Conventional Thermal Power Research Articles

A Comparative Shaking Table Study on Inelastic Torsion and Torsional Performance of Conventional Thermal Power Plant Main Building and Thermal Power Plant Main Building with the Buckling-Restrained Braces

A Comparative Shaking Table Study on Inelastic Torsion and Torsional Performance of Conventional Thermal Power Plant Main Building and Thermal Power Plant Main Building with the Buckling-Restrained Braces

Greenhouse gases emission reduction for electric power generation sector by efficient dispatching of thermal plants integrated with renewable systems

This research aims to contribute in developing a mathematical model for the composite probabilistic energy emissions dispatch (CPEED) with renewable energy systems, and it proposes a novel framework, based on an existing astute black widow optimization (ABWO) algorithm. Renewable energy power generation technology has contributed to pollution reduction and sustainable development. Therefore, this research aims to explore the CPEED problem in the context of renewable energy generation systems to enhance the energy and climate benefits of the power systems. Five benchmark test systems, combined with conventional thermal power plants and renewable energy sources such as wind and solar, are considered herein to obtain the optimum solution for cost and pollutant emission by using the ABWO approach. The ascendancy is not limited to environmental impacts, but it also provides the diversification of energy supply and reduction of reliance on imported fuels. As a result, the research findings contribute in lowering the cost of fuel and pollutant emissions, correlated with electricity generation systems, while increasing the renewable energy usage and penetration. Finally, the performance and efficacy of the designed scheme have been fully validated by comprehensive experimental results and statistical analyses.

Dynamic Stability Analysis of Isolated Power System

The islanded mode of operation of an electric power system (EPS) that has generation capabilities provided by conventional thermal power plants, by a pumped-storage power station, or from an interlink with a neighboring electric power system through an HVDC BtB converter is addressed in this paper. The risk for electrical power systems to fall into an islanded mode has recently grown, as it is caused not just by technical reasons but by a geopolitical situation as well. The current strains demand the close consideration of problems related to EPS operation in an islanded mode. This paper considers several. The research covers the following issues. The response of the islanded system to a sudden and spasmodic load change is analyzed in cases when the system deals with the disturbance with internal resources alone and with the help of an HVDC BtB converter’s frequency control functionality. Analysis of the impact of the settings of the HVDC BtB converter on the system’s response to disturbances is presented and the optimal set of parameters found. The impact of the system’s extended inertia on the system’s response is evaluated by using an additional unit of the pumped-storage power station in synchronous condenser mode. Transients in the system when switching a unit operating in synchronous condenser mode on and off are analyzed. The capability of the system to withstand major disturbances, such as disconnection of the pumped-storage power station’s unit operating in a pump mode and disconnection of the HVDC BtB converter in emergency modes, if a situation demands, is researched. The research is carried out by numerical simulations using PSS Sincal Electricity Basic software. Updated operating parameters of the isolated power system and the LCC HVDC BtB converter, as well as frequency control automation provided by ABB, were used in the simulations.

Analysis of a direct vapor generation system using cascade steam-organic Rankine cycle and two-tank oil storage

A direct vapor generation solar power system using cascade steam-organic Rankine cycle and two-stage oil tanks is proposed. It offers a significantly enlarged storage capacity due to the unique discharge operation mode. Synthetic oil Therminol® VP-1 is used as the heat carrier and storage medium. Compared with the direct steam generation system, the steam turbine inlet temperature is elevated from 270 °C to 311 °C. Thermodynamic analysis indicates that the optimal equivalent heat-to-power conversion efficiency (ηeq,opt) is 27.91% when benzene is used as the bottom fluid and the mass of oil is 1000 tonnes. ηeq,opt is raised by 7.72–11.60% for the selected four organic fluids as compared with the direct steam generation type. The temperature drop of oil during discharge can reach about 280 °C. Economic studies demonstrate that the proposed system is more cost-effective. Its equivalent payback period is less than 5 years for a 10 MW system with 2000 tonnes of oil. Further investigation shows that it is also more advantageous than a conventional thermal oil-based indirect solar power system due to the cost reduction in heat storage.

