enhancing off-grid wind energy systems with controlled inverter integration for improved power quality

Introduction. Off-grid wind energy systems play a pivotal role in providing clean and sustainable power to remote areas. However, the intermittent nature of wind and the absence of grid connectivity pose significant challenges to maintaining consistent power quality. The wind energy conversion system plays a central role in tapping renewable energy from wind sources. Operational parameters such as rotor and stator currents, output voltages of rectifiers and converters, and grid phase voltage variations are crucial for stable power generation and grid integration. Additionally, optimizing power conversion output through voltage gain analysis in boost converters is essential. Moreover, ensuring electricity quality via total harmonic distortion reduction in inverters is vital for grid compatibility. Goal. Enhancing the power quality of grid-integrated wind energy conversion systems. Methods. The proposed topology is implemented in MATLAB/Simulink with optimized control strategies for enhancing power quality in off-grid wind energy systems. Results. Control strategies with a grid-connected wind energy conversion system yields substantial improvements in power quality. This includes effectively mitigating voltage fluctuations and harmonics, resulting in smoother operation and reduced disturbances on the grid. Practical value. The proposed topology has proven to be extremely useful for off grid-integrated wind system. References 18, table 1, figures 11.

Analytical study on improving the efficiency and environmental friendliness of solid organic fuels

The purpose of this study was to analyse methods of increasing the efficiency and environmental friendliness of the use of solid organic fuels (SOF) in electricity generation. This study employed a comprehensive approach to the analysis and optimisation of technological processes, operational systems, and environmental aspects of the use of SOF. The study found that the use of modern technologies, such as gasification and pyrolysis, considerably increases the efficiency of converting SOF into electricity. Optimisation of boiler and turbine designs and automation of fuel supply systems helps to reduce energy losses and improve overall system efficiency. It was found that the use of new materials for boilers increases their resistance to corrosion and erosion, which extends the service life of the equipment. The study also showed that the introduction of gas cleaning and secondary combustion systems significantly reduces emissions of harmful substances, which improves environmental performance. An analysis of ash utilisation opportunities showed that its use as a fertiliser or construction material is a promising area. The study proved that an integrated approach to the use of SOF can substantially increase their efficiency and environmental friendliness. The findings of the study suggest that the use of innovative methods of combustion process control allows achieving more stable and efficient power generation. It was proved that the introduction of automated monitoring and control systems reduces operating costs and increases the reliability of equipment. The study also found that the use of advanced analytical tools to predict equipment wear and tear allows for prompt preventive maintenance, which further increases the efficiency and duration of uninterrupted operation of energy systems

Permeate gap thermo-osmotic system for simultaneous freshwater production, energy storage, and power generation

The emerging thermo-osmotic system enables harvesting low-grade thermal energy below 100 °C for the simultaneous production of fresh water and electricity. Considering the fluctuation of low-grade heat sources, a novel permeate gap thermo-osmotic system without pump pressurization was proposed in this study, which also allows for energy storage. A lab-scale setup with a 32 cm2 membrane area was built, by which a 2 W light bulb was successfully illuminated through the thermal energy-potential energy-electricity conversion process. In the pressurization process of the permeate side, the hydrophobic membranes with non-woven support exhibit higher pressure resistance, capable of withstanding pressures exceeding 200 kPa. Through experimental and theoretical analyses, the influences of different operation conditions and membrane properties on system performance were studied. Furthermore, utilizing solar energy as the heat source, a case study was conducted based on real meteorological data from a typical coastal city over a consecutive 72-hour period. In the solar-driven PGTO system with a power capacity of approximately 150 kW, the exergy efficiency can achieve 1.04 %, with a power density surpassing 0.1 W m−2, and an average daily freshwater production of over 70000 t. The energy storage function enables stable power generation within the 72 h, and it can sustain steady operation for nearly 7 h thereafter in the absence of sunlight. This study demonstrated the potential of the proposed PGTO system to efficiently utilize fluctuating low-grade thermal energy.

