Combined Cycle Research Articles

Investigation of Combine Cycle Power Plants with Low-Grade Heat Utilization Working Methane-Hydrogen Mixtures

The Russian energy sector remains heavily reliant on thermal power plants, with gas generation accounting for approximately 66% of the installed capacity. However, the industry faces challenges such as depletion of reserves, rising prices for hydrocarbons, and increasing concentrations of carbon dioxide in the atmosphere. This study focuses on developing new scientific and technical solutions to increase the efficiency and environmental safety of combined cycle power units. The research involves structural and parametric optimization of trinary cycle power plants operating on a methane-hydrogen mixture, as well as the development and optimization of turbine and heat exchange equipment for low-temperature power plants. The results show that the transition to trinary CCGT (Combine Cycle Gas Turbine) units with deep utilization and the use of hydrogen fuel can significantly reduce specific CO2 emissions and increase energy efficiency up to 0.21% with also increases in capacity of turbine of approximately 17 MW. The aim of this research is to calculate the efficiency, cost effectiveness and environmental-friendly solution for power generation using mixture of hydrogen- methane as fuel in combine cycle power plant that includes ORC. Additionally, the efficiency of the organic Rankine Cycle (ORC) benefits from the increased moisture, with capacity improvements of 1-2 MW observed when the hydrogen proportion rises from 25% to 50%. Moreover, the potential for zero emissions, coupled with significant increases in power output and efficiency, underscores hydrogen's role as a pivotal component in the future of energy production.

Thermodynamic Analysis and Optimization of Power Cycles for Waste Heat Recovery

Improvement of energy efficiency in technological processes at industrial enterprises is one of the key areas of energy saving. Reduction of energy costs required for the production of energy-intensive products can be achieved through the utilization of waste heat produced by high-temperature thermal furnace units. Generation of electric power based on the waste heat using power cycles with working fluids that are not conventional for large power engineering, may become a promising energy saving trend. In this paper, thermodynamic analysis and optimization of power cycles for the purposes of waste heat recovery are performed. The efficiency of combining several power cycles was also evaluated. It has been established that the combination of the Brayton recompression cycle on supercritical carbon dioxide with the organic Rankine cycle using R124 allows for greater electrical power than steam-power cycles with three pressure circuits under conditions where the gas temperature is in the range of 300–550 °C and the cooling temperature of is up to 80 °C. Additionally, when cooling gases with a high sulfur and moisture content to 150 °C, the combined cycle has greater electrical power at gas temperatures of 330 °C and above. At enterprises where the coolant has a high content of sulfur compounds or moisture and deep cooling of gases will lead to condensation, for example, at petrochemical and non-ferrous metallurgy enterprises, the use of combined cycles can ensure a utilization efficiency of up to 45%.

Thermodynamic integration in combined fuel and power plants producing low carbon hydrogen and power with CCUS

Demand for low-carbon sources of hydrogen and power is expected to rise dramatically in the coming years. Individually, steam methane reformers (SMRs) and combined cycle gas power plants (CCGTs), when combined with carbon capture utilisation and storage (CCUS), can produce large quantities of on-demand decarbonised hydrogen and power respectively. The ongoing trend towards the development of CCUS clusters means that both processes may operate in close proximity, taking advantage of a common infrastructure for natural gas supply, electricity grid connection and the CO2 transport and storage network. This work improves on a previously described novel integration process, which utilizes flue gas sequential combustion to incorporate the SMR process into the CCGT cycle in a single “combined fuel and power” (CFP) plant, by increasing the level of thermodynamic integration through the merger of the steam cycles and a redesign of the heat recovery system. This increases the 2nd law thermal efficiency by 2.6% points over un-integrated processes and 1.9% points the previous integration design. Using a conventional 35% wt. monoethanolamine (MEA) CO2 capture process designed to achieve two distinct and previously unexplored CO2 capture fractions; 95% gross and, 100% fossil (CO2 generated is equal to the quantity of CO2 captured). The CFP configuration reduces the overall quantity of flue gas to be processed by 36%–37% and increases the average CO2 concentration of the flue gas to be treated from 9.9% to 14.4% (wet). This decreases the absorber packing volume requirements by 41%–56% and decreases the specific reboiler duty by 5.5% from 3.46–3.67 GJ/tCO2 to 3.27–3.46 GJ/tCO2, further increasing the 2nd law thermal efficiency gains to 3.8%–4.4% points over the un-integrated case. A first of a kind techno economic analysis concludes that the improvements present in a CO2 abated CFP plant results in a 15.1%–17.3% and 7.6%–8.0% decrease in capital and operational expenditure respectively for the CO2 capture cases. This translates to an increase in the internal rate of return over the base hurdle rate of 7.5%–7.8%, highlighting the potential for substantial cost reductions presented by the CFP configuration.