Economic-emission load dispatch for power system operation using enhanced sunflower optimization

Conventional thermal power plant uses limited sources of gas, fuel or coal which contributes to the rise of air pollution. Thus, it is crucial to efficiently use the natural sources and minimize the emissions of greenhouse gases and other pollutants. This paper presents an optimal economic dispatch considering three factors which are cost of generation, loss of power transmission and amount of emission for an efficient operation of power generation. Enhanced sunflower optimization (ESFO) algorithm is applied to determine the solution for three different cases: economic load dispatch, emission load dispatch and economic-emission load dispatch. The optimal solution based on the minimum generation cost and emission is obtained for the IEEE 6-unit test system using MATLAB software

Phase compensation based active disturbance rejection control for high order superheated steam temperature system

With the continuous penetration of renewable energies, the control requirements for conventional thermal power unit superheated steam temperature (SST) systems are gradually increasing, to cope with more frequent and large-scale load changes. As a key parameter in the thermal power generation process, SST directly affects the safe and economic operation of the unit. However, the SST system is a typical high-order, large inertia industrial process, which poses severe difficulties to improve the control performance in practice, especially the disturbance rejection performance. To this end, this paper proposes a phase compensation (PC) based low-order active disturbance rejection control (ADRC) strategy for a class of high-order, large-inertia processes. Firstly, the working principles and control problems of SST system are illustrated, and the SST model is identified based on the open-loop step experiment data. Then, the phase compensation network model is derived in detail by low-frequency approximation. A design shift is presented, PC is adopted to compensate process dynamics and obtain reduced-order plant equivalently, which makes it also accessible to other error-based controllers. For engineering practice, its simple implementation and equivalent plant analysis for PC-ADRC control system are also given. At last, the stability and robustness of the PC-ADRC control system are carefully studied. The PC-ADRC controller parameters are determined according to the ideal dynamics and the trade-off between the performance and robustness. Both analysis and simulations show that the PC can effectively improve the robustness and fast response ability of high-order process control system. The efficacy of the proposed method is verified by simulation results based on the identified model, and a laboratory experiment shows the promise in practical applications.

An Advanced Neuro-Fuzzy Tuned PID Controller for Pitch Control of Horizontal Axis Wind Turbines

Modern power systems comprise a variety of generating systems, including conventional thermal power stations and advanced renewable generating sources, one contender being a wind energy conversion system (WECS). Blade pitch control is an important part of the highly non-linear WECS. Many control strategies have been proposed by researchers around the globe. Current research work focuses on developing a control structure for a non-linear pitch control system using an advanced neuro-fuzzy tuned PID (NF-PID) controller. This approach utilizes the simplicity of a PID controller and the power of a soft computing technique like neuro-fuzzy to handle non-linearity. The model in this study is developed on the MATLAB Simulink platform and the obtained simulation results satisfy the requirements of constant output power even if the wind speed input changes abruptly.

Optimal Power Flow of Renewable-Integrated Power Systems Using a Gaussian Bare-Bones Levy-Flight Firefly Algorithm

This article proposes a Gaussian bare-bones Levy-flight firefly algorithm (GBLFA) and its modified version named MGBLFA for optimizing the various kinds of the different optimal power flow (OPF) problems in the presence of conventional thermal power generators and intermittent renewable energy resources such as solar photovoltaic (PV) and wind power (WE). Several objective functions, including fuel costs, emission, power loss, and voltage deviation, are considered in the OPF problem subject to economic, technical, and safety constraints. Also, the uncertainties of solar irradiance and wind speed are modeled using Weibull, lognormal probability distribution functions, and their influences are considered in the OPF problem. Proper cost functions associated with the power generation of PV and WE units are modeled. A comprehensive analysis of ten cases with various objectives on the IEEE 30-bus test system demonstrates the potential effects of renewable energies on the optimal scheduling of thermal power plants in a cost-emission-effective manner. Numerical results show the superiority of the proposed method over other state-of-the-art algorithms in finding optimal solutions for the OPF problems.

Improving the Concept of High Power Unit Closed-Loop Control for Conventional Thermal Power Plants to Comply with Unit Load Control and Primary Frequency Control Requirements

Improving the Concept of High Power Unit Closed-Loop Control for Conventional Thermal Power Plants to Comply with Unit Load Control and Primary Frequency Control Requirements

Optimization of the hybrid solar power plants comprising photovoltaic and concentrating solar power using the butterfly algorithm

This study optimized grid intermittency and instability resulting from photovoltaic (PV) by adding concentrating solar power (CSP) equipped with thermal energy storage (TES), which can be used to form hybrid solar power for grid dispatching. The PV–CSP were optimized by using a hybrid butterfly algorithm to meet the power generation demands and lowest system operation costs. Based on the optimal output and operating characteristics of hybrid power, the economics of peak-valley and fixed electricity prices were studied and compared. The optimal TES capacity was 6-h electricity generation. Hybrid power with optimal TES capacity could achieve a 4.2% increase for power production and 10.4% decrease for operation cost. The peak-valley price provided a better economic benefit than the fixed electricity price. A reasonable configuration of TES can ensure the flexibility and stability of hybrid plant. Hybrid power contributes to a flexible use of dispatch capabilities by equipped with TES, making PV power completely utilize, especially during the periods of high solar radiation. For power systems, hybrid power can be used to replace partly conventional thermal power to achieve highly economic and environmental benefits.

