Power Generation Process Research Articles

Analysis and Design of Real Time Data Acquisition System for Critical Analog and Digital Parameters in Nuclear Power Plant

Data is the basis of making any decision. Whether the Data is economical, political, environmental, or Process control related, it is required to be acquired in a precision manner and used for Control / monitoring. Data Acquisition Systems used in Power Plants determines the changing status and behavior of process of power generation, foreseeing impacts, and managing what can be controlled for the maximum benefit to the plant with minimum risks and human interaction. This paper provides the general ideas of developing the Real Time Data Acquisition System with scan rate up to 1 millisecond. First section of the paper concentrates on the introduction of DAS and RTDAS. In next section it exposes the analysis of RTDAS. Last section of the paper presents the design issues of the RTDAS. This paper mainly concentrates on RTDAS for critical analog (Disturbance Recorder) and digital (Event Sequence Recorder) parameters in nuclear power plant.

Evaluation of monolith catalyst in catalytic combustion of anode off-gas for solid oxide fuel cell system

Solid oxide fuel cells (SOFC) can operate at high temperatures (> 650 °C) and have attracted attention because of their high efficiency. However, the CH4, CO, and H2 contained in the anode off-gas that are not reformed or does not participate in the SOFC power generation process must be treated. A catalytic combustion process, which can improve the efficiency by treating the target substances and heat recovery, is essential for this purpose. This study examined the CH4 combustion performance of Pd- and Pt-supported catalysts in the presence or absence of H2O in the feed, at O2/2CH4 ratios of 15 and 20, at a gas hourly space velocity (GHSV) of 5000, 10,000, and 20,000 h−1, and at inlet temperatures of 100–580 °C. The Pd-rich catalyst with a cell per square inch of 400 exhibited the best CH4 combustion performance, as CH4 combustion was possible even at an inlet temperature of 200–300 °C. The performance of this catalyst was evaluated by applying it to a 5-kW scale catalytic combustor. CH4, CO, and H2 combustion experiments of the catalyst in this apparatus were performed at a O2/C of 12–15, GHSV of 8400–16,800 h−1, and inlet temperatures of 100–580 °C, and CO and H2 conversions exceeding 98 % and a CH4 conversion exceeding 75 % were obtained. We expect that the results of this study can be used for the scale-up design of high-efficiency SOFC systems capable of reducing the concentrations of emitted CO and CH4 and utilize the heat generated in the power generation process through the AOG catalytic combustor.

Photovoltaics literature survey (No. 181)

Photovoltaics literature survey (No. 181)

Performance Monitoring of Wind Turbines Gearbox Utilising Artificial Neural Networks — Steps toward Successful Implementation of Predictive Maintenance Strategy

Manufacturing and energy sectors provide vast amounts of maintenance data and information which can be used proactively for performance monitoring and prognostic analysis which lead to improve maintenance planning and scheduling activities. This leads to reduced unplanned shutdowns, maintenance costs and any fatal events that could affect the operations of the overall system. Performance and condition monitoring are among the most used strategies for prognostic and health management (PHM), in which different methods and techniques can be implemented to analyse maintenance and online data. Offshore wind turbines (WTs) are complex systems increasingly needing maintenance. This study proposes a performance monitoring system to monitor the performance of the WT power generation process by exploiting artificial neural networks (ANN) composed of different network designs and training algorithms, using simulated supervisory control and data acquisition (SCADA) data. The performance monitoring is based on different operating modes of the same type of wind turbine. The degradation models were developed based on the generated active power resulting from different degradation levels of the gearbox, which is a critical component of the WTs. The deviations of the wind power curves for all operating modes over time are monitored in terms of the resulting power residuals and are modelled using ANN with a unique network architecture. The monitoring process uses the recursive form of the cumulative summation (CUSUM) change detection algorithm to detect the state change point in which the gearbox efficiency is degraded by evaluating the power residuals predicted by the ANN model. To increase the monitoring effectiveness, a second ANN model was developed to predict the gearbox efficiency to monitor any failure that could happen once the efficiency degrades below a threshold. The results show a high degree of accuracy in power and efficiency prediction in addition to monitoring the abnormal state or deviations of the power generation process resulting from the degraded gearbox efficiency and their corresponding time slots. The developed monitoring method can be a valuable tool to provide maintenance experts with alarms and insights into the general state of the power generation process, which can be used for further maintenance decision-making.

