Power Generation Technologies Research Articles

Research on optimization of photovoltaic capacity in the multi-energy complementary power generation system

Multi-energy complementary power generation (MEPG) technology is one of the effective utilization means of renewable energy generation. In this paper, a MEPG system is proposed, which includes a photovoltaic (PV) subsystem and ISCC (solar integrated combined cycle) subsystem. To optimize the capacity of the PV subsystem, the dynamic simulation of the MEPG system is carried out under the condition of operating for 2 hours continuously. By stabilizing the output power of the MEPG system at the target value during the operation, the relatively suitable capacity of the PV subsystem is obtained. The results show that for the MEPG system, the PV subsystem should be less than the capacity of the solar field in the ISCC subsystem.

Analysis of China’s power system transformation

China is the largest CO2 emitter, and thermal power units are the main source of CO2 emissions. The low-carbon transformation of thermal power units is the key to carbon emission reduction. China is rich in wind and solar energy resources; wind power and photovoltaic power generation technologies are mature and have good economic prospects. Significantly increasing the proportion of installed wind power and photovoltaic power is the main idea of the power system low-carbon transformation. Biomass fuel blending is the only solution for thermal power units to reduce carbon emissions. Drawing on the large proportion of biomass blending technology in large foreign coal power units, the low-carbon transformation of thermal power units will be completed, and eventually, together with wind power and photovoltaic power generation, China’s renewable energy-based low-carbon power system will be formed. The process of low-carbon transformation of the power system reduces the use of fossil energy, reduces external energy dependence, and improves national energy security. The low-carbon transformation of the power system should be steadily promoted to prevent large adverse impacts on society and the economy.

Intelligent Cleaning Strategy of Photovoltaic Solar Cell Modules

With the decrease of disposable energy and the increase of social demand for power resources, photovoltaic power generation technology has been rapidly developed. The photovoltaic modules exposed outdoors for a long time accumulate serious ash, and the photovoltaic power generation efficiency is affected, so the photovoltaic modules need to be cleaned. Since various factors affecting the power generation efficiency of photovoltaic modules are difficult to quantify and mostly rely on the experience judgment of operation and maintenance personnel, this paper uses the historical operation data of photovoltaic power stations, comprehensively considers various influencing factors, establishes an intelligent cleaning data model, and combines the cleaning cost analysis to provide a basis for intelligent control of photovoltaic module cleaning robots.

Study on the Influence of the Tube Bundle Arrangement on the Performance of Condenser in Nuclear Power Plant

Nuclear power generation technology is obviously a safe and economical way of generating power in modern society. As the low temperature heat source, the condenser of the nuclear power technology condenses the steam into condensate water and then establishes a certain degree of vacuum at the exhaust port of the turbine. The operation of condenser is critical to the nuclear power generation technology. In this paper, the influences of the arrangement of tube bundles on the condenser of nuclear power generation technology were investigated. Three types of condensers, including the church window type, the centripetal type, and the UT type, were analyzed using Ansys Fluent software. The steam flow velocity distribution, air concentration distribution, temperature distribution, and heat transfer coefficient distribution were studied. Under specific design conditions, the flow velocity in the church window type was large, the exhaust air concentration was small, the maximum flow rate distribution was relatively reasonable, and the air concentration distribution was more concentrated. The performances of the centripetal type and the UT type were slightly worse, and the steam condensation was less. In contrast, the condensation of the church window type was large, the relative performance was high, and the heat transfer performance was better.

Improved RUL Predictions of Aero- Engines by Hyper-Parameter Optimization of LSTM Neural Network Models.

Abstract: In the industry domains such as transportation, power generation and heavy engineering industries utilize complex machinery, as their working principles are very complex and it is very difficult to predict their exact life and operational availability due to difficulties involved in their operations. PHM- Prognostics and health management is one such domain which supports in the management of this machinery also known as assets for continuous monitoring for their best utilization and maximum efficiency. For any machine, the current health of the system can be determined by operational and raw sensor data. This data can also be utilized for the prediction of remaining useful life (RUL) of the system provided a reliable prediction model is available. It is always be challenging to determine the remaining useful life of complex machines such as turbofan jet engines from the knowledge of the data available from operating conditions and sensor data. An HPT LSTM- advanced hyper parameter tuned LSTM- Long Short Term Memory neural network model is developed to accurately determine the remaining useful life of the turbojet fan engines. To test this predictive model, a NASA developed database CMAPSS- Commercial Modular Aero Propulsion System Simulation is used. The performance of this HPT LSTM is found to be much improved as compared to reference machine learning algorithms such as simple linear regression and Lagged Multi- Layer Perceptron Models