Submillimeter‐Scale Superlubric Triboelectric Nanogenerator

AbstractTriboelectric nanogenerator (TENG) for mechanical energy harvesting has been regarded as one of the most prospective energy technologies for the new era. However, inevitable material wear during triboelectrification results in output reduction and even failure of the TENG. In this work, a submillimeter‐scale superlubric TENG (SS‐TENG) is reported that enables ultra‐low friction coefficient (µ) and stable power generation. By using the micro/nano‐processing technology, the interdigital electrodes are embedded into the dielectric layer as a flat surface, on which the highly‐hydrogenated diamond‐like carbon (PLC) is deposited as the triboelectric layer to effectively reduce the friction coefficient. The frictional properties are systematically investigated at different parameters, in which a submillimeter‐scale (130 µm) superlubricity state (µ = 0.0084) is achieved at 4 N, 2 Hz and nitrogen atmosphere. Meanwhile, the SS‐TENG has a maximum power density of 3 mW m−2, which can remain stable at the superlubric condition. This work has first realized the freestanding‐mode superlubric TENG in submillimeter scale and provided a viable strategy for the development of long‐lifetime TENG, which may have great applications in frictional energy recovery from mechanical components, human joint motion, and the natural environment.

Simulation test of 50 MW grid-connected “Photovoltaic+Energy storage” system based on pvsyst software

With the implementation of the national “double carbon” strategy, the installed capacity of new energy power generation continues to grow, and stable photovoltaic power generation solutions have received increasing attention. The PV + energy storage system with a capacity of 50 MW represents a certain typicality in terms of scale, which is neither too small to show the characteristics of the system nor too large to simulate and manage. This study builds a 50 MW “PV + energy storage” power generation system based on PVsyst software. A detailed design scheme of the system architecture and energy storage capacity is proposed, which is applied to the design and optimization of the electrochemical energy storage system of photovoltaic power station. Based on the results of PVsyst operation simulation test, the operation performance of 50 MW “PV + energy storage” power generation system is explored. The results show that the 50 MW “PV + energy storage” system can achieve 24-h stable operation even when the sunshine changes significantly or the demand peaks, maintain the balance of power supply of the grid, and save a total of 1121310.388 tons of CO2 emissions during the life cycle of the system. The various parts of the system, including the photovoltaic array, the energy storage unit and the grid interface, demonstrated efficient collaborative performance in the simulation environment of PVsyst.The analysis of power generation shows obvious seasonal changes. The unit power generation is higher from March to September, and the more the power generation is the overall annual power generation shows good consistency and predictability under the regulation of the energy storage system. Through the analysis of different operating scenarios, the key parameters that affect the system performance are further determined, such as lighting conditions, battery storage capacity, power consumption device efficiency. For lighting conditions, the total radiation amount of the incident lighting surface takes the most proportion in the interval of 380–900 W/m2 and 25-60kwh/m2/Bin. The simulation test also reveals the important role of energy storage unit in power grid demand peaking and valley filling, which has an important impact on balancing the instability of photovoltaic power generation and improving the system response ability.

A pyramidal residual attention model of short‐term wind power forecasting for wind farm safety

AbstractWind power fluctuation significantly impacts the safe and stable operation of the wind farm power grid. As the installed capacity of grid‐connected wind power expands to a certain threshold, these fluctuations can detrimentally affect the wind farm's operations. Consequently, wind power prediction emerges as a critical technology for ensuring safe, stable and efficient wind power generation. To optimize power grid dispatching and enhance wind farm operation and maintenance, precise wind power prediction is essential. In this context, we introduce a joint deep learning model that integrates a compact pyramid structure with a residual attention encoder, aiming to bolster wind farm operational safety and reliability. The model employs a compact pyramid architecture to extract multi‐time scale features from the input sequence, facilitating effective information exchange across different scales and enhancing the capture of long‐term sequence dependencies. To mitigate vanishing gradients, the residual transformer encoder is applied, augmenting the original attention mechanism with a global dot product attention pathway. This approach improves the gradient descent process, making it more accessible without introducing additional hyperparameters. The model's efficacy is validated using a dataset from an actual wind farm in China. Experimental outcomes reveal a notable enhancement in wind power prediction accuracy, thereby contributing to the operational safety of wind farms.

