Utility Power Generation Research Articles

Full-engine simulation of micro gas turbine based on time-marching throughflow method

Gas turbines are widely used in power generation, aviation, and clean energy utilization. The accuracy of the overall performance prediction is of great importance when designing gas turbines. The purpose of this study is to develop a full-engine throughflow simulation method based on a time-marching scheme to obtain a more accurate prediction of gas turbine performance. To precisely calculate the flow deflection inside the blades, a robust inviscid blade force model was established using a theoretical derivation. The results indicate that in transonic flow, the blade force model can deteriorate the conservation of the throughflow governing equations during the time-marching process. To overcome this issue, a quasi-orthogonal body-fitted coordinate system was adopted based on theoretical analysis. Subsequently, a viscous force model coupled with a variety of empirical models was introduced to simulate the viscous effects. A simple but effective way of distributing the fuel source terms in the combustion area was employed to simulate the burning process. Finally, the developed throughflow method was applied to conduct flow simulations of the KJ66 micro gas turbine engine. The predicted overall performance matched well with the experimental data, with a maximum error of less than 6.48% among the comparisons of thrust, specific fuel consumption, and exhaust gas temperature; furthermore, the proposed method was more accurate than the traditional thermal cycle calculation. The novelty of the present study lies in the time-marching solution of the full-engine throughflow simulation and its ability to eliminate the dependence on the generic component map and obtain meridional distributions of the flow parameters. The results can offer valuable guidelines for the integrated design and optimization of components in Brayton cycles. • A strictly conservative throughflow model is developed for gas turbine simulation. • The full-engine throughflow simulation of micro gas turbine is achieved. • Throughflow model can eliminate the dependence on generic map of components. • Throughflow model can improve off-design performance prediction for gas turbine. • Throughflow model can obtain meridional details of flow parameters in gas turbine.

Bioinspired Micro/Nanostructured Polyethylene/Poly(Ethylene Oxide)/Graphene Films with Robust Superhydrophobicity and Excellent Antireflectivity for Solar-Thermal Power Generation, Thermal Management, and Afterheat Utilization.

The rational utilization and circulation of multiple energy sources is an effective way to address the crises of energy shortages and environmental pollution. Herein, microextrusion compression molding, an industrialized polymer molding technology that combines melt blending and compression molding, is proposed for the mass production of a bioinspired micro/nanostructured polyethylene/poly(ethylene oxide)/graphene (MN-PPG) film. The MN-PPG film exhibits robust shape stability, high storage energy density, and excellent thermal management capability owing to the cocontinuous network formed by poly(ethylene oxide) and the polyethylene matrix. The MN-PPG film has sufficient photothermal property due to the uniformly dispersed graphene nanosheets and the bioinspired surface micro/nanostructures. Interestingly, the MN-PPG film surface exhibits durable superhydrophobicity, acid/alkali resistance, and active deicing performance. Further, a multifunctional energy harvesting and circulation system was established by integrating the MN-PPG film, an LED chip, and a thermoelectric module. The hybrid system produced an open-circuit voltage of 315.4 mV and power output of 2.5 W m-2 under 3 sun irradiation. Furthermore, the afterheat generated by the LED chips at night can be converted into electricity through thermoelectric conversion. The proposed method enables the large-scale fabrication of multifunctional phase change composites for energy harvesting in harsh environments.

Construction and application of decision support indicator system for new energy development in Hexi Corridor

Due to the lack of a scientific and objective index system for the development and utilization of new energy in China’s Hexi Corridor, there have been different opinions and views on the selection of new energy fields that need to be developed as a priority and the ranking of development, which is not conducive to scientific decision-making on new energy development. In response to this problem, this paper takes the current situation of new energy industry research in China’s Hexi Corridor as a starting point, uses economic returns, social recognition, environmental protection and unit investment ratio as evaluation indicators, takes solar thermal utilization, photovoltaic power generation, wind power generation and biomass power generation as development objects, establishes a new energy evaluation index system for the Hexi Corridor, and derives principles for the development of new energy in the Hexi Corridor through expert evaluation and analytic hierarchy process. This index system was also applied in the new energy development planning and decision-making study in Jiuquan City. The study showed that Jiuquan City should focus on developing wind power generation, followed by photovoltaic power generation and solar thermal utilization, and finally selectively develop biomass power generation. The results of the study are consistent with the actual situation in Jiuquan City, and can provide theoretical support for the development of the new energy industry in Jiuquan City.