Photovoltaic Systems through the Lens of Material-Energy-Water Nexus

Solar photovoltaics (PV) has emerged as one of the world’s most promising power-generation technologies, and it is essential to assess its applications from the perspective of a material-energy-water (MEW) nexus. We performed a life cycle assessment of the cradle-to-grave MEW for single-crystalline silicon (s-Si) and CdTe PV technologies by assuming both PV systems are recycled at end of life. We found that the MEW network was dominated by energy flows (>95%), while only minor impacts of materials and water flows were observed. Also, these MEW flows have pyramid-like distributions between the three tiers (i.e., primary, secondary/sub-secondary, and tertiary levels), with greater flows at the primary and lower flows at the tertiary levels. A more detailed analysis of materials’ circularity showed that glass layers are the most impactful component of recycling due to their considerable weight in both technologies. Our analysis also emphasized the positive impacts that increased power-conversion efficiency and the use of recycled feedstock have on the PV industry’s circularity rates. We found that a 25% increase in power-conversion efficiency and the use of fully recycled materials in PV panel feedstocks resulted in 91% and 86% material circularity for CdTe and s-Si PV systems, respectively.

Digitalisation and Modernisation of Hydropower Operating Facilities to Support the Colombian Energy Mix Flexibility

Hydropower plants cover almost 70% of the Colombian electrical demand, were built several decades ago, and present low levels of digitisation compared to other modern power-generation technologies, e.g., wind turbines, solar PV plants, and recently buil hydroelectric plants t. Renovating power plant equipment and investing in modernisation and digitisation can significantly increase the plant flexibility. Those actions will increase a plant’s operational safety and contribute to the solution of environmental and social problems. This work presents the actions followed to extend the lifetime of a 1000 MW hydropower plant operating for more than 40 years. Activities included a residual life status evaluation of generators and component upgrades, among others. The rehabilitation and digitalisation of the generation units allow their integration and remote monitoring so that diagnostic actions can be carried out during a continuous and economically sustainable operation. These activities complement the plan implemented by the company during the last decade to ensure the plant’s operation for another 50 years and its respective integration with nonconventional generation systems at the national level. Besides the generator’s life extension, the main result of rewinding is an increase in the Minimum Breakdown Voltage by almost 140% (from 38.4 kV to 95.6 kV) with respect to the current operation state, ensuring its operation for the following years.

Comparison of turbo compounding technoligies on gasoline and diesel engines

This paper presents a parametric study and comparison of turbocompound gasoline engine with diesel engine based on analysis done in previous papers. Turbocompounding is an important technique to recover waste heat from engine exhaust and reduce CO_2 emission, improving fuel economy. By the time detected one of the biggest problems for IC engines is pollution. Downsizing studies are popular at the industry for the moments to get emission and fuel consumption decreased. Even if the racing industry gets involved in this trend having more efficient and more green racing vehicles is quite important for saving environment. Powertrain works with supercharged internal combustion engine by co-operation of two electric motors MGU-H (Motor-Generator Unit-Heat) and MGU-K (Motor-Generator Unit-Kinetic). It is also seen in passenger, light and heavy commercial vehicles with diesel engines using turbocompounding technology to decrease the pollution. The present paper compares the outcomes which were shown in previous papers and demonstrate the better performance in terms of greenhouse effect and pollution as well as engine power generation performance.

Near-Field Thermophotovoltaic Energy Conversion: Progress and Opportunities

Thermophotovoltaic (TPV) energy conversion is a promising power-generation technology for converting heat to electricity. Recent studies have explored TPV devices featuring nanoscale gaps, which take advantage of near-field effects that enable much larger radiative fluxes and power density. The authors review the physics of near-field thermal radiation, and assess theoretical and experimental advances in predicting and validating near-field enhancements of power output and efficiency in TPV devices. Their discussion of the near-field photonic heat engines presented here will help to guide future engineering solutions in developing practical near-field energy-conversion devices.

Applications of machine learning approaches in aerodynamic aspects of axial flow compressors: A review

A compressor is one of the key components of a gas turbine engine and its performance and characteristics significantly affect the overall performance of the engine. Axial flow compressors are one of the most conventional types of compressors and are widely used in turbine engines for large-scale power generation. Intelligent techniques are useful for numerical simulation, characterization of axial compressors, and predicting their performance. The present work reviews studies applying different intelligent methods for performance forecasting and modeling different aerodynamic aspects of axial compressors. Corresponding to the outcomes of the considered research works, it can be expressed that by using these methods, axial compressors can be characterized properly with acceptable exactness. In addition, these techniques are useful for performance prediction of the compressors. The accuracy and performance of these methods is impacted by several elements, specifically the employed method and applied input variables. Finally, some suggestions are made for future studies in the field.

