Large-scale Thermal Power Research Articles

Influence of different thermal degradation processes on the optical property of Pyromark-2500

Concentrating solar power (CSP) is emerging as an increasingly important component of renewable energy. CSP systems are being widely adopted in the establishment of large-scale thermal power plants, with an increase in the number of successfully operating demonstration systems.Special coatings are generally used in various types of receivers for solar collector systems. Selective coatings are used for receivers intended to be operated at low or medium temperatures. Similar selective coatings are not currently available for application under high temperatures. In such cases, high-temperature absorbing coatings are generally used to improve the thermal efficiency of the receiver and protect their tubes from oxidation. It is worthwhile to observe the behaviour of such coatings when exposed to high fluxes for extended periods, in order to develop more efficient technologies.Currently, the essential properties for characterizing the paint are absorptivity, emissivity, and structural integrity of the coating (adhesion and cohesion). Good understanding of the behaviour of this paint under representative operating conditions would help to improve the design of the plant, maintain its performance and maintain the thermal efficiency of the receiver. The principal objective of this study was to provide extensive knowledge of the durability and variation of the optical properties of Pyromark when it is consolidated with improved methods. No degradation or loss of optical performance was observed at temperatures under 700 °C. The substrate affected the crystalline structure of an initial coating at high temperatures owing to the diffusion of metal ions. Concentrated solar radiation was the main factor that affected the integrity of the coating. At concentrations higher than 550× suns, a significant area of the irradiated samples was found to be uncoated. These results can be used to design more accurate latest generation receivers to improve the performance of this technology.

Research on Grid-connected Performance of Solar-thermal-storage Coupled System Including Thermal, PV and Flywheel

With the rapid development of renewable energy, the demand for frequency regulation and peak shaving of coal-fired power plants is increasing. As the utilization hours of coal-fired power plants are gradually reduced, the economy of coal-fired power plants is gradually reduced. In order to improve the economic benefits of thermal power plants, thermal power plants are changing from the income model dominated by power generation to the income model of “cogeneration of power generation and auxiliary power service”. Among them, the energy storage system of Lingwu power plant of Ningxia electric power company of Guoneng group belongs to the first large-scale thermal power plant large-capacity solar thermal energy storage (flywheel) project at home and abroad. While ensuring the functions of conventional power supply, heating and cogeneration, the system can also provide auxiliary power services, support the safe and stable operation of a large power grid, and improve the flexibility and economic benefits of traditional thermal power plants. With the application of new technologies in coal-fired power plants, improving the economy of coal-fired generating units and power auxiliary services will be the main direction of power generation groups. At the same time, it also puts forward new requirements for power grid operation.

Thermodynamic evaluation of a pumped thermal electricity storage system integrated with large-scale thermal power plants

The use of renewable energies is an alternative for decarbonizing the electricity generation sector and thus large-scale energy storage systems are required. The purpose of the present study is to assess the performance of the emerging Pumped Thermal Electricity Storage (PTES) systems and their integration with thermal power plants (TPP). A suitable thermal storage system (TES) has been extensively studied and five alternatives for the simulation of two-tank molten salt storage are implemented. Several options for the charge and discharge systems are modeled. The Round-Trip-Efficiency (RTE) is evaluated and accompanied by the power and energy density. A sensitivity analysis is performed by varying the main operational parameters to evaluate different utilization scenarios. The results are compared with the reported performance of commercial systems. The RTE of the integrated PTES configurations is around 50%–65% and high values of energy and power density can be achieved. For Rankine cycle configurations, the argon heat pump is recommended. Reusing old coal power plants, while plausible for reducing costs, results in moderate RTEs. In modern supercritic Rankine cycles, the reachable RTE is greater than 63%. RTE in Brayton and air heat pump configurations is similar, especially over 700°C at the discharge. However, it is highly sensitive to other operational parameters, and the energy density is significantly lower. Therefore, a more suitable TES system is required. Compared to commercial technologies, the system studied has the potential of being implemented if energy and power density are exploited to produce cost-effective systems.

Modeling of Large-Scale Thermal Power Plants for Performance Prediction in Deep Peak Shaving

To integrate more renewable energy into the power grid, large-scale thermal power plants have to extend their operating ranges and participating in deep peak shaving. In order to improve the thermal economy of large-scale thermal power plants participating in deep peak shaving, and to determine the performance of a thermal system under different conditions, a method of modeling for the performance prediction of large-scale thermal power plants in deep peak shaving is proposed. In the algorithm design of the model, a three-layer iterative cycle logic is constructed, and the coupling relationship between the parameters of the thermal system is analyzed from the mechanism level. All of the steam water parameters and the correction values of the flow rate at all levels of the system after the parameter disturbance are obtained. The algorithm can simulate the response of a thermal power plant under load variation and operation parameter variation. Compare the error between the data given by the prediction model and the test, the accuracy of the proposed prediction model is verified. When the unit participates in deep peak shaving, the prediction model is used to analyze the relative deviation of the unit thermal efficiency caused by cycle parameters and energy efficiency of equipment. It provides a date basis for the performance evaluation and multi-parameter coupling optimization. The research results can be used to determine the operation mode and equipment transformation scheme.