Electricity Consumption Forecasting System Using Deep Learning

Energy modeling in Smart Buildings (SB) and planning and operating the generation of power based on the information extracted are key components of the Smart Grid’s (SG’s) energy management system. In the world, buildings use a significant amount of energy that contributes to energy efficiency programs. Additionally, excessive utilization power generation appliance also including air conditioners and heater, breathing, and climate control (HVAC) units, improper microclimate control, and inappropriate start-up and ordering of power equipment waste a lot of heat pumps. The utility can mitigate energy generation costs when it anticipates electrical loads and schedules generation resources in accordance with the demand. To estimate electricity usage at varying tiers of utility grid systems, a range of techniques have already been used. The goal of this study will be to create a hybrid deep learning model can predict resource utilization in infrastructures. Model building and data cleaning are the two stages of the proposed framework. Data cleaning involves pre-processing techniques and adding additional lag values to raw data. This hybrid deep learning (DL) approach is made up of a series of completely connected layered and linear Long Short-Term Memory (LSTM) sections layered over bi-directional Long Short-Term Memory (LSTM) components and is based also on collected information. You could incorporate the dependence structure of electricity usage on regressors and increase computation efficiency, training time, as well as computational complexity by using the results obtained.

Soil Pollution Assessment of a Gas Flare Site in the Niger Delta Region

Aim: The aim of this research was to investigate the level of pollutants deposition on soil generated from a gas flaring site.
 Study Design: The Soil Samples for this study were picked from two sets of locations (a proposed gas flare site situated at Ogbogu Gas plant and two control sites sfrom a primary source of local farm lands). A total number of eighteen samples were collected from the five different sampling spots as designated using the global positioning system (GPs).
 A contaminated Site and three farm lands within Ogbogu and Ebocha community were mapped at 20m, 50m, 100m, 500m & 700m from the gas flare site and mapped with GPs location at two different sampling depths (0-15 & 15-30) cm.
 A Control Site and two (2) farm lands within Idu Ekpeye community were mapped outside the area of concentration from the gas flare sites. These locations were chosen to determine by comparative assessment, the impact of gas flaring on the soil properties of the contaminated sites.
 Place and Duration of Study: This study was carried out in Ogba/Egbema/Ndoni Local Government Area of Rivers State. This area was chosen for this study because of the high volume of petroleum activities. Oil and gas processing, production, transportation and utilization for power generation occur daily in the area resulting in numerous cases of environmental degradation and pollution.
 Methodology: This research explores and presents a method of analysing the environmental impact of gas flaring in the Niger Delta so as to provide the data required for the complete analysis and evaluation of the various observed and noted health and environmental effects of gas flaring in Niger Delta. Different samples at various proximities at 200m, 500m, 1000m, 5000m and 7000m from the flare site using a hand aguar equipment sampled at depths of (0-15)cm and (15–30)cm were taken and measurements and experimentations were meticulously carried out.
 Results: The results obtained in this research show a marked trend as all the parameters considered indicated a gradient away from the flare points in all the flow stations such as soil pH changing from acidic (4.0-4.2) to near neutral (6.4-6.6) away from the flare points and the average low soil moisture content of (17% - 23%) as against 40% for the (10m and 20m) and control distance. The quantity of carbon emitted by these flares are about 2,525,000.00 tonnes of carbon per day. These values portray a bad omen for the affected communities.
 Conclusion: Contamination of agricultural soils by trace metals creates a serious risk of the introduction of these xenobiotics into human food chain. The soil fertility is being reduced as this study has revealed an increase in temperature along-side an increase in gas flaring and flare distances.
 This study recommends that gas flaring should be seen as a violent action against the people and that the flared gas should be channelled to meeting the ever increasing demand for energy in the industrial sector of the economy.

Life-cycle assessment of hydrogen utilization in power generation: A systematic review of technological and methodological choices

Interest in reducing the greenhouse gas emissions from conventional power generation has increased the focus on the potential use of hydrogen to produce electricity. Numerous life-cycle assessment (LCA) studies of hydrogen-based power generation have been published. This study reviews the technological and methodological choices made in hydrogen-based power generation LCAs. A systematic review was chosen as the research method to achieve a comprehensive and minimally biased overview of hydrogen-based power generation LCAs. Relevant articles published between 2004 and 2021 were identified by searching the Scopus and Web of Science databases. Electrolysis from renewable energy resources was the most widely considered type of hydrogen production in the LCAs analyzed. Fuel cell technology was the most common conversion equipment used in hydrogen-based electricity LCAs. A significant number of scenarios examine the use of hydrogen for energy storage and co-generation purposes. Based on qualitative analysis, the methodological choices of LCAs vary between studies in terms of the functional units, allocations, system boundaries, and life-cycle impact assessment methods chosen. These discrepancies were likely to influence the value of the environmental impact results. The findings of the reviewed LCAs could provide an environmental profile of hydrogen-based electricity systems, identify hotspots, drive future research, define performance goals, and establish a baseline for their large-scale deployment.