Generalized predictive control using improved recurrent fuzzy neural network for a boiler-turbine unit

The ultra supercritical (USC) for the boiler-turbine unit has become an advanced power generation technology due to its high combustion efficiency and low-carbon emission. Considering the complex nonlinearity and uncertainty in USC boiler-turbine units, a novel recurrent fuzzy neural network (RFNN) is produced to model dynamic responses of nonlinear systems and improve the control performance of the outputs in the boiler-turbine unit. However, the number of fuzzy rules in previous networks is mostly predefined with experts’ experience, which contributes to the decline in the generalization and efficiency of system modeling. This challenge is tackled in this paper by a subtractive clustering (SC) algorithm, which can determine the optimal number of fuzzy sets in the proposed RFNN. Additionally, aiming at minimizing the tracking errors of the outputs in the boiler-turbine unit, a global generalized predictive control (GPC) strategy is further designed to control the fuel flow, the feedwater flow, and the steam governor valve in the boiler-turbine unit. With the real-time data generated in a 1000MW USC boiler-turbine unit, the proposed SC-RFNN-based GPC can achieve a testing root mean-square-error (RMSE) of 0.0411 as well as the lower integral absolute error (IAE) values of system outputs.

Organic rankine cycle systems with mixture of pure fluids: On infeasible fluid’s fractions due to the interaction between the mixture glide and the hexs pinchs

The Organic Rankine Cycle (ORC) is a promising technology for power generation from low-grade heat. The selection of working fluids is one of the important key points to improve the performance of an ORC system. Zeotropic mixtures show promising performances as working fluids. In fact, their temperature glide during phase change enables better match between the working fluid and the heat source/sink temperatures. In order to reveal the performance of mixture in ORC system, this paper deals with the thermodynamic model of the subcritical Organic Rankine Cycle (ORC) systems driven by low grade heat source while using zeotropic mixture working fluids with a special consideration to the interaction between phase change glides and the pinch value and their location in both the evaporator and the condenser (HEXs). Zeotropic mixtures of seven pure fluids are evaluated as working fluids for a subcritical ORC system. The mass fraction effects of mixtures on the thermal efficiency are analyzed. For given working conditions (working fluid mass flow, pressure and bubble temperature) the results show that for each considered zeotropic mixture there exist mass fraction ranges that are not consistent with the pinch values constraint in the HEXs and leads to so-called ‘infeasible zones’ with unreal HEXs dimensions. Results shows also that, out of these “infeasible fractions” zone, keeping unchanged the working conditions, the thermal performances of ORC system using zeotropic mixture are always better than the thermal performances of the same systems using the correspondent pure fluids. In addition, out of these highlighted “unfeasible zones” it was found that mixture with high temperature glide improve the thermal efficiency of ORC system.

Hydrogen supply chain: Current status and prospects

AbstractIn the current world energy scenario with rising prices and climate emergencies, the renewable energy sources are essential for reducing pollution levels triggered by carbon‐based fuels. Hydrogen rises in the world energy scenario as an important non‐carbon‐based energy able to replace fossil fuels. For this reason, the rapid development of hydrogen‐related technology has been seen in recent years. This review paper covers hydrogen energy systems from fossil fuel‐based hydrogen production, biomass and power from renewable energy sources, to hydrogen storage in compressed gases, liquefied and solid materials, and hydrogen‐based power generation technology. It represents a quiet complete set of references that may be effective in increasing the prospects of hydrogen as a fuel in the coming years. The main conclusions drawn are that natural gas and coal supply nearly all of the current hydrogen. The commercially available technologies for hydrogen production are steam methane reforming, partial oxidation, and alkaline electrolysis. The most economical methods for hydrogen production are partial oxidation, steam methane reforming, coal gasification, and biomass gasification. Metallic cylindrical reservoirs are the most promising alternative to underground storage of compressed hydrogen at large scales. Some metal compounds and composites can store a significant amount of hydrogen while maintaining reasonable adsorption and desorption kinetics. The transportation sector is likely to see widespread use of hydrogen in the future, helping to reduce pollution. Vehicles can be powered by fuel cells, which are much more efficient than internal combustion engines. There are still several obstacles in the way of widespread hydrogen utilization. The first one is that the cost of producing hydrogen from low‐carbon sources is elevated. As the cost of renewable energy declines and hydrogen production is scaled up, it is anticipated that the hydrogen production costs would decrease over the next years. Innovative technologies are expected to increase the interest on thermochemical hydrogen production to massively substitute electrochemical technologies since they are theoretically cost‐effective. More research is needed to fix concerns with some of the thermochemical cycles in order to rise its maturity. Increasing the chemical reaction conversion ratios, which can be resolved utilizing nonequilibrium reactions, is one of them. The transportation sector is likely to see extensive use of hydrogen in the future, helping to reduce carbon dioxide emissions. The power required by vehicles may be supplied by fuel cells, which are more efficient than internal combustion engines.