Development of a hydrogen free-piston engine generator for range extenders

Free-piston engine generator (FPEG), as an important branch of range extender, is a very competitive development direction. In this paper, a hydrogen-fueled opposed-piston FPEG is proposed, which adopts a mechanical-pressurized structure and a two-layer control strategy based on the inner and outer dead center. The prototype well meets the requirements of stable power generation and vehicle loading. The experimental tests have been conducted, which show that the pure hydrogen is successfully ignited under the cold start condition, the combustion efficiency and generation efficiency reach 30 % and 20 % respectively, and the peak pressure is close to 40 bar. However, the prototype was unable to enter the stable operation stage due to frequent misfire phenomena. Based on the above, the causes of abnormal combustion were discussed and the energy loss of the prototype was calculated. The prototype was simulated to run in the stable operation stage finally, and the future optimization scheme based on control strategy and structure was concluded.

Direct methanol oxygen-ion conducting solid oxide fuel cell with an integrated in-situ cracking reactor

Methanol, as an indirect hydrogen storage medium rich in hydrogen, is considered an ideal fuel for fuel cells. Oxygen-ion conducting solid oxide fuel cells (O-SOFCs) powered by methanol are renowned for their high energy conversion efficiency and minimal environmental impact, offering broad application prospects. However, challenges to their stable power generation arise from the rate of hydrogen production through methanol decomposition at the anode and carbon deposition on nickel-based anodes. To address these issues, this study explores the optimal operating temperature and concentration of methanol as an O-SOFCs fuel, while also developing a novel cell design. In this design, an in-situ cracking reactor for internal conversion of methanol is constructed by loading Ru-GDC high-efficiency nanofiber catalysts on dendritic anode microchannels, significantly enhancing the cell's power generation performance. Experimental results demonstrate that at 800 °C and a 30 % methanol concentration, the system increases the maximum power density (MPD) from 0.622 W cm−2 to 0.893 W cm−2, exhibiting a 43.57 % increase in power density and a 13.03 % improvement in methanol utilization. Additionally, the system effectively mitigates carbon deposition and nickel anode deactivation, thereby enhancing the cell's operational stability.

Experimental and modeling study of full- condition combustion characteristics of exhaust gas burners for solid oxide fuel cells

SOFC exhaust gas burner is an essential component of the SOFC thermal management system. The burner in the whole operating conditions of safe and stable combustion and smooth transition in the switching operating conditions is of great significance to the long-term and efficient operation of the SOFC power generation system. This paper builds an experimental test platform for the SOFC exhaust gas burner, tests the combustion performance of the burner in full operating conditions and operating conditions switching process, and establishes a prediction model for the combustion performance of SOFC exhaust gas burner by machine learning algorithm. The results show that the SOFC exhaust gas burner can meet the requirements of safe and stable combustion in all operating conditions and smooth transition between operating conditions; reliable combustion is achieved at the stable power generation condition with excess air factor of 7 ∼ 26, and the average cathode and anode pressure drop in the stable power generation condition is 142 Pa and 185 Pa, respectively; BP neural networks, support vector machines and random forests are used to establish a prediction model for the performance of the SOFC exhaust gas burner, and the random forests achieve the best prediction effect.

Electromagnetic–Thermal Characteristics Analysis of a Tubular Permanent Magnet Linear Generator for Free-Piston Engines

Temperature rise of the tubular permanent magnet linear generator (TPMLG) might lead to insulation failure and demagnetization of permanent magnets, affecting the safe and stable operation of other equipment and the entire system. Herein, a bidirectional electromagnetic–thermal coupling method for analyzing the electromagnetic loss and thermal characteristics of a TPMLG considering the effect of increased temperature on the permanent magnet was proposed. To study the electromagnetic–thermal characteristics of the TPMLG under stable power generation, a two-dimensional electromagnetic field model and a three-dimensional temperature field model were established and coupled. The temperature field of the TPMLG was numerically calculated using computational fluid dynamics over finite volume method under natural air cooling and forced air cooling conditions. Effects of loss and air flow velocity on the steady temperature field were investigated. Results indicated that copper loss increased by 24.5% considering the influence of temperature rise. The windings’ top central position in the TPMLG was the spot with the highest temperature of 127.8 °C and there was a potential demagnetization risk for the permanent magnets. Some reference for future research of clarifying thermal characteristics and cooling design was provided.