Parametric optimization of a novel solar concentrating photovoltaic-near field thermophotovoltaic hybrid system based on cascade utilization of full-spectrum solar energy

Based on cascade utilization of full-spectrum solar energy, a novel solar concentrating photovoltaic and near-field thermophotovoltaic hybrid system (CPV-NFTPVS) is proposed to achieve efficient solar power generation. The full-spectrum solar energy is split into two parts by spectrum splitter: The high-frequency part is provided to concentrating photovoltaic module while the rest to near-field thermophotovoltaic module. The effect of operating parameters such as concentration ratio, split wavelength, applied voltage, and vacuum gap on the energy conversion performance of the hybrid system is investigated. Starting with a concentration ratio of only 210, the efficiency of the hybrid system exceeds the maximum efficiency of near-field solar thermophotovoltaic system (NF-STPVS) with a concentration ratio of 2000. Considering the technical difficulties of the ultrahigh concentration ratio and ultrahigh cooling rate, a concentration ratio of 1000 is a practical choice for the hybrid system and its efficiency reaches 56.20%, which is about 1.12 times higher than the maximum efficiency of NF-STPVS. The law of the optimal value of the operating parameters is further explored and it's found that the optimal gap distance is always 10 nm and the optimal split wavelength needs to be adjusted according to the concentration ratio. The significant value of CPV-NFTPVS based on cascade utilization in solar power generation is indicated and practical application of the near-field thermophotovoltaic is guided.

Numerical simulation and sensitivity analysis of automatic optimization of gas extraction well locations in abandoned mines

There are large numbers of abandoned mines in China and abroad, among of which stores relative abundant coal-bed gas. The gas extraction from abandoned mines can be used for power generation or industrial gas utilization. In this paper, the present situation of abandoned mines in China and abroad was studied, and the disadvantages of the common layout and optimization methods of gas extraction in abandoned mines were pointed out. Based on the analysing of reservoir conditions and physical property parameters, the finite element software COMSOL was used to do the numerical simulation of extraction well automatically optimize, and take shenbei coal mine as an example. Moreover, an automatic optimization APP of well location was developed based on the results of simulation. Finally, the parameter sensitivity of gas extraction is analysed. Through the study, it is found that the most basic and common method of gas extraction in abandoned mines is empirical method, which lacks of theoretic support and accuracy, thus causing unreasonable extraction and waste of resources. In this study, the COMSOL numerical simulation software was used to explore the numerical simulation method of automatic well position optimization combined with the optimization algorithm. The Nelder-Mead algorithm was selected as the optimization algorithm after comparing the advantages and disadvantages of various algorithms. The operation flow and type of Nelder-Mead algorithm were analysed, and the optimization parameters of numerical simulation were set. Through the numerical simulation, the function of automatically searching the high-gas production position near the preset well position was realized, and the automatic optimization APP for gas extraction in abandoned mines was developed. Finally, the sensitivity of parameters to gas production in different well locations under three different pumping conditions which are horizontal, vertical and bottom-hole negative pressure was analysed; and the simulation results were discussed.

Integrated Heat Regenerator (IHR) Designs with Hydrogen Preheater and Thermoelectric Generator for Power Enhancement of a 2 kW Fuel Cell Vehicle

The power train efficiency of fuel cell vehicles (FCV) can be enhanced by improving the hydrogen energy utilization. Based on a mini FCV running on a 2 kW open-cathode Polymer Electrolyte Membrane (PEM) fuel cell, a waste heat recovery system design needs to be developed as an approach towards higher energy efficiency. The novelty of the system is on the integration of thermoelectric generator technology with hydrogen preheating process for a combined heat and power output. This manuscript presents the proposed integrated heat regenerator (IHR) designs, analysed using numerical computational modelling. Three IHR designs were proposed where the main design criteria are (i) a minimum of 10oC hydrogen preheating degree, and (ii) non-parasitic active cooling for the Thermoelectric generator (TEG) cells. Three design concepts were studied to identify its design and performance limitations. The numerical results were validated with theoretical modelling analysis for hydrogen exit temperatures and TEG surface temperatures. The analysis on predicted fuel cell power enhancement, TEG power generation and waste heat utilization were performed by relating the temperature profiles of the hydrogen reactant and TEG surfaces to fuel cell reaction models and TEG power relationships. A compact IHR design that produced 7.7 to 8 % total power enhancement and suitable in size for a mini FCV was identified for future development works