A Deep Learning-Based Surface Defects Detection and Color Classification Method for Solar Cells

In recent years, solar photovoltaic-based power generation technology has become the key planning direction of many countries around the world. In the process of making solar cells, the quality inspection requirements are very particular, such as physical damages, surface scratches, broken grids and microcracks. In traditional factory production, the detection of the above defects requires professional inspectors to carry out visual inspection, which often leads to low detection efficiency, subjective assumption and fatigue, as well as some detection errors. In recent years, the rapid development of computer vision makes it possible to be used to detect the defects in solar cells. To overcome existing barriers, this paper proposes a method for detecting surface defects in solar cells based on deep neural network. Specifically, a specified image segmentation model named U-Net is developed for this purpose. By automatically segmenting little objects using the proposed recognition approach, surface defects detection can be realized. At last, we use a set of experiments on images from real scenes to verify the proposed method.

The Economic and Environmental Evaluations of Combined Heat and Power Systems in Buildings with Different Contexts: A Systematic Review

Cogeneration systems—also known as combined heat and power systems—form a promising technology for the simultaneous generation of power and thermal energy while consuming a single source of fuel at a site. A number of prior studies have examined the cogeneration systems used in residential, commercial, and industrial buildings. However, a systematic review of the economic and environmental evaluations of the system is not found in the literature. The present study aims to address this research gap by reviewing the most relevant studies on the cogeneration systems applied to buildings in different contexts (e.g., residential, commercial, and industrial) and provides systematic evaluation approaches from economic and environmental perspectives. Results show that the cogeneration system can significantly reduce energy consumption, operating costs, carbon dioxide equivalent emissions, and positive performance on other relevant parameters. The present study provides extensive evidence to show that the cogeneration system is simultaneously economically profitable and environmentally friendly in various application contexts. To achieve the maximum benefits from cogeneration systems, several practical suggestions are provided for their successful installation and implementation in real-life situations.

A power generation device based on shape memory alloy and piezoelectric ceramic

A power generation technology that combines shape memory alloy (SMA) and piezoelectric ceramic is proposed. The piezoelectric ceramic is pulled by the deformed SMA to produce a positive piezoelectric effect, which eventually generates electrical energy. The research was conducted through structural design, collection and storage of electrical energy, and experimental verification. The experimental results show that the power generation device has an open circuit voltage of 11.6 V when heated by hot air at 100 °C. The device was used to charge a 1000μF/6.3 V capacitor through the energy harvesting circuit, and the final capacitor voltage was stabilized at about 6 V.

High-temperature silicon carbide material with wicking and evaporative cooling functionalities fabricated by femtosecond laser surface nano/microstructuring

A multifunctional silicon carbide (6H–SiC) material with efficient wicking and evaporative cooling performances in a temperature range of 23–180 °C is created through hierarchical surface nano/microstructuring by a femtosecond laser. The elaborated hierarchical surface structure is an array of nanotextured microgrooves that includes structural features in a range between about 15 nm and 140 μm, integrating benefits from micro- and nanoscale physics of capillarity and thermodynamics. The spatiotemporal dynamics of both water spreading and temperature field obtained by optical and infrared imaging show the excellent wicking and evaporative cooling functionalities of the created material. The range of applications of the developed multifunctional 6H–SiC material includes the technologies for enhancing power generation efficiency, waste heat recovery, and cooling high-heat-flux Si- and SiC-based electronic devices. The application of the created material in cooling technologies for power generation can result in substantial fuel savings and global reduction in greenhouse gas emissions.