Low-grade heat utilization for combined cycle power plants using organic rankine cycle

This paper presents a comprehensive thermodynamic analysis of trinary power plants, focusing on the efficiency of Organic Rankine Cycle (ORC) configurations and regenerative heating methods. Despite advancements in nuclear and renewable energy, fossil fuels still dominate electricity generation, necessitating improved efficiency in existing power plants. The study reveals that low-pressure mixing-type heaters provide higher efficiency compared to surface heaters, with net efficiencies of 0.099%, 0.227%, and 0.425% at deaerator pressures of 0.12, 0.3, and 0.7 MPa, respectively. The analysis highlights the impact of feedwater temperature on the thermal efficiency of steam turbine units (STUs), noting that while optimal feedwater temperatures enhance efficiency, they can reduce STU capacity. The study identifies configurations for regenerative heating that optimize exhaust gas temperatures, facilitating additional electricity production through a low-boiling working fluid in the ORC. The findings indicate that R245fa refrigerant is optimal for ORC without recuperative heater, achieving maximum net power at a feedwater temperature of 115°C. For ORC with a recuperative heater, R236ea is preferred for temperatures between 115°C and 154.5°C, while R245fa is optimal for higher temperatures. The results also demonstrate that trinary power plants with recuperators achieve greater efficiency and net capacity compared to double-circuit systems, with notable improvements in thermal efficiency attributed to effective regeneration schemes. This research underscores the potential for optimizing existing domestic power units to enhance their efficiency and performance without significant financial or technical burden, thereby contributing to more sustainable energy generation.

Prediction of Full-Load Electrical Power Output of Combined Cycle Power Plant Using a Super Learner Ensemble

Prediction of Full-Load Electrical Power Output of Combined Cycle Power Plant Using a Super Learner Ensemble

A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters

This paper introduces a novel hyperparameter optimization framework for regression tasks called the Combined-Sampling Algorithm to Search the Optimized Hyperparameters (CASOH). Our approach enables hyperparameter tuning for deep learning models with two hidden layers and multiple types of hyperparameters, enhancing the model’s capacity to work with complex optimization problems. The primary goal is to improve hyperparameter tuning performance in deep learning models compared to conventional methods such as Bayesian Optimization and Random Search. Furthermore, CASOH is evaluated alongside the state-of-the-art hyperparameter reinforcement learning (Hyp-RL) framework to ensure a comprehensive assessment. The CASOH framework integrates the Metropolis-Hastings algorithm with a uniform random sampling approach, increasing the likelihood of identifying promising hyperparameter configurations. Specifically, we developed a correlation between the objective function and samples, allowing subsequent samples to be strongly correlated with the current sample by applying an acceptance probability in our sampling algorithm. The effectiveness of our proposed method was examined using regression datasets such as Boston Housing, Critical heat flux (CHF), Concrete compressive strength, Combined Cycle Power Plant, Gas Turbine CO, and NOx Emission, as well as an ‘in-house’ dataset of lattice-physics parameters generated from a Monte Carlo code for nuclear fuel assembly simulation. One of the primary goals of this study is to construct an optimized deep-learning model capable of accurately predicting lattice-physics parameters for future applications of machine learning in nuclear reactor analysis. Our results indicate that this framework achieves competitive accuracy compared to conventional random search and Bayesian optimization methods. The most significant enhancement was observed in the lattice-physics dataset, achieving a 56.6% improvement in prediction accuracy, compared to improvements of 53.2% by Hyp-RL, 44.9% by Bayesian optimization, and 38.8% by random search relative to the nominal prediction. While the results are promising, further empirical validation across a broader range of datasets would be helpful to better assess the framework’s suitability for optimizing hyperparameters in complex problems involving high-dimensional parameters, highly non-linear systems, and multi-objective optimization tasks.