Multi-stage coherent beam combination of semiconductor optical amplifiers in ready-made fiber couplers

We report on multi-stage coherent beam combination (CBC) of continuous-wave (CW) outputs from semiconductor optical amplifiers (SOAs) in ready-made fiber couplers. The first CBC stage combines two 120-mW outputs from SOAs seeded by an extended-cavity diode laser (ECDL) at 1458 nm in a 2×2 50%:50% fiber coupler. Two beams generated by two such CBC setups are then combined in the second stage. By concatenating three stages we obtained an output power of 723 mW at 1458 nm from eight SOAs with a total combining efficiency of 75.3%. Stable power generation without interrupts nor degradation over three days was successfully implemented using a simple low-bandwidth servo system. An averaged single-stage combining efficiency of 89.5% deduced from seven CBC setups constituting the three-stage CBC is used to estimate scaling to further stages. As a practical application the output is used to second harmonic generation (SHG) in a nonlinear crystal to achieve an output power of 239 mW at 729 nm.

Design and control of LSTM-ANN controllers for an efficient energy management system in a smart grid based on hybrid renewable energy sources

Many isolated locations, including hilly areas, remote sites, and military camps, lack feasible access to the main power grid. In these conditions, locally established Microgrids can provide the necessary power supply. However, to meet the demands of these isolated areas, numerous individual Microgrids are required. Although some of these Microgrids might be integratable, geographical constraints may preclude full integration. Under these circumstances, the establishment of a smart grid—integrating multiple Microgrids with a battery management system—can potentially solve many power supply issues. A smart grid control system paired with a centralized battery management system is proposed in this paper. The system considers the use of multiple renewable energy sources at various locations for stable and reliable power generation. The proposed method incorporates a long short-term memory (LSTM)-based artificial neural network (ANN) to ensure a stable, high-quality power supply at different load buses. Additionally, this work introduces an artificial intelligence-based operating system designed to maintain energy management under various conditions. To enhance voltage quality, a 7-level aligned multilevel inverter is incorporated into the system. As compared with PI and Fuzzy controllers, the proposed method with LSTM-ANN controller is improved the power quality under sudden changes in the system which are also presented in results, Voltage variation of PI, Fuzzy, and LSTM-ANN is 370V,180V,and 70V . The effectiveness of the proposed energy management system (EMS) is verified by using a hardware-in the-loop approach with OPAL-RT modules, yielding realistic results.

Enhancing Ocean Thermal Energy Conversion Performance: Optimized Thermoelectric Generator-Integrated Heat Exchangers with Longitudinal Vortex Generators

The effective utilization of renewable energy has become critical to technological advancement for the energetic transition from fossil fuels to clean and sustainable sources. Ocean Thermal Energy Conversion (OTEC) technology, which generates electricity by leveraging the temperature differential between surface and deep ocean waters, enables stable power generation around the clock. In this domain, the combination of thermoelectric generators (TEGs) and heat exchangers has exhibited immense potential for ameliorating the deficiencies of conventional OTEC. This study uses finite element numerical simulation of the COMSOL5.5 software to investigate the fluid dynamics characteristics of heat exchangers with flat fins and different types of longitudinal vortex generators (LVGs) under the same number of fins. This research encompasses heat exchangers with rectangular, triangular, and trapezoidal LVGs. Concurrently, the analysis examines how the vortices generated by the LVGs influence the thermoelectric performance of the TEGs. The results demonstrate that heat exchangers integrating flat fins and LVGs can enhance the power generation efficiency of TEGs. However, the pumping power required by the LVGs constrains the thermoelectric conversion efficiency. Compared to rectangular and triangular LVGs, trapezoidal LVGs achieve a superior balance between output and pumping power. Heat exchangers utilizing trapezoidal LVGs can attain the highest TEG thermoelectric conversion efficiency with a specific seawater flow velocity. Overall, these findings provide valuable reference information for applying TEGs and heat exchangers in OTEC design.