Analysis and treatment of vibration of 1000MW secondary reheat steam turbine with super-long single-support shafting

In the context of new energy grid connection, thermal power units are gradually developing in the direction of large-scale and long-axis. However, due to the static deflection of the long shaft system, the rotor presents the shape of a lift curve during the installation process, which brings a huge challenge to the vibration stability of the rotor during operation. In addition, the shafting of the new million units in my country gradually takes the single support as the main support form, and the double support solution cannot be directly applied to the method of dealing with vibration excess. At the same time, there are few mature and complete technical solutions for reference in China. In this regard, this paper analyzes the vibration data and frequency spectrum of the generator during the commissioning of the No. 2 59.9 m ultra-long shafting unit in a factory, and finds that the vibration is caused by the thermal state generated by the generator rotor under load. unbalanced. Finally, after designing a targeted balance weight scheme and implementing it on site, the vibration of the generator bearing has reached an excellent level. This paper fills the vacancy of the vibration treatment of the ultra-long single-support shafting of the million-level units in China, and lays the foundation for the large-scale and long-shafted thermal power units.

Research of Turbine Oil Varnish in Generator Unit

In recent years, due to the fact that thermal power generating units have been deeply involved in the peak shaving work of the power grid, the frequent start and stop operations of the units and rapid load-carrying operations have made the operating conditions of the units very bad. In large-scale thermal power generation units, shutdown accidents caused by varnish failures are becoming more common. Take the serious varnish failure of Unit 3 in a domestic power plant as a case for analysis. The steam turbine oil after the varnish is formed is fully analyzed and tested and the metal ion content test is carried out. The changes in the physical indicators of the steam turbine oil during the formation of the varnish are studied to determine the influence of the steam turbine oil on the physical indicators of the steam turbine oil during the formation of the steam turbine oil. The operation and maintenance personnel can detect the varnish in advance through the daily sampling and analysis of the steam turbine oil, and timely take treatment measures to remove the varnish components in the oil to ensure the safe and stable operation of the unit. This article summarizes the reason for the formation of varnish and the detection method of varnish. It is of great significance to effectively discover and control the production of varnish during the operation of the generator set, to study the formation mechanism of varnish and to find an effective method to remove varnish. This article also introduces the commonly used paint film treatment methods for the convenience of electric power technicians.

Uncovering GHG emission characteristics of industrial parks in Central China via emission inventory and cluster analysis

Abstract Industrial parks (IPs) contribute greatly to China's economic development while emitting lots of greenhouse gas (GHG). Establishing GHG emission inventories for IPs is essential to generate low-carbon strategies. Taking 11 IPs in Central China as objects, this study established GHG inventories including direct and indirect emissions, exploring the characteristics from the point of view of energy types and industrial sectors. We then adopted cluster analysis to classify these IPs into “3Hs”, “3Ls” and “Mixed” parks, and subsequently chose representative IPs for case study. The results show that total CO2 emissions of the parks in 2017 were 14.47 Mt. Coal combustion from energy types and energy-intensive industries from industrial sectors were the dominant emission sources, both accounting for 80% of the total emission in 11 IPs. Reducing power export and using renewable energy are crucial to mitigate GHG emission in the IPs including large-scale thermal power plants. Cluster analysis reveals that “3Hs” and “Mixed” parks should be put in a high priority in GHG mitigation, focusing on energy-intensive industries transformation and energy structure adjustment. This study is helpful to understand GHG emission characteristics of IPs in Central China and promotes the proposal and implementation of GHG emission reduction strategies in IPs.

Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

Research on vibration control of large-scale thermal power plants

Research on vibration control of large-scale thermal power plants

Performance evaluation of a large-scale thermal power plant based on the best industrial practices

The aim of this study is to assess and evaluate the performance of a large-scale thermal power plant (TPP). The performance rating was conducted in compliance with the statistical principles. The data for this analysis were obtained for a TPP with an installed capacity of 375 MW during a span of 8 years (2010–2017). Four parameters were used to evaluate the performance of the TPP including the availability, the reliability, the capacity factor, and the thermal efficiency. These parameters were calculated using a set of equations and then compared to the international best practices and target values. The results indicate that approximately 91% of the expected capacity was available throughout the studied period against the industry best practice of 95%. However, the average TPP’s reliability was found to be approximately 95% against the target value of 99.9%. Furthermore, the average capacity factor throughout the studied period is 70% as against the international value of 40–80%. Moreover, the thermal efficiency of the TPP is 40% against the target value of 49%. Due to the outage hours and malfunctions, the power losses throughout the studied period reached 846 MW. Overall, the analysis indicates that the studied TPP is not within the scope of the best industrial practices.

