OS0824 格子磁石を用いたサンプリングモアレ法による大型高温配管の動的熱変形分布計測

Dynamic Thermal Deformation Measurement of Large-Scale, High-Temperature Piping in Thermal Power Plants Utilizing the Sampling Moiré Method and Grating Magnets

Usage of conventional energy resources has high limitations and constrains now a days. The thermal efficiency of the equipments in the modern thermal based power plant is mandatory for effective power generation with low production cost and pollution. The systems and equipments in the thermal power plant should be operated with optimum efficiency. An assessment of these system performance and comparing it with the design value is necessary for its improvement. This paper presents the findings of the observations and trials carried out on thermal power plant energy equipments. The main objective of this work is to assess the performance of various thermal power plant systems in respect of efficiency and determining the main factors which contribute to the efficacy of the power plant by indirect method. Further, suitable measures are recommended to enhance the energy performance with cost benefits. While making the measurements, care is taken to maintain the accuracy and wherever any discrepancy is found, the readings were again taken to ensure the best possible results.

Power systems are inherently water dependent. Future energy development needs to jointly consider the interaction between power and water systems, especially the stream dynamics related to both water temperature and availability. Such connection is particularly pronounced in thermal and hydro power plants, where once-through cooling systems face disruptions from high intake water temperature and water scarcity, and hydropower generation is affected by drought conditions. Equally important is the impact of power system operations on water temperature and availability. For instance, warm water discharged from thermal power plants can increase water temperature, while cool water released from reservoir bottoms can cause temperature declines. Additionally, hydropower operations can alter water availability through changes in reservoir storage. Despite the importance of those factors, existing electricity capacity expansion models typically do not fully consider such feedbacks between stream dynamics and power system operations, as they lack the capability to accurately represent cascade reservoir operations and cooling processes for thermal power plants at sufficiently high spatial-temporal resolutions. To address this research gap, we develop an integrated model coupling a hydrological model (Community Water Model, CWatM), a stream temperature model (River Basin Model, RBM), and a novel electricity capacity expansion model (Pathways for Renewable Energy Planning coupling Short-term Hydropower OperaTion, PREP-SHOT, https://github.com/PREP-NexT/PREP-SHOT) to better represent the two-way feedback between stream dynamics and power system operations. The coupled model, applied in Mainland Southeast Asia featured by a diverse array of hydropower reservoirs and thermal power plants, supports informed, sustainable, and environmentally friendly planning for future energy development in the region.

Entry into the electricity market: Uncertainty, competition, and mothballing options

Power generation in Saudi Arabia is mostly from thermal power plants. This paper involves the minimization of the total cost of power generation from thermal plants in the Western Operating Area of Saudi Electricity Company, incorporating the environmental constraints and the transmission line losses. Economic Dispatch is one of the most important function that is performed in a power system control center so as to minimize the oil consumption in thermal power plants and thus decrease the power generation cost. As the power generation process in thermal power plants causes the emission of significant amount of harmful gases such as carbon dioxide (CO 2 ), and oxide of nitrogen (NO x ), it is important to minimize the emission of these gases by appropriate allocation of the total power demand among the various power plants in the system on a continuous basis. Hence this paper focusses on the minimization of the fuel cost of the thermal power plants subjected to these emission constraints. The gradient descent technique based on Lagrange multiplier method is utilized in this environmental economic dispatch of the thermal power plants. Investigations are carried out with the daily hourly load curve corresponding to three days, each one covering three different seasons: summer, winter and Hajj. The investigations reveal that a considerable reduction in the emission of gases can be achieved with the implementation of the environmental economic dispatch function in the area load dispatch center

Digital twin and machine learning for decision support in thermal power plant with combustion engines

PurposeRecent developments in the electricity generation sector of Nigeria necessitated the re-assessment of its contribution to air emission level in the country as information provided by previous inventory is nearly out-of-date. The purpose of this paper is to quantify the carbon dioxide (CO2) emissions generated from existing thermal power plants in the country.Design/methodology/approachThermal power plants in Nigeria and their installed capacities were identified, and estimation of CO2 emission from each of the plants was carried out using the emission factor method. In addition to the direct emissions generated through the combustion operation of the power plants, indirect emissions resulting from upstream activities such as extraction, production, and transportation of fuels consumed by the thermal power plant was determined using the same method.FindingsIn total, 40 thermal power plants are currently operational in Nigeria. Additional 18 thermal plants are at different stages of completion. The operational thermal plants have average generation output of 40 percent of their installed capacity and produce 87.3 million metric tonne (mmt)/annum CO2 emissions. In total, 66.9 percent of the estimated emissions are direct emissions, i.e. fuel combustion emissions; the rest are indirect emissions. Additional 67.9 mmt was estimated as expected overall emissions from the thermal power plants under construction. Considering the global warming potential of CO2, proactive measures must be taken to regulate its emissions from the country’s thermal power plants.Originality/valueThis paper bridged the information gap existing in the emission inventory from the Nigeria electricity sector by providing up-to-date data on the contribution of the sector to greenhouse gas emission level in the country.

Rational planning of thermal power capacity is one of the main measures to reduce emissions.According to air pollution control plan, different environmental capacity regions provide different constraints to the scale of thermal power plants.With the development of electric market, unified relationship among thermal power plants has been changed to gambling one.To solve the above new problems emerged in the area of thermal power capacity planning, this paper presents a game model for thermal power capacity planning considering the constraint of environmental capacity.In this game-theory-based model, the thermal environmental adaptability factor, that reflecting the adaptability of environmental capacity to thermal power in different regions, is brought into the traditional profit function.Consequently, proper thermal power planning capacity adapting to environmental capacity could be obtained to provide support and basis for government regulation and enterprise decision.The effectiveness of the proposed model is validated by a series test results of different scale power planning examples.