Synergizing Wind and Solar Power: An Advanced Control System for Grid Stability

In response to the escalating global energy crisis, the motivation for this research has been derived from the need for sustainable and efficient energy solutions. A gap in existing renewable energy systems, particularly in terms of stability and efficiency under variable environmental conditions, has been recognized, leading to the introduction of a novel hybrid system that combines photovoltaic (PV) and wind energy. The innovation of this study lies in the methodological approach that has been adopted, integrating dynamic modeling with a sophisticated control mechanism. This mechanism, a blend of model predictive control (MPC) and particle swarm optimization (PSO), has been specifically designed to address the fluctuations inherent in PV and wind power sources. The methodology involves a detailed stability analysis using Lyapunov’s theorem, a critical step distinguishing this system from conventional renewable energy solutions. The integration of MPC and PSO, pivotal in enhancing the system’s adaptability and optimizing the maximum power point tracking (MPPT) process, improves control efficiency across key components like the doubly fed induction generator (DFIG), rectifier-sourced converter (RSC), and grid-side converter (GSC). Through rigorous MATLAB simulations, the system’s robust response to changing solar irradiance and wind velocities has been demonstrated. The key findings confirm the system’s ability to maintain stable power generation, underscoring its practicality and efficiency in renewable energy integration. Not only has this study filled a crucial gap in renewable energy control systems, but it has also set a precedent for future research in sustainable energy technologies.

Efficient radiative cooling with bi-rhombic metamaterial and its application in thermoelectric power generation

In this work, we have not only demonstrated a bi-rhombic radiative cooling metamaterial but also explored its application in power generation. It exhibits ultrahigh broadband emission in both the first and second atmospheric windows. The net cooling power reaches up to a value of 165.09 W/m2 in the daytime. Based on the analysis of the electric field distribution, such high emissivity in the atmospheric window derives from the patterned metamaterial and the inclusion of the dielectric layer. Moreover, excellent cooling performance is maintained at different incident angles and heat transfer coefficients. The cold end of the thermoelectric generator is coupled to the radiative cooler, which allows for a maximum temperature difference of 8.28 K during the daytime, resulting in continuous and stable power generation. Therefore, the design of bi-rhombic radiative cooling metamaterial provides a simple, economical, and environmentally friendly method to achieve efficient cooling and continuous power generation, thereby enhancing the efficiency of energy utilization.

Modelling and performance analysis of hybrid electrical power generation system for condensate fractionation plant

Refinery industries are mostly installed at the rural area or distant islands considering the hazardous conditions and transportation facilities. However, more often than not these islands or rural areas have no grid connections to facilitate electrification for these kinds of plants. Even if a grid extension is possible, the availability of power cannot be guaranteed in such rural areas. In any case, disruption in power continuity is not allowed for keeping every subsystem (e.g., heating, reaction subsystem) of the refinery industries under running condition. So, having a standalone, failure free and robust power generation system is a prerequisite criterion before starting up such plants in those areas. Diesel generator is the inevitable choice to meet the demand of electricity in such situation, although the cost of running a diesel generator dependent power system to support these sophisticated plants has been quite a challenge. However, with the available modern technologies, it is possible to think of a stable renewable power generation system that can ensure power availability at any time with the lowest possible operating cost. In this paper, a hybrid power generation system is modelled for a Condensate Fractionation Plant (CFP). Optimization, performance analysis and validation of the proposed model are assessed by using HOMER simulation tool

Characteristics of Ag-doped LaMnO3 perovskite oxide and its application as a solid oxide fuel cell cathode

Ag-doped LaMnO3 perovskite oxides were evaluated as new cathode materials for solid oxide fuel cells. Stable power generation properties were obtained, which indicated that the Ag acceptor was stable and was compatible with the YSZ electrolyte.