Life‐cycle greenhouse gas emissions in power generation using palm kernel shell

AbstractPalm kernel shell (PKS) utilization for power generation has greatly increased in Japan since the introduction of the feed‐in tariff (FIT) in 2012. However, the FIT fails to consider the entire palm industry while evaluating the environmental impacts of using PKS. Therefore, this study aimed to elucidate the life‐cycle greenhouse gas (GHG) emissions of power generation using PKS. We targeted two PKS‐firing power plants as these are the first two instances of the use of PKS in power plants in Japan. A system boundary was established to cover palm plantation management in Indonesia and Malaysia, as both power plants import PKS from these countries. The GHG emissions were derived from land‐use change, palm plantation, oil extraction, PKS transportation, and power plants. Six scenarios were examined for the emissions based on the type of land‐use change and the existence of biogas capture in oil extraction. CO2 emissions from PKS combustion were also calculated by assuming that carbon neutrality was lost because of cultivation abandonment. The GHG emissions in one scenario, where the plantations were replanted and continuously managed and no biogas capture implemented in oil extraction, exhibited an average of 0.134 kg‐CO2eq/kWh reduction in a plant in Kyushu District, and 0.043 kg‐CO2eq/kWh reduction in a plant in Shikoku District for liquid natural gas‐fired steam power generation, respectively. More than 65% of life‐cycle GHG emissions originate from biogas generated during oil extraction; thus, biogas capture is an effective strategy to reduce current emissions. In contrast, in the case of accompanying land‐use change or collapse of carbon neutrality, the emissions considerably exceeded those of fossil fuels. These findings indicated that the FIT fails to consider the risk of increased emissions or further substantial emission reductions. Therefore, the feasibility of FIT application to PKS needs to be re‐established by evaluating the entire PKS life cycle.

Characterization of some Nigerian coal for effective power generation and industrial utility

Large numbers of trace elements occur in coals used for coal power plants combustion. In order to assess the environmental impact of the coal fuel cycle, coal and coal ash samples need to be analyzed for a number of toxic and radioactive elements. Six coal samples from Ridi-Awe and Lafia (Nasarawa State), Garin Maiganga (Gombe state) Nigeria coal deposit were collected. The samples were subjected to gross calorific value determination, X-ray diffraction spectrometry, X-ray fluorescence spectroscopy to determine it suitability for power generation and industrial utility. Base on the laboratory analysis and results, it is observed that the gross calorific values of Awe are 29.18MJ/kg, 30.79MJ/kg. Lafia are 26.10MJ/kg, 25.10MJ/kg and Maiganga are 25.50MJ/kg, 24.21MJ/kg respectively. The XRF results indicates the presence of transition metals and some trace element but void of elements such as Arsenic, tin and tungsten which makes it environmental and health hazard friendly. The proximate analysis revealed that the % ash content of Awe, Lafia, and Maiganga is 87, 62, 79. % moisture content of Awe, Lafia, and Maiganga is 8.7, 16.3, 8.3 and % volatile matter content of Awe, Lafia, and Maiganga coals is 4.3, 21.7 and 12.7 whereas % fixed carbon of Awe, Lafia, and Maiganga 78.3,55.8 and 71.1 respectively. However, in terms of coal rank, the Awe is bituminous high volatile C, whereas Lafia and Maiganga coal are Subbituminous A, hence the reactivity and maturity of the coal decrease in the order of Awe (A) ˂ Lafia (L) ˂ Maiganga (M). The result shows that the coal samples are void of nitrogen and dangerous radioactive elements.