Design, energy efficiency, and CO2 emissions analysis of a power generation process of coking dry gas reforming coupled with solid oxide fuel cell and organic Rankine cycle

Coking dry gas is a kind of refinery dry gas, which is rich in H2 and light hydrocarbon resources, but it’s often used as fuel, resulting in inefficient utilization of dry gas resources and a large amount of air pollutants emissions. Solid oxide fuel cell can efficiently convert the chemical energy of hydrogen into electricity. Therefore, this work establishes a model of a power generation process of coking dry gas reforming coupled with the solid oxide fuel cell and organic Rankine cycle. Process simulation is used to analyze the influence of key operating parameters on the system output performance. The obtained results indicate that the net electrical efficiency of the proposed system is increased from 45.45 % of the coking dry gas direct combustion for power generation system to 56.89 %. In terms of environmental impact, the CO2 emissions of the new system is 373.31 kg/MWh, 20.12 % lower than that of the direct combustion process. Besides, the effect of air excess ratio on system performance is evaluated and the net electrical efficiency of the proposed system increases to 63.73 % as the air excess ratio decreases from 2.0 to 1.1. The above results show that the proposed hybrid power system can provide an effective way for efficient and clean utilization of coking dry gas.

Performance Analysis of the Impact of Mathematical Modelling and Optimisation on Power Generation Systems Via Renewable Sources

A significant component of society’s sustainable development is producing energy from renewable sources. Various energy sources, including solar, biomass, biogas, and wind, must be utilised to their full potential to fulfil current demands. In most nations like Nigeria, there are a lot of rural areas that suffer from energy supply. This has brought up many studies on how optimisation techniques can help manage the sustainability of the supply of this generated energy to such areas. Therefore, this review paper focuses on the performance analysis of several studies on the impact of mathematical modelling and various optimisation techniques on power generation systems via renewable sources. The study review papers from a quality outlet such as Elsevier, Springer, and other quality journals indexed in Scopus databases. On biomass production, wind energy production system, steam and solar energy. The finding from the study showed that the application of real-life engineering optimisation tools and models developed significantly improved the power generation process globally. Therefore, in the study’s conclusion, the authors provided sustainable recommendations on how to apply these models to improve the sustainable power generation process.

A Study on Global Warming Effect of Combined Cycle Power Generation Process

A Study on Global Warming Effect of Combined Cycle Power Generation Process

Fabrication and study of a high output power flexible fabric hydrovoltaic generator

Higher capacity of attracting ions causes an increase in charge imbalance and enhances the power generation performance of GCMHEG, and only physical behavior exists in the modified power generation process.

Survey Paper About Carbon Footprint

The aim of this proof of concept is to develop a framework to trace the carbon footprints emitted by fossil fuels during power generation. The framework will utilize a life cycle assessment approach to identify the amount of greenhouse gas emissions associated with each stage of the power generation process, from raw material (fuel) extraction to power delivery. The proof of concept will focus on the use of coal and natural gas, which are the most widely used fossil fuels in power generation.The data collected from sources is used to create model which can help us to estimate the amount of carbon footprint generated from different types of power plants like coal-fired power plants and natural gas-fired power plants.The results of this proof of concept are analyzed to identify areas where we can reduce the greenhouse gas emission and also to develop and deploy strategies to transition to cleaner sustainable energy sources.Overall, this concept will provide a valuable tool for energy policymakers and stakeholders to make informed decisions about reducing carbon footprints from fossil fuel power generation

Software prototype development for non-centralized objects of wind flow amplification

This research is devoted to the development of software to increase the efficiency of autonomous wind-generating substations using panel structures, which will allow the use of wind energy to generate electricity with minimal losses and for the life support of buildings and structures. In the course of the work, a software and hardware system with a functional diagram for experimental measurements was developed. The paper also describes the process of modeling wind generation, collecting and transmitting real-time data to a web server via the HTTPS protocol. Due to the intensive development of wind energy in Kazakhstan, there is a need to apply methods to improve the energy generation process. In particular, the use of hardware and software to monitor and make decisions on optimizing the power generation process will help solve the problem of limited economic and labor resources. The results of the experiments revealed that the automatic control of the shield structures allows specialists to increase the effectiveness of the energy generation process by 25 % and, thus, a non-linear relationship between the power of the generated energy, the speed and direction of wind has been revealed. It should also be noted that the results obtained in the course of this research make it possible to solve the problem of saving electricity in the cities of Kazakhstan, since so far there are only large-scale wind farms, which is not always available in simple urban conditions. Moreover, the software developed during the study will allow autonomous control and analysis of the behavior of the wind farm, taking into account various weather conditions. In the future, the methods of data analysis will be applied to the data obtained via the process of modeling. A script for receiving and transmitting real-time data with wind speed and direction sensors has been developed