Integrated Carbon-Capture-Based Low-Carbon Economic Dispatch of Power Systems Based on EEMD-LSTM-SVR Wind Power Forecasting

The optimal utilization of wind power and the application of carbon capture power plants are important measures to achieve a low-carbon power system, but the high-energy consumption of carbon capture power plants and the uncertainty of wind power lead to low-carbon coordination problems during load peaks. To address these problems, firstly, the EEMD-LSTM-SVR algorithm is proposed to forecast wind power in the Belgian grid in order to tackle the uncertainty and strong volatility of wind power. Furthermore, the conventional thermal power plant is transformed into an integrated carbon capture power plant containing split-flow and liquid storage type, and the low-carbon mechanism of the two approaches is adequately discussed to give the low-carbon realization mechanism of the power system. Secondly, the mathematical model of EEMD-LSTM-SVR algorithm and the integrated low-carbon economic dispatch model are constructed. Finally, the simulation is verified in a modified IEEE-39 node system with carbon capture power plant. Compared with conventional thermal power plants, the carbon emissions of integrated carbon capture plants will be reduced by 78.248%; the abandoned wind of split carbon capture plants is reduced by 53.525%; the total cost of wind power for dispatch predicted using the EEMD-LSTM-SVR algorithm will be closer to the actual situation, with a difference of only USD 60. The results demonstrate that the dispatching strategy proposed in this paper can effectively improve the accuracy of wind power prediction and combine with the integrated carbon capture power plant to improve the system wind power absorption capacity and operational efficiency while achieving the goal of low carbon emission.

Comparative analysis of thermal economy of two SOFC-GT-ST triple hybrid power systems with carbon capture and LNG cold energy utilization

This paper studies the coupling of fuel cell power generation technology and conventional thermal power generation technology, constructs the thermodynamic model of combined cycle power generation of fuel cell, gas turbine and steam turbine, and analyzes the thermodynamic performance of the system from the important links such as compressor pressure ratio, steam carbon ratio, fuel utilization, fuel cell operating temperature and gas recirculation. Since natural gas as fuel will emit a lot of greenhouse gases, two new low-carbon power generation systems including composite power system, carbon capture and liquified natural gas cold energy utilization are proposed. In this paper, the post-combustion carbon capture which is more practical and conducive to the safe operation of the system is used. The adsorbents used in the two carbon capture methods are MDEA and CaO respectively. In the MDEA carbon capture process, flash tower and split flow process are added to reduce energy consumption. In the calcium looping carbon capture process, CO2 reflux process is set to optimize the calcination temperature, and two-stage waste heat boilers are set to recover a large amount of waste heat of CO2 and clean flue gas respectively. After that, to further save energy consumption, a method of cascade utilization of liquified natural gas cold energy is proposed. It can not only increase power output, but also provide natural gas at normal temperature and pressure for the system and the outside. The calculation results show that the efficiency of the optimized combined cycle system of fuel cell, gas turbine and steam turbine reaches 70.32%. In terms of energy saving, the system efficiency of MDEA carbon capture process is 1.81% higher than that of calcium looping carbon capture process, and calcium looping carbon capture process has more advantages in economic cost. In addition, the cascade utilization of liquified natural gas cold energy provides additional 410.86 kW, 382.64 kW electric energy and more directly usable natural gas for the two systems. The research results of this paper can provide meaningful guidance for the design of low-carbon and high-efficiency power generation system based on fuel cell.

Approach for the adaptations of a nuclear reactor model towards more flexibility in a context of high insertion of renewable energies

The massive penetration of renewable energy sources (RES) that are variable and not “dispatchable”, may weaken the power system supply-demand balance. Nuclear power plants (NPP) contribute in part to this daily and seasonal balance thanks to the “load-following” mode in France for example, but there are still limits to their use. These limits prevent a nuclear power modulation as efficient and quickly as the conventional thermal power plants. The need in terms of power ramps for nuclear in a constrained power system has been quantified in previous studies. Nuclear may compensate for the removal of thermal power plants, in order to fulfill energetic strategies of CO2 reduction. The possibility that nuclear reactors can achieve power ramps of significant values (>5%Pn/min) is put forward and could make possible to replace the services currently provided by thermal power plants. The objective of the study is then to use these power system requirements as the main input parameter for the modelling of a current simplified nuclear reactor capable of responding to frequency control within a specific hypothesis framework. In this paper, a French 1300 MW pressurized water reactor is modelled. Parametric studies are carried out in order to reveal technical and technological constraints when increasing electric power ramp. The study explores ways of design, which may influence reactor flexibility, such as the neutron parameter, Doppler coefficient, or the thermohydraulic parameter, delay in the primary loop.