Thermo-economic and environmental study of solar hybridization for existing fossil-fueled combined cycle power plants: comparison of two practical approaches

Thermo-economic and environmental study of solar hybridization for existing fossil-fueled combined cycle power plants: comparison of two practical approaches

Comparative Industrial-Scale Life Cycle Assessment of Base Case and Heat Recovery Scenarios for Carbon Capture from Natural Gas Combined Cycle Power Plants Using Aqueous Ammonia

Comparative Industrial-Scale Life Cycle Assessment of Base Case and Heat Recovery Scenarios for Carbon Capture from Natural Gas Combined Cycle Power Plants Using Aqueous Ammonia

EWMA control charts to monitor energy output in combined cycle power plant: a new approach based on RBS profiling

Electric energy production frequently uses combined cycle power plants (CCPPs) to handle peak loads. CCPPs must be continuously monitored for power performance to enhance the electrical output power. The electrical output datasets often show asymmetric behavior; therefore, the Birnbaum-Saunders (BS) distribution is one of the potential models for fitting such datasets. In this study, novel exponentially weighted moving average (EWMA) control charts based on the Reparametrised Birnbaum-Saunders (RBS) regression model are developed. We perform a simulation study to evaluate the effectiveness of derived approaches in terms of run length characteristics. Moreover, a case study on the combined cycle power plant’s (CCPP) electrical energy output is provided to demonstrate further the suitability of the recommended approach for early fault detection in electric power systems.

Benchmarking of liquid air energy storage with and without added firing against batteries and gas-fired power plants

Rapid deployment of variable renewables is broadly viewed as the primary mechanism for reducing the carbon intensity of electricity systems, motivating the development and implementation of technologies such as liquid air energy storage (LAES). This study investigates the thermodynamic performance of LAES and evaluates the improvements attained through natural gas added firing (AF), determining the coefficients of structural bonds to identify design optimization priorities. Subsequently, LAES configurations are benchmarked against mid-scale natural gas combined cycles (NGCC) and batteries through an economic optimization based on electricity price profiles from different European markets for the year 2023. At a CO2 emissions tax of 100 €/ton, results reveal that the LAES-AF concept located in Germany could compete with an NGCC plant if natural gas prices exceed 8.3 €/GJ, while for prices above 9.1 €/GJ batteries (with cost reduction projected to 2030) were the preferred option. In this range, the LAES-AF plant reduced fuel consumption by 24.0–27.2 % relative to the NGCC benchmark, which would reduce emissions when using natural gas or costs when using costlier carbon-neutral fuels. The standalone LAES plant did not prove economically viable in any location, being outperformed by batteries and requiring a CO2 price above 300 €/ton to compete with LAES-AF. As electricity price volatility keeps rising with growing wind and solar market shares, the economic attractiveness of LAES should improve as longer periods of near-zero electricity prices negate its lower round-trip efficiency and capitalize on its lower cost for energy storage. Therefore, further work on the development of innovative LAES cycles is recommended.