Design of Renewable Energy Consumption Scheduling Model Based on Quantitative Feedback Theory

In the renewable energy consumption scheduling, due to the large fluctuation of wind power output, the renewable energy consumption rate is low, and the energy consumption scheduling effect is poor. Therefore, a new renewable energy consumption scheduling model based on quantitative feedback theory is designed. For the first time, calculate the output response of wind power generation, obtain the output change rate of the wind farm at the time scale, and determine the response curve of wind power generation according to the power generation process is divided into three stages: the initial stage, the peak stage and the end stage, and the response output during the peak period, so as to obtain the transfer rate of output during the peak period. Build a mathematical model of renewable energy power generation, calculate the output state of wind power generation, and analyze the output characteristics of renewable energy storage system; Secondly, the objective weight coefficient of renewable energy consumption is determined by using quantitative feedback theory, the objective function of renewable energy consumption is constructed, the power injected by parameter nodes is determined, the quantitative feedback controller is designed by using loop shaping technology, the control structure of two degrees of freedom is determined, the objective function of renewable energy consumption is constructed, and the constraint range of renewable energy consumption capacity is determined according to static constraints such as current constraints and voltage constraints; Then, the quantitative feedback theoretical controller is designed, the input and output transfer functions of the consumption system are determined, and the renewable energy consumption scheduling model is constructed. The renewable energy consumption scheduling model is solved by particle swarm optimization through a variety of index parameters in the renewable energy consumption determined by the QFT controller. The experimental results show that the proposed model can effectively improve the renewable energy consumption rate and optimize the consumption scheduling effect.

Techno-Economic Analysis towards Full-Scale Pressure Retarded Osmosis Plants

Pressure retarded osmosis (PRO) is a power generation process that harnesses the salinity gradient between two water bodies of different salinities. Using high salinity water as a draw solution, this work assesses the techno-economic feasibility of the technology to generate electricity using single and multistage systems. This work utilizes a simulator built on the rigorous Q-Electrolattice equation of state and a mass transfer model that accounts for concentration polarization, combined with the Dakota optimization tool to perform sensitivity analysis and optimization studies. The economic indicator of interest is the Levelized Cost of Electricity (LCOE), which serves to compare PRO with other sources of renewable energy. An LCOE value of USD 0.1255/kWh was obtained from the use of commercial membranes at an efficiency of 100% for the mechanical components of the PRO system. This LCOE drops to USD 0.0704/kWh when an ideal membrane is used—thus showing the improvements to economics possible with improved membrane properties. With currently obtainable membrane properties and mechanical equipment, the LCOE of a single-stage process increases to USD 0.352/kWh, which is not cost-competitive with other renewable energy sources. Setting up multistage PRO systems towards minimizing the LCOE was found to be detrimental to the net power production by the plant.

Overview of carbon capture, utilisation and storage technologies to ensure low-carbon development of energy systems

Carbon dioxide CO2 is a component of air that is responsible for the growing global warning and greenhouse gases emissions. The energy sector is one of the main sources of CO2 emissions in the world and especially in Ukraine. Carbon capture, utilization and storage (CCUS) is a group of technologies that play a significant role along with renewable energy sources, bioenergy and hydrogen to reduce CO2 emissions and to achieve international climate goals. Nowadays there are thirty-five commercial CCUS facilities under operation around the world with a CO2 capture capacity up to 45 million tons annually. Tougher climate targets and increased investment provide new incentives for CCUS technologies to be applied more widely. CCUS are applications in which CO2 is captured from anthropogenic sources (power generation and industrial processes) and stored in deep geological formations without entering atmosphere or used in various products using technologies without chemical modification or with conversion. The article discusses the use of various technologies of CO2 capture (post-combustion capture, pre-combustion capture and oxy-combustion capture), CO2 separation methods and their application in the global energy transition to reduce the carbon capacity of energy systems. Technical and economic indicators of CO2 capture at different efficiencies for coal and gas power plants are given. Technologies of transportation and storage of captured carbon dioxide and their economic indicators are considered. The directions for the alternative uses of captured CO2, among which the main ones are the production of synthetic fuels, various chemicals and building materials, are also presented and described in the paper. The possibility of utilization captured СО2 in the production of synthetic fuel in combination with Power-to-Gas technologies was studied. Keywords: greenhouse gases emissions, fossil fuels, СО2 capture technologies, capture efficiency, synthetic fuel