Study of the interaction between a Mn ore and alkali chlorides in chemical looping combustion

Chemical looping combustion (CLC) is a novel technology for heat and power generation with inherent CO2 capture. Using biomass in CLC (bio-CLC), negative CO2 emissions can be attained. Biomass usually contains high content of alkalis (mainly K and Na) which can be problematic in the process, such as potential alkali-bed interaction, and this is the focus of current work. This work uses charcoal with and without the impregnation with alkali chlorides, KCl and NaCl. The results are compared to previous data from samples impregnated with K2CO3 and Na2CO3. A low-alkali braunite manganese ore is used as bed material to study the oxygen carrier interaction with the alkalis in cyclic experiments at 950 °C in a quartz batch fluidized-bed reactor. As compared to charcoal without alkali impregnation, the impregnation with KCl, NaCl, K2CO3, and Na2CO3 can improve the rate of gasification by a factor of 4, 3, 10, 8, respectively. Partial-defluidization of the braunite particles was found with all the alkali-fuels, although the extent differed, e.g., K2CO3 and KCl resulted in earlier onset of defluidization than Na2CO3 and NaCl. Further, indications of partial defluidization were earlier and more permanent with the carbonates than the chlorides. Partial agglomeration with soft agglomerates of the bed was observed, while hard agglomerations were never seen. Accumulation of K, Na, Si, and Ca was found in the agglomerates after cycles with K2CO3-charcoal and Na2CO3-charcoal, while little K and Na was detected in the bridges between particles after the KCl and NaCl cycles. A significant fraction of the alkali added was found in the oxygen carrier, with 80% or more being retained for the Na salts, and around 40% for the K salts. There was no clear difference between chlorides and carbonates with respect to retention. The fresh and used braunite have very similar reactivity with CH4 and H2, whereas some decrease in reactivity is noticed with CO.

Optimal Planning of Hybrid Electricity–Hydrogen Energy Storage System Considering Demand Response

In recent years, the stability of the distribution network has declined due to the large proportion of the uses of distributed generation (DG) with the continuous development of renewable energy power generation technology. Meanwhile, the traditional distribution network operation mode cannot keep the balance of the source and load. The operation mode of the active distribution network (ADN) can effectively reduce the decline in operation stability caused by the high proportion of DG. Therefore, this work proposes a bi-layer model for the planning of the electricity–hydrogen hybrid energy storage system (ESS) considering demand response (DR) for ADN. The upper layer takes the minimum load fluctuation, maximum user purchase cost satisfaction, and user comfort as the goals. Based on the electricity price elasticity matrix model, the optimal electricity price formulation strategy is obtained for the lower ESS planning. In the lower layer, the optimal ESS planning scheme is obtained with the minimum life cycle cost (LCC) of ESS, the voltage fluctuation of ADN, and the load fluctuation as the objectives. Finally, the MOPSO algorithm is used to test the model, and the correctness of the proposed method is verified by the extended IEEE-33 node test system. The simulation results show that the fluctuation in the voltage and load is reduced by 62.13% and 37.06%, respectively.

Theoretical investigation of a novel electrochemical electricity generator driven by diurnal temperature variation

Diurnal temperature variation is ubiquitous and abundant, which is an untapped energy source generated by intermittent solar radiation. Tapping into this vast energy with energy-efficient and cost-effective technologies may provide a promising approach for transitioning to an energy-sustainable economy and society. In this study, a novel temperature-induced electrochemical power generator is proposed and investigated to harvest the thermal energy brought by the diurnal temperature variation. The novelty of such a power generator lies in its separate electrochemical and heat exchange processes. The mathematical models are established and functionalized to simulate the performance of the proposed generator in practical application. To investigate and prove the feasibility and effectiveness of the proposed generator, several essential environmental parameters and working condition factors are studied. The results show that the proposed generator is workable for generating electricity empowered by the diurnal temperature variation, which could generate 3.27 kWh of electricity at a standard working condition in one diurnal period. Whereas ambient temperature is marginal to its net energy output, other parameters, i.e., solar radiation, wind velocity, and cells’ area, have significant effects on the performance. The net energy outputs of the proposed generator grow significantly from 0.69 kWh to 7.10 kWh with the solar radiation increasing from 200 W/m2 to 1200 W/m2, which is acceptable to provide electricity for the domestic daily demand, otherwise can be scalable to meet the needs. Furthermore, annual average energy conversion efficiencies of the generator are more than 2% in different typical weather conditions. This paper may enrich the renewable and sustainable power generation technology, as well as guide the design, optimization and application of the novel temperature-induced electrochemical power generator driven by the diurnal temperature variation to expedite the net zero.