Evaluation of the Effect of Natural Gas Enrichment with Hydrogen on Gas Turbine Emissions: Numerical Study Based on Chemical Equilibrium

Decarbonization involves the intensive use of renewable energy to obtain a sustainable energy matrix. Brazil has an electrical matrix strongly anchored in renewable sources, historically in hydraulic energy, and more recently, in solar, photovoltaic, and wind sources. The latter are stochastic and, therefore, have strong restrictions on their insertion into the matrix in a broad and dominant manner. Due to these limitations, excess supply can be used to produce green hydrogen and even methane in a process called methanation (chemical reaction between CO2 and H2). The use of electrical energy from renewable sources for the production of fuels is known in literature as power-to-gas. These fuel vectors (H2 and CH4) can be used directly to generate energy or can be mixed with natural gas to enrich it in terms of energy and potentially reduce emissions. This study evaluates the effect of enriching mixtures of natural gas and hydrogen on CO, CO2, and NOx emissions, considering combustion applications in Gas Turbines. The analyses were numerical and involved the use of a thermodynamic combustion model with chemical equilibrium. The chemical equilibrium model is based on chemical equilibrium constants and assumes that the reactants and products are ideal gases. The volumetric fractions of H2 in the mixture from 0 to 30% and the effect of the combustion pressure were investigated. The pressure was varied according to the application chosen. Gas turbines are part of the combined power cycles, and plants can operate with gas turbines of different pressure ratios according to the model, power, and manufacturer of the Gas Turbine. The analyses focused on medium and large gas turbines, and the chosen pressure range was 12:1 to 24:1.

Centralized Automatic Greasing with Intelligent Notification to Maximize Reliability and Hazardous Waste Reduction in Combined Cycle Power Plant

Abstract Cooling water system on Steam Turbine Generator is affected by sea water cleanliness. Traveling Drum Screen (TDS) is used to filter trash and rubbish from the sea water before entering cooling water system in a Power plant. From 2018 to 2022, the Pinion Gear on the Traveling Drum Screen had been damaged many times with an average of 6 times per year and had potential loss of IDR 2.8 billion. From the inspection results, damage occurred on support bearing due to uneven lubrication entering the bearing housing. The lubrication process was conducted manually and produced hazardous waste. This study aims to analyse how to change the system to become digitally maintain and produce less waste. The systematic methodology and implementation of the new system will be explained on this article. The method of this study can increase the optimization of the greasing system and TDS reliability by 2.43×10−3. It also cuts corrective maintenance out. The application of the changed system impact to minimize manual action work and usage of absorbent pad. The results of this research are reducing contaminated hazardous waste and saving hazardous waste management cost.

The energy management strategy of two-by-one combined cycle gas turbine based on dynamic programming

The complexity and nonlinearity of components in large-scale thermal facilities have resulted in a lack of recognized energy management models, and simple rule-based energy management strategies are still the main approach, which reduces their operating efficiency. In this study, a dynamic programming (DP) method for globally optimal power distribution and operation mode decision for two-by-one combined cycle gas turbine is proposed. First, the energy management model of system is established. Then the drum pressure of the heat recovery steam generator, which indicates the thermal energy storage of the system, is chosen as the state variable, while the control variables are the gas turbine power, turbine power and operation mode. In addition, the system response time is considered to re-evaluated the mode switch command. The simulation results show that the DP optimizes the thermal storage management, which allows the gas turbine to run in the high-efficiency operating range for a longer time. The DP-based strategy saves 6.25%, 5.89%, and 4.92% of fuel at initial drum pressure 8MPa, 9MPa, and 10MPa, respectively, compared to the rule-based strategy. The results of this study can be used as a benchmark to evaluate online energy management strategies in future work.

Assessment of air pollution dispersion during wet season: A case study of Rumaila Combined Cycle Power Plant, Basrah, Iraq

This study presents an assessment of the levels of air pollution emanating from natural gas combustion at the Rumaila Combined Cycle Power Plant (CCPP) in Basrah City by using a Gaussian dispersion model, with results at distance of 100, 500 and 1000 m for the pollutants CO, SO2, NO, and particulate matters (PM). Data on atmospheric stability assessments were taken from meteorological stations in Basrah Governorate that belong to the Iraqi Ministry of Agriculture. The study determined the emission rates from the five stacks of the plant and the wind speed, wind direction at stack height, and Turner-Pasquill stability classes for the wet conditions of 2023/2024. The following are the maximum pollutant concentrations emanating from the stacks: CO was 186 μg.m-3 at 100 m, 6 μg.m-3 at 500 m, and 2.5 μg.m-3 at 1000 m; SO₂ was 0.5 μg.m-3 at 100 m, 0.05 μg.m-3 at 500 m, and 0.01 μg.m-3 at 1000 m; NO was 0.07 μg.m-3 at 500 m and 0.03 μg.m-3 at 1000 m; PM was 11 μg.m-3 at 100 m, 0.4 μg.m-3 at 500 m, and 0.15 μg.m-3 at 1000 m. All of these measurements are well below national ambient air quality standards, which means that the Rumaila power plant is not locally deleterious to the air quality.