Study on oxidation desulfurization treatment of tail gas from large thermal power plants in Central Asia

In recent years, Kazakhstan’s economic development has brought serious environmental problems. A large number of exhaust emissions are the important reasons for environmental pollution. Most of the tail gas emissions are due to coal combustion. In Kazakhstan, as many as 70% of large-scale thermal power plants will produce a lot of sulfur dioxide and other substances when burning coal, which will lead to acid rain and bring serious harm to the environment. On this basis, Kazakhstan continues to carry out research on desulfurization and denitrification technology of exhaust gas, so as to reduce the air pollution caused by exhaust gas. Combined with wind energy development technology, the oxidation desulfurization treatment method of power generation tail gas of large thermal power plants in Central Asia is studied in order to better purify the power generation tail gas and protect the environment.

Phase-space exploration of unit ensembles in energy management

Abstract Currently, a transition of the electrical power system occurs that results in replacing large-scale thermal power plants at transmission grid level by small generation units mainly installed in the distribution grid. A shift from the transmission to the distribution grid level and an increase in ancillary service demand is a direct result of this transition, demanding delegation of liabilities to distributed, small energy resources. Decoder-based methods currently are not able to cope with ensembles of individually acting energy resources. Aggregating flexibilities results in folded distributions with unfavorable properties for machine learning decoders. Nevertheless, a combined training set is needed to integrate e. g., a hotel, a small business, or similar with an ensemble of co-generation, heat pump, solar power, or controllable consumers to a single flexibility model. Thus, we improved the training process and use evolution strategies for sampling ensembles.

Energy and economic performance assessment of the novel integration of an advanced configuration of liquid air energy storage plant with an existing large-scale natural gas combined cycle

This article proposes the novel integration of an advanced configuration of Liquid Air Energy Storage (LAES) plant and an additional gas turbine cycle with an existing large-scale Natural Gas Combined Cycle (NGCC). A novel mode of exploiting the electric energy stored within the LAES plant and additional gas turbine cycle in combination with the existing NGCC is aimed at increasing its revenues in the electricity market. The energy performance analysis of the integrated plant at off-design conditions is carried out in presence of simultaneous changes of the pressure in the liquid air storage site (p3) and of the pressure at the outlet of the cryogenic pump in the discharging circuit (p25). The maximum storage efficiency is 2.173. The uncertainty economic analysis is performed in three alternative economic scenarios - expected, pessimistic and optimistic - in order to assess the profitability of the installation and operability of the integrated plant compared with the stand-alone NGCC. In the expected scenario, the integrated plant leads to profitability in the whole range of each p3 and p25, with the exception of the minimum value of p25. With varying p3 and p25, the profitability is always absent in the pessimistic scenario, whereas it is always present in the optimistic one. The proposed approach can be extended to the integration of an LAES plant with a generic existing large-scale thermal power plant in order to increase its revenues in the electricity market.

Study on the Seismic Performance of Bent Columns in Vertical Bent Frame Structures

A novel reinforced concrete (RC) vertical bent frame structure system consisting of a RC frame structure and RC bent structure has been proposed for the development of large-scale thermal power plants. To better understand the seismic performance of RC bent columns in vertical bent frame structures, a 1/5-scale representative component selected from a common vertical bent frame structure was tested by quasi-static testing (QST). The failure mode hysteretic characteristics, ductility, energy dissipation capacities of RC bent columns were investigated. Based on the experimental results, finite element models for the bent frame columns and vertical bent frame structures were developed and the nonlinear dynamic analyses were carried out. The results of finite element analysis indicate that the axial pressure ratio has significant effects on the seismic behaviour of RC bent columns. The relationship of drift angle for bent frame column under frequent earthquake and infrequent earthquake are investigated. The limitation values of axial compression ratios and the inter-storey drift angle for RC bent columns in vertical bent frame structures are suggested.

Intelligent Construction and Management of Thermal Power Plant Based on Internet + Mode

How to respond to the national call, the establishment and management of intelligent thermal power plants under the Internet + mode is a problem that the current thermal power plant management staff needs to think about. Throughout the domestic large-scale thermal power companies have gradually entered the era of information and intelligent management. Based on this, the paper first analyzes the concept and characteristics of intelligent thermal power plants, analyzes its construction foundation, discusses the system architecture and business direction of intelligent thermal power plant construction, and combines new technologies such as artificial intelligence and new products to analyze intelligent thermal power plants. Prospects for development, thereby maximizing the economic benefits of the power plant and the social benefits.