Understanding the role of advanced materials for energy infrastructure and transmission

The era of fossil fuels may be coming to an end. Our decades-old reliance on fossil fuels has degraded the environment. As a result, governments are shifting to renewable energy technologies. Renewable resources are considered to be sufficiently plentiful and the costs of producing energy per unit are lower; further economy of scale is making them affordable. The present energy mix consists of conventional thermal power plants that operate on fossil fuels, natural gas and renewable energy infrastructures. However, efficiencies of these energy facilities remain insufficient except for hydroelectricity. The lower performance results in inadequate energy production for huge populations and urbanization; thus, due to such reasons, scientists and researchers have adopted a new approach to deal with the efficiency issue. The new system is based on new techniques and study and development of new advanced materials used in the energy infrastructures. Some materials like graphene have been used for energy harvesting and storage in different energy technologies and facilities. Such materials are being studied and considered for various energy applications like energy storage, energy harvest, etc. To preserve our environment and solve the issues regarding efficiencies and energy storage systems, there is an urgent need to develop new materials to alleviate our efficient energy production and storage problem. This paper explores the various materials which have been introduced in multiple energy technologies as well as other energy-related applications.

Two-stage configuration optimization of a novel standalone renewable integrated energy system coupled with hydrogen refueling

Two-stage optimization framework of a novel hybrid renewable integrated energy system is proposed. Firstly, system topological structure and corresponding behaviors are constructed. In this system, renewable energy and conventional thermal power satisfy electricity, heating and cooling demands of the system, and hydrogen storage subsystem is extended for heavy-load fuel cell vehicle refueling. Next, a multi-objective model is constructed to minimize life-time cost of comprehensive loads (LCCL), energy externality rate (EER), and hydrogen hiatus rate (HHR). As for model solution stage, Kernel functions are applied to create typical day scenarios, which contain uncertain information and profoundly ease computational difficulty. Enhanced particle swarm optimization algorithm based on immune clone concept is applied to search non-inferior solutions. Additionally, preference of decision-makers is expanded in solution selection stage that includes more than objectives in the first stage. In the second stage, best Worst Method and Multi-attributive Border Approximation Area Comparison are applied to determine the optimal alternative that corresponds with subjective preference the best. To validate the model, a case in Datong city, Shanxi province in China is selected to validate the framework. Optimization result shows good performance, with LCCL 2.31 Yuan/kWh, EER 6.66%, and HHR 1.09%. Moreover, scenario analysis shows that 1) preference of decision-makers could dramatically influence the ideal solution; 2) double hydrogen refueling demands could be ensured. 3) solar photovoltaic alone could also support the system in Datong. 4) current carbon trade policy almost does not influence the system.

Transformation of the electricity sector with thermal storage power plants and PV – A first conceptual approach

The paper presents a model algorithm for a global transformation of conventional thermal power plants to thermal storage power plants (TSPP). TSPP are thermal power stations that provide highly flexible and at the same time renewable power. The idea behind such transformation is to conserve the firm capacity of the existing thermal power plant fleet and at the same time substitute the related fuel demand by solar energy. Taking Germany as a reference case, several ranking criteria were applied to existing power stations in order to identify a priority list for such transformation. In order to relate the available solar energy potential to each power plant of this list, a geographic information system was set up in order to quantify and identify suitable land area for potential PV installations nearby the plants. After briefly recapitulating the potential function and impact of TSPP in the German national power supply system, the paper proposes a method of ranking existing thermal power plants and of identifying the required PV potential for their transformation. The preliminary results show the feasibility of such approach, identify several limitations and provide first ideas for further development.

Slurryability and flowability of coal water slurry: Effect of particle size distribution

As a part of clean coal technology, the coal water slurry has a popular application in the conventional and new thermal power stations. The hydrotransport is now-a-days a preferred method, due to its low specific energy consumption and non-polluting nature. The lignites and high ash coals, available in abundance, show poor slurryability, thereby making the process unsustainable. This study proposes and demonstrates how a careful selection particle size distribution can help in the improvement of the slurry stability, rheology and flow characteristics. To achieve this objective, 3 different size ranges of pre-pulverized coal are considered and blended to get a total of 8 blended samples. The influx concentration of a given sample ranges in 10–60%. The influx velocity of mixture lies in the range of 0.25–1.25 m/s, through a pipeline of 100 mm diameter. The parameters viz. Settling characteristics, apparent viscosity, headloss and specific enthalpy consumption are evaluated to choose the best particle size distribution of the coal sample. The 30% fraction of >53 μm and <75 μm particles and 20% fraction of >75 μm and <106 μm are found to be optimum for high stability, low viscosity and specific enthalpy consumption. This study provides a simple solution to enhance the flow characteristics of a high ash Indian coal.