Two Facile Aniline-Based Hypercrosslinked Polymer Adsorbents for Highly Efficient Iodine Capture and Removal

Effective capture and safe disposal of radioactive iodine (129I or 131I) during nuclear power generation processes have always been a worldwide environmental concern. Low-cost and high-efficiency iodine removal materials are urgently needed. In this study, we synthesized two aniline-based hypercrosslinked polymers (AHCPs), AHCP-1 and AHCP-2, for iodine capture in both aqueous and gaseous phases. They are obtained by aniline polymerization through Friedel-Crafts alkylation and Scholl coupling reaction, respectively, with high chemical and thermal stability. Notably, AHCP-1 exhibits record-high static iodine adsorption (250 wt%) in aqueous solution. In the iodine vapor adsorption, AHCP-2 presents an excellent total iodine capture (596 wt%), surpassing the most reported amorphous polymer adsorbents. The rich primary amine groups of AHCPs promote the rapid physical capture of iodine from iodine water and iodine vapor. Intrinsic features such as low-cost preparation, good recyclability, as well as excellent performance in iodine capture indicate that the AHCPs can be used as potential candidates for the removal of iodine from radioactive wastewater and gas mixtures.

Techno-economic and environmental assessment of a novel co-generation system integrating heat pump with Allam cycle

Allam cycle is known as a promising alternative cycle for power generation, which combines the advantage of both oxygen-enriched combustion technology and supercritical carbon dioxide technology. In this study, an integrated energy system consisting of an Allam cycle and a heat pump is proposed to co-generate power and heat. The heat of carbon dioxide in the compression train of the Allam cycle is recovered by the heat pump system, which is used for space heating. The techno-economic and environmental performances of the co-generation system are analyzed and compared with those of the single systems. The results show that the net electrical efficiency of the Allam cycle is improved by 1.56 %, and the coefficient of performance of the heat pump in the combined system is increased by 42.02 %. The lowest and highest investment-increment payback periods are 0.26 and 5.80 years, which indicates the proposed integrated system is economically feasible. Meanwhile, the sensitivity analysis of key economic parameters is also conducted. Finally, the carbon emission of different generation configurations are compared and the results indicate that the integration of the heat pump with the Allam cycle can effectively reduce system carbon emission. The proposed concept provides a new approach to efficient utilization of the heat from the carbon dioxide mixture cooling process for heat and power generation with nearly zero emission, and it would be a better choice for cold regions.

Low-Carbon Scheduling of Integrated Electricity and Gas Distribution System Considering V2G

With the development of EVs (Electric Vehicles) and the rapidly developing policies on low carbon and environmental protection, electric power systems and natural gas systems become increasingly larger. Under these circumstances, the V2G (Vehicle-to-grid) and the coordinated operation of an integrated electricity–gas distribution system (IEGDS), considering CO2 emissions, can play a part together in the process of energy conservation. Firstly, the V2G model is discussed; this paper presents the cost differences between out-of-order and order for the car. Secondly, the IEGDS model presents coupling constraints of gas turbines and power-to-gas. Lastly, carbon emission is considered in this paper; a carbon capture plant (CCP) captures the CO2 burning by fossil fuel in the power generation process and stores it in a carbon storage tank. This paper also considers trading with the carbon market via a carbon storage warehouse. With the cooperation of various components, a comprehensive model considers the use of V2G to store power in the IEGDS system, with consideration of the carbon trade. Numerical experiments validate the effectiveness of the combination between V2G and IEGDS, considering carbon emissions and carbon trading.