Potential economic gains and emissions reduction on carbon emissions trading for China's large-scale thermal power plants

Carbon emissions trading is one of the important economic means to solve the environmental externality. Based on the data of CO2 emissions from the thermal power plants over the period from 2005 to 2010 in China, this paper uses no-parametric optimization models to estimate the potential economic gains and potential carbon emissions reduction under three allocation strategies of carbon emissions trading allowance. Results show that the maximum potential gains can be obtained by the spatial allocation scenario for the combination of CO2-SO2 emissions trading, and the output growth ratio among power plants varies huge. The establishment of jointed CO2-SO2 emissions trading is usually highly beneficial to achieve the three targets, including the optimal allocation of resources, the increase of potential gains and the reduction of pollutant emissions.

Economic Analysis of Electricity Storage Based on Heat Pumps and Thermal Storage Units in Large-Scale Thermal Power Plants

In this paper the financial viability of a novel storage concept, referred to as ‘integrated pumped-heat-electricity storage’, is assessed for both a coal-fired and a combined cycle (CC) power plant located in Germany, as well as for a concentrated solar power (CSP) plant located in Spain. The rationale of this concept is to use electricity during times of cheap wholesale market prices, e.g. stemming from a high supply of renewable energies, in order to generate thermal energy via a heat pump, since thermal energy can be stored at comparatively low cost. If the electricity demand rises again, the stored thermal energy is used to power a conventional water-steam cycle, thereby reducing the amount of fossil fuels used or enlarging the operating time of a CSP plant. A mixed integer linear program, considering the day-ahead wholesale market electricity prices and remunerations of offering tertiary control power in Germany, is employed to find an approximation of the optimal schedule for the generation in the power plant as well as for the purchase and the sale of electricity. The financial viability is assessed using net present value (NPV) and real options analysis. Storing electricity to profit from temporal arbitrage is found to be unprofitable, since the (conservatively estimated) costs of thermal storage units are still too high. The largest part of the revenues stems from the remunerations of offering tertiary control power. Therefore, while the utilization of heat pumps, which are estimated to have rather high costs, is not profitable, employing electric heaters without storage units is found to be economically viable for a coal-fired and a CC power plant in Germany. Here, NPV and real options analysis yield the same result, i.e. to invest immediately in such an application. In Spain, offering tertiary control power is presently not remunerated, but only the call-offs of tertiary control energy, which are not considered in the mixed integer linear program. Consequently, employing electric heaters in CSP plants in Spain is found to be not financially viable either.

Main causes of long-standing alarms and their removal by dynamic state-based alarm systems

Long-standing alarms are those in the alarm state continuously for a long period of time. Some long-standing alarms belong to nuisance alarms, playing a detrimental role to the performance of industrial alarm systems, and hence they should be removed. The paper analyzes the main causes leading to long-standing alarms as nuisance ones; industrial examples from a large-scale thermal power plant are provided as supportive evidences of the main causes. A dynamic state-based alarm system is designed to remove long-standing alarms caused by the inconsistency between the alarm design and discrete-valued operating states. The design is based on two rules formulated to select state variables and a novel alarm generation mechanism to generate state-based alarm variables. Industrial case studies illustrate the effectiveness of the dynamic state-based alarm system in significantly reducing the severity of long-standing alarms.

An Overview of Industrial Alarm Systems: Main Causes for Alarm Overloading, Research Status, and Open Problems

Alarm systems play critically important roles for the safe and efficient operation of modern industrial plants. However, most existing industrial alarm systems suffer from poor performance, noticeably having too many alarms to be handled by operators in control rooms. Such alarm overloading is extremely detrimental to the important role played by alarm systems. This paper provides an overview of industrial alarm systems. Four main causes are identified as the culprits for alarm overloading, namely, chattering alarms due to noise and disturbance, alarm variables incorrectly configured, alarm design isolated from related variables, and abnormality propagation owing to physical connections. Industrial examples from a large-scale thermal power plant are provided as supportive evidences. The current research status for industrial alarm systems is summarized by focusing on existing studies related to these main causes. Eight fundamental research problems to be solved are formulated for the complete lifecycle of alarm variables including alarm configuration, alarm design, and alarm removal.

Study on Transient Stability Simulation of District Grid Containing High Proportion of Wind Power

As wind is random, intermittent and instability, with continual installation of wind farms, the impact of large scale wind farm on power system has become an important issue for integration and operation of wind farm. Aiming at studying the transient stability of district grid containing high proportion of wind power, numerical simulations with BPA for an actual district grid of China Southern Power Grid are presented. In these simulations, the interaction between the large-scale wind farm and traditional thermal power plants (TPPs) is investigated taking the different operating modes and fault location into account. The critical clearing time (CCT) is adopted as the measurable indicator to assess the interaction.