Multiobjective Dynamic Optimization for Optimal Load-Following of Natural Gas Combined Cycle Power Plants under Stress Constraints

With the increasing penetration of intermittent renewable energy sources into the electric grid, there is an associated need for conventional thermal power plants that are designed to operate at base-load conditions to cycle their load rapidly and frequently and operate under low-load conditions. Fast load-following operations lead to plant efficiency loss and the reduction of equipment life. A high-fidelity dynamic model of a natural gas combined cycle power plant, with rigorous equipment level submodels, is developed to capture the plant transient performance and the thermomechanical stress evolution at the high-pressure drum is computed to assess the drum life consumption. Stress evolution is modeled for the location of the edge at the drum/downcomer junction that experiences high circumferential stress amplitude during the fast load-following operation, leading to higher fatigue damage than locations considered under existing design standards. A dynamic optimization problem is solved for optimal load-following operation. Depending on the value of the stress constraint and the desired ramp rate, satisfying the desired stress constraint may be infeasible without relaxing the ramp rate. A multiobjective dynamic optimization problem is solved using a lexicographic approach that minimizes ramp rate relaxation and maximizes efficiency while satisfying stress constraints, avoiding spraying to saturation, and maintaining main steam and reheat steam temperature within bounds. It was observed that the optimal ramp rate can be highly nonlinear as opposed to the industry-standard linear ramp rate. Nonlinear optimal ramp-rate profiles not only help to avoid stress constraints that may be unavoidable by using the linear profile but also result in higher efficiency than the linear profile. The study shows that there is a strong tradeoff between the relaxation in the plant ramp rate and the time-average thermal efficiency.

Техніко-економічні показники технологій теплової енергетики, що експлуатуються в маневрених режимах

There is a deficit in united energy system of Ukraine of installed capacity of flexible generation units which are able to quickly reach the operating mode, change the power generation levels in a wide range. To model additional measures increasing the flexibility of the power system, it is necessary to know the technical and economic indicators of thermal power technologies and its specific operating modes. The purpose of the article is to determine: efficiency factors depending on the power unit load; start-up costs depending on downtime duration and different fuel prices; the influence of maneuvering modes on lifetime resource indicators; as well as comparison of indicators for various technologies of thermal energy. The following thermal power technologies: natural gas, hard or bituminous coal fired steam turbine supercritical pressure, steam-gas, gas turbine open cycle and gas piston engines. The calculation formulas allowing estimate the influence of the power plant operation mode on the efficiency is obtained. The results of calculation of the start-up specific costs depending from the type of the unit and the idle time is presented. The different values of thermal power unit start-up cost are presented depending on idle time. As an example, the balancing of 660 MW electric power with different equipment composition are considered. The analysis of the results shows that the highest start-up cost is for coal-fired steam turbine plants, and the composition of the equipment with the lowest start-up cost varies depending on the downtime: up to 2 hours, 2 – 5 hours, more than 5 hours. Formulas for recalculating the cost of starting at different fuel prices are obtained. The influence of maneuvering modes on the lifetime resource indicators of thermal power plants is also presented. The conventional thermal power generators of the united energy system of Ukraine have actually overcome their physical capabilities to ensure effective load following, therefore, it is necessary to introduce new highly flexible capacities, and the proposed formulas and results could be helpful to determine the volumes and characteristics of new thermal power plants needed to implement into power system. Keywords: thermal power, maneuverable mode, efficiency, downtime, start-up cost, service life

Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems: An Uncertainty Handling Perspective

Due to growing concerns regarding climate change and environmental protection, smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy. Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties. The burgeoning era of machine learning (ML) and data-driven control (DDC) techniques promises an improved alternative to these outdated methods. This paper reviews typical applications of ML and DDC at the level of monitoring, control, optimization, and fault detection of power generation systems, with a particular focus on uncovering how these methods can function in evaluating, counteracting, or withstanding the effects of the associated uncertainties. A holistic view is provided on the control techniques of smart power generation, from the regulation level to the planning level. The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility, maneuverability, flexibility, profitability, and safety (abbreviated as the “5-TYs”), respectively. Finally, an outlook on future research and applications is presented.