Research on Greenhouse Gas Emissions and Economic Assessment of Biomass Gasification Power Generation Technology in China Based on LCA Method

China is rich in biomass resources, taking straw as an example, the amount of straw in China is 735 million tons in 2021. However, at the level of resource use, biomass resources have the practical difficulties of being widely distributed and difficult to achieve large-scale application. By collecting large amounts of biomass and generating electricity using gasification technology, we can effectively increase the resource utilization of biomass and also improve China’s energy security. By using a life cycle assessment (LCA) approach, this paper conducted a life cycle assessment with local biomass gasification power generation data in China and found that the LCA greenhouse gas emissions of biomass gasification power generation technology is 8.68 t CO2 e/104 kWh and the LCA cost is 674 USD/104 kWh. Biomass gasification power generation technology has a 14.7% reduction in whole life carbon emissions compared to coal power generation technology. This paper finds that gas-fired power generation processes result in the largest carbon emissions. In terms of economics, this paper finds that natural gas brings the most additional costs as an external heat source.

Group decision‐making analysis based on distance measures under rough environment

AbstractA rough set as a superset of a crisp set is a mathematical tool to cope with uncertainty using initial data without additional assumptions and pre‐defined parameters. Using the technique of upper and lower approximations, rough models provide a complete description of the problem. This paper aims to introduce the notion of distance function, which is a metric, in rough graphs. We establish formulae of distance function, degree and radius of certain products of rough graphs in terms of initial given rough graphs. We discuss the concepts of weak isomorphism and isomorphism in rough graphs, and describe the properties of isomorphic rough graphs. We demonstrate the significance and importance of the distance function with an application to a decision making problem concerning organ trafficking networks. An application of rough matrices in steam valve systems is discussed, and we show how they can help to identify the potential failures and risk components during the power generation process. The results obtained under the rough model are compared with existing extensions of graphs and fuzzy based approaches.

The Economic Impact and Significance of Implementing New Technologies in the Power Storage Segment

In the present article will be considered the economic aspects in the implementation of new technologies in energy storage and energy transportation. After reduction of the carbon footprint in power generation process, it’s also very important that the flexible transfer and storage of the produced energy that is not immediately consumed. For the last 15 years the industrial storage of electricity is technically realistic, but it’s still a matter of discussion how economically justified it is. Some economic risks can be identified and some security measures can be taken. There is possible optimization of energy storage that can make it adjustable to the demand and energy market prices. There are some implications to the Industry 4.0 and increase of e-mobility generated energy consumption.

Environmental impact assessment of VOC emissions from biomass gasification power generation system based on life cycle analysis

The control of volatile organic compounds (VOC) is one of the key challenges in biomass combustion. This study aims to establish a process-based model to assess the life cycle VOC emissions of a biomass gasification power plant in China. In this study, the life cycle assessment (LCA) method was used for the first time to evaluate the direct VOC emissions and indirect VOC emissions from biomass gasification power generation. The whole system consists of three parts: biomass waste feedstock system, gasification power generation system and waste treating system. And waste treatment mainly includes waste water treatment and waste gas treatment. Results show that the life cycle VOC emissions intensity from the biomass gasification power generation process as a whole are calculated as 57.05 g/MWh, without considering the influence of air pollution control devices’ (APCDs). With the implementation of APCDs, this value will be reduced to 7.08 to 22.83 g/MWh, reducing by 12.41 to 40.02 %. In the scenario analysis, APCDs with different combinations of installations are evaluated by applying the practical engineering applications. The scenario of selective catalytic reduction (SCR) and wet electrostatic precipitation (WESP) can achieve the best removal effect, under which VOC emissions intensity can achieve 34.22 g/MWh, and the indirect emissions account for 46.15 % of life cycle VOC emissions, which are mainly from wastewater treatment process. The photochemical ozone generation potential and ozone layer depletion potential from emitted VOC are the two largest in this scenario, accounting for 17.71 % and 8.59 % respectively. If all open burning and indoor combustion of biomass in China can be replaced by the biomass gasification power generation technology, the relevant national VOC emissions reduction potential could reach up to 1.95 Mt/year. Among all the provinces, Heilongjiang, Anhui, Henan, Shandong and Jilin are the five provinces with the highest VOC emissions reduction potential. The influence of key input variables on overall VOC emission is also analyzed in this study. Based on the results, the optimal direction and possible measures to reduce VOC emission are put forward. This study is of great significance for the accurate control of VOC emissions in biomass gasification power generation technology.