Influence of electrode spacing and fed-batch operation on the maximum performance trend of a soil microbial fuel cell

The effect of electrode spacing on a soil microbial fuel cell (MFC) performance under fed-batch treatment with synthetic urine medium (SUM) was investigated at 2, 5, and 8 cm electrode spacing. The electrodes consisted of stainless-steel mesh with coarse layers of carbon-black. The MFCs were fed with SUM when the natural substrate of the medium was exhausted. Initial feeding resulted in 79.6, 108.7, and 103.1% increase in OCV with a proportional percentage increase in power at 2, 5, and 8 cm electrode spacing. Six days after the first feeding, the power was 189.9, 150.7, and 108. 5 mW/m 2 in ascending order of electrode spacing. With more extended treatment, the overall maximum power was obtained at 8 cm spacing. In ascending order of electrode spacing, the highest power (207.92, 263.38, and 271.1 mW/m 2 ) was obtained on days 39, 42, and 93, respectively. The study shows that a larger anode-to-cathode distance requires a longer time for the soil MFC to achieve stable and maximum performance in fed-batch operation. • Soil MFC is optimized for efficient substrate utilization and long-term sustainable power generation. • The effect of long-term fed-batch operation on the MFC performance with varying electrode spacing is investigated. • Soil MFC performance stability is time dependent on electrode spacing under fed-batch operation. • Smaller electrode spacing results in initially better performance due to lower internal resistance. • Larger electrode spacing takes a longer time for the MFC to reach stable and maximum performance.

Efficiency, Economic, Energy, and Safety (3ES) Analyses on Different Configurations of MDEA Absorption Process for Coke Oven Gas Desulfurization

The purification of Coke Oven Gas received great attention due to its high potential of utilization for power generation and hydrogen production. This study simulated different configuration of MDEA process flowsheet and implemented the comprehensive evaluation. The comprehensive evaluation included H2S removal efficiency, energy consumption, techno-economic analysis, and safety assessment. The modified MDEA processes applied additional flash drums to enhance H2S removal efficiency and reduce heat duty of distillation column reboiler. MDEA with two intermediate flash drums showed the highest efficiency (96.5%), lowest reboiler duty (6.27 MW), and the lowest operation cost ($ 50/ Nm3-y). Conventional MDEA process exhibited the lowest capital cost ($ 1.531 million) and H2S leakage amount (30.3 kg) for an accident. MDEA with two flash drums process can be recommended when high purity coke oven gas was required. Conventional MDEA was recommended to consider safety and short-term operation with the lowest capital cost. MDEA with one flash drum can be recommended for stable desulfurization operation.

Aluminum doping of mesoporous silica as a promising strategy for increasing the energy storage of shape stabilized phase change materials containing molten NaNO3: KNO3 eutectic mixture

Efficient thermal energy storage at high temperature is necessary for both industrial waste heat utilization and continuous solar power generation. Shape-stabilized phase change materials containing mesoporous aluminosilicates and eutectic NaNO3: KNO3 (1:1 mol) molten salt mixture were obtained at 90% wt. salt. The influence of aluminum doping was studied for the first time. All samples show thermal stability up to 550 °C and two distinct phase transitions corresponding to the melting/freezing of nanoconfined and interparticle salt phases. The radius and spherical shape of the nanoconfined phase were determined from the melting and freezing point depressions with respect to bulk. The enthalpy decrease was quantified in terms of surface tension and the contributions of a non-melting fraction of surface adsorbed ions. SBA-15 type aluminosilicates matrices yield composites with high latent heat storage of 76–77 Jg−1, of which 8 Jg−1 for the nanoconfined phase and good thermal reliability. Aluminum doping is a simple and promising strategy for obtaining high temperature, efficient thermal energy storage materials due to a lack of non-melting salt fraction. The resulting shape-stabilized PCMs have a higher operating temperature range and latent heat storage, offering a 36% increase in total heat capacity over the pristine salt.

Parametric Investigations on Solid oxide fuel cell and gas turbine combined system

This paper presents a thermodynamic investigation on the SOFC-GT combined system for maximizing power generation and optimal energy utilization. The system modeling and analysis are based on the first law of thermodynamics. Performance of the solid oxide fuel cell-based system is analyzed for parametric variation of compression ratio, turbine inlet temperature, fuel utilization factor, and ambient temperature. Direct energy conversion system has an advantage over the indirect system as they reduce the adverse impact on the environment, so solid oxide fuel cell-based systems are environmentally friendly. The maximum.output.of.the considered cycle.is 120.08 kW/Kg of air. The combined efficiency of the system is 51.02% at 1400 K.turbine.inlet temperature. and.13 compression ratio at fixed fuel utilization factor of 80%.