Due to the growing world population and its increasing energy demand, the construction of new power plants is inevitable. At the same time, it is necessary to keep the rise of the global average temperature well below 2 °C compared to pre-industrial level in order to significantly reduce the impacts and risks of climate change. Therefore, an environmental friendly energy infrastructure is required to reduce greenhouse gas emissions. Solar thermal power plants are a promising technology, as they provide the possibility to buffer solar energy in a thermal storage. Thus, it can produce electricity according to the demand and is independent of meteorological fluctuations. A life cycle assessment is necessary to assess the environmental impact of a solar thermal power plant and its individual components. This work analyses the extent of the environmental effects of solar thermal tower power plants in the following selected impact categories according to the CML-method: Global Warming Potential (GWP 100 years), Abiotic Depletion potential (ADP elements), Eutrophication potential (EP) and Acidification Potential (AP). The most ecologically relevant components are identified and modelled with different specifications in order to compare the influence of different building types. Furthermore, the life cycle assessment model is applied to different geographical locations in order to enable site-specific considerations. The selected locations are Upington in South Africa, Evora in Portugal and Calama in Chile. The life cycle inventory is generated based on an extensive literature research and forms the foundation for the modelling of solar thermal tower power plants in the LCA software GaBi ts. As a result, the most ecologically relevant components are determined. A comparison of the different locations allows statements on the ecological potential of solar thermal tower power plants at a specific site. The heliostats and the molten salt (MS) as heat transfer fluid and storage medium dominate the impact on the GWP 100 years. The heliostats consist mainly of steel and glass and are needed in large numbers. The molten salt is used in a high amount and consists of a mixture from sodium nitrate and potassium nitrate which both have a high impact on GWP. Moreover, the transport and the construction on site have relevant contributions to GWP. The impact of the transport results from the large mass of all shipped components. The impact of the construction on site has copper cables as the main contributor. The end-of-life scenarios have a significant effect on the total impact. Depending on the recovery of the metals and especially the further use of the molten salt, the environmental impact is decisively influenced.

The present study aims to investigate the effect of Thermal power plant emissions upon two species of plant Alhagi mourorum and Suaeda vermiculata which growth in the region close to Thermal power plant. triplicater samples were collected seasonllys from autumn 2016 up to summer 2017 one time from each season. three station were selected in the study area to execute this study meters. The first station distances 400 meters from the thermal power station, The second station is located 800 meters from the thermal power plant . While, the third station distances 1200 meters from the thermal power plant . Three stations were with prevailing wind direction (north wind) , while control station situated far from the thermal power plant about 12 km. the concentratios of heavy metals Cd, Cu, Pb and Zn were estimate in root and shoot systems for both plants, their concentration in root system more higher than their concentrations in shoot system. its concluded from the present study that thermal electric power station emissions affected upon the plants which growth in the surrounding region with thermal power plant.

Methodology for thermodynamic and economic analysis of hierarchical dual-cycle gas-gas nuclear power and CHP plants with high-temperature reactors and helium as the circulating medium

Scrutiny of combustion quality and its equivalent NOx emissions from flame images in thermal and gas turbine power plants is of immense significance in the realm of climate change. A remote monitoring scheme using image processing, Artificial Intelligence (AI) and Internet of Things (IoT) to efficiently minimize the flue gas emissions can be carried out. The principal goal is in detection, recognition and understanding of combustion conditions in power plants ensuring low green house or flue gas emissions which contribute to climate change. In this work, smart sensors using feed forward neural network with Ant Colony Optimisation (ACO) and Particle Swarm Optimization (PSO) are used for estimation of various flue emissions. This scheme uses the information from the colour of the flame images in the combustion chamber at power plants, which is the foundation for obtaining high combustion quality and low flue gas emissions. The initial gait is to describe a facet vector for each flame image including 10 feature elements. Image Enhancement is done to obtain distinctive attributes from the captured images. The perception of object (flame feature) recognition and classification of the flame image is conceded out to measure the combustion quality and flue gas emissions from the flame colour. The samples including some flame images, parts of which are used to train and test the model. Finally, the entire samples are recognized and classified. Experiments prove that flame image classification to be an effective monitoring scheme for reducing the flue gas emissions.  

3 - Steam turbine cycles and cycle design optimization: advanced ultra-supercritical thermal power plants and nuclear power plants

This Special Issue aims to cover the recent research results being developed, both theoretically and experimentally, on the laboratory, pilot, and industrial scale about thermal processes in power plants. This reprint focuses on thermal and flow processes and their impact on highly efficient and low-emission electricity generation and heat production in thermal power plants. Special attention is given to steam condensers and separators for application in thermal power plants, development systems and tools for heat production forecasting in combined heat and power plants, presenting such ideas as the negative CO₂ emission gas power plant cycle and production of gas fuels by sewage sludge gasification as well as about methods and techniques for CO₂ capture. The research investigation results can find implementation in real-scale power technologies such as steam power plants, gas power plants, nuclear power plants, and hybrid power plants based on renewable energy sources.

The superheater in the thermal power plant makes the wet steam into the dry steam with high temperature and high pressure by using the boiler heat. The dry steam pressure rotates the turbine-generator system. The efficiency and life time of the boiler heavily depends on the steam temperature regulation. The steam temperature can be deviated from the reference by the MW demand of the power plant. It is therefore required that the PI(proportional-integral) controller should be robust against the disturbance such as the MW demand. In this paper, the PI controller with the integral state predictor is proposed and applied to regulate the steam temperature of the superheater, and it is compared with the conventional PI controller operated in the thermal power plant in view of control performance.