Current Situation and Prospect of Hydrogen Energy Industry Chain and Hydrogen Power Generation Utilization Technology

Current Situation and Prospect of Hydrogen Energy Industry Chain and Hydrogen Power Generation Utilization Technology

Actual Measurement and Evaluation of the Balance between Electricity Supply and Demand in Waste-Treatment Facilities and Development of Adjustment Methods

In Japan, breakthroughs to improve the share of renewable energy in the energy mix have become an urgent issue. However, the problem could not be solved by simply adding more power plants for various technical reasons, such as the unsuitability of using renewable energy as baseloads due to its intermittency. Furthermore, establishing the required cooperative systems for regionally distributed power adjustment is also tricky. Based on these backgrounds, this paper constructs an operation plan that minimizes CO2 emissions by correcting the generation and load patterns of the renewable energy of solar power, utilizing power generation from waste as a substitute for baseload power, and estimating the power demand of each facility. The result shows that by adjusting the operation plans, the model can reduce CO2 emission by 20.95 and 8.30% in weeks with high and low solar power generation surpluses, respectively. Furthermore, these results show that it is possible to reduce CO2 emissions in regions that have power sources with low CO2 emission coefficients by forecasting the amount of power generation and power load in the region and appropriately planning the operation in advance.

Dynamics Water Quality in Koto Panjang Reservoir, Indonesia

Riau Province has the Koto Panjang reservoir which is generated from the damming of the Kampar River flow for hydroelectric power generation and other utilization activities. The increase in community activities in reservoir waters and on land causes water quality dynamics that can affect fish farming activities. The purpose of this study was to determine the dynamics of reservoir water quality. The survey was conducted in March – August 2021 at seven sampling points, where water samples at each sampling point were taken at a depth of 1 m as much as 1 liter using a van dorn water sampler and preserved and analyzed according to standard methods. Data from measurement and analysis were tabulated and analyzed descriptively including temperature, pH, turbidity, TSS, TDS, DO, nitrate, ammonia, total nitrogen, BOD5, COD, and total phosphate. The results obtained indicate that the values of temperature, turbidity, TDS, TSS, pH, DO, ammonia, nitrate, and phosphate are still below the quality standard, except in the range of BOD values of 4.30 – 5.75 mg/L and COD of 17.90. – 23.73 mg/L is an indication of organic matter originating from other activities on the reservoir land, such as plantations, agriculture, settlements, tourism, apart from floating net cage cultivation activities.

Greenhouse gas mitigation potential from waste heat recovery for power generation in cement industry: The case of Thailand

The cement industry has the highest proportion of energy consumption and greenhouse gas (GHG) emitted in the Thai demand-side industry sector. Therefore, the potential GHG emission from energy efficiency is necessary to achieve the NDC target. Due to vast thermal energy consumption for cement production, especially clinker production, waste heat recovery utilization for power generation which partially replaced the on-grid electricity for cement production, has been estimated the GHG emission performance tracking in this study. We found that there are 12 waste heat power plants with a total 263.5 MW installed capacity in the Thai cement industry. With a potential of 1,663,674.21 MWh electricity production annually and GHG mitigation potential of 793,572.60 tons CO2eq per year in 2019. This GHG mitigation figure accounts for 7.21% of GHG mitigation targets for the NDC roadmap.

Channel Detection Under Impulsive Noise and Fading Environments for Smart Grid

The advanced 6G Technology benefits the Internet of Things (IoT) in various applications. As one essential application scenario, smart grid (SG) incorporates communication and management techniques and promises an efficient and intelligent power system, whereby cognitive radio (CR) is believed to be an essential tool for better resource utilization in power generation and delivering processes. In the CR-assisted IoT in SG scenarios, channel detection (CD) will play an essential role to accurately sense the available channel resource. However, for SG scenarios, high-accuracy CD may become a challenging task in complex power supply environments with unexpected impulsive noise (IN) and channel fading, which will significantly affect the signal statistical property. To address this problem, we propose a novel CD mechanism in the context of the wireless environment with IN and random channel fading. To be specific, taking the wireless channel status, IN and time-variant fading into account, a novel quaternary hypothesis testing model (QHTM) is formulated to describe the detection task, and by which a new dynamic state-space model (DSM) is developed to capture the dynamical behavior of the CD system. On this basis, a joint detection and estimation algorithm based on Bayesian statistical inference is devised to accomplish the CD task. Benefiting from the joint <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">posteriori</i> distribution estimation procedure, our algorithm can not only accurately detect the unknown channel status, but also estimate the real-time channel state information (CSI), thereby eliminating their effects on the detection performance. Numerical simulation results validate the proposed CD mechanism.