Equivalent combined cycle modeling and performance optimization for a three-heat-reservoir thermal Brownian heat transformer with external heat-transfer

Three-heat-reservoir (THR) heat transformers can upgrade temperature gradient of thermal energy, and lots of instructive research has been conducted in the last decades. However, study of THR heat transformer cycle theory in micro systems remains lacking. By employing macro equivalent combined cycle method, this paper builds a finite-time thermodynamic model of THR thermal Brownian heat transformer, which is a combination of a two-reservoir thermal Brownian heat pump driven by a two-reservoir thermal Brownian engine. Expressions of performance parameters are deduced, and operating temperatures and external load ratio are determined by solving heat balance equations. Maximal heating load and corresponding coefficient of performance (COP) are given by modulating external load, heat exchanger inventory allocations and barrier height synchronously, and the optimal thermal conductance allocations and optimal working temperatures are identified. Results indicate that external thermal resistances affect heat flow transmission and the coupling of combined cycle, ultimately shaping the cycle performance. Half of the overall heat exchanger inventory should be arranged in middle heat exchanger under maximal heating load objective. Heating load exhibits an extremum with respect to COP. Equivalent combined cycle modelling is an effective and efficient method for performance optimization of THR thermal Brownian heat transformers with external heat-transfer.

Self-superheated combined flash binary geothermal cycle using transcritical-CO2 power cycle with LNG heat sink as the secondary cycle

Combined flash binary geothermal cycle (CFBGC) is an efficient geothermal energy conversion technology. Natural gas (NG) is a preferred fuel in the current energy scenario. LNG gasification is a needed step for delivering NG among the end users. In the present study, a self-superheated single-flash geothermal steam cycle, a transcritical CO2 power cycle and an LNG gasification unit are integrated into a CFBGC. This study shows that the LNG gasification rate and power output can be increased simultaneously by increasing the steam turbine inlet pressure. At a higher steam turbine inlet pressure, desirable steam quality (i.e., 0.9) at the steam turbine exit is maintained by implementing self superheating of the steam. It is observed that 15°C DSH of steam enables the CFBGC to operate at a steam turbine inlet pressure that substantially enhances the output power without a noticeable increase in levelized electricity cost (LEC). The CFBGC operating at this condition yields 9.97% higher power output compared to that of the CFBGC operating at steam turbine inlet pressure requiring no DSH of steam. As a geothermal-based power plant emits very low CO2, the proposed energy system may emerge as a future sustainable energy option.

Waste heat recovery of a combined internal combustion engine and inverse Brayton cycle for hydrogen and freshwater outputs: 4E optimization and comparison

Waste heat recovery of a combined internal combustion engine and inverse Brayton cycle for hydrogen and freshwater outputs: 4E optimization and comparison

Comprehensive study on waste heat recovery from gas turbine exhaust using combined steam rankine and organic rankine cycles

Waste heat recovery technology has proven to be an effective approach for enhancing energy efficiency, reducing greenhouse gas emissions, and lowering energy costs. This study assesses the performance of different waste heat recovery systems from thermodynamic, exergy destruction, economic, and environmental perspectives. Using the DWSIM software, the study simulated a waste heat recovery cycle powered by a high-temperature heat source (508.99 °C) to maximize recovery power and determine the optimal system configuration, including standalone Organic Rankine Cycle (ORC), standalone Steam Rankine Cycle (SRC), and combined systems like SRC with series ORC (SRC + S-ORC), cascade ORC (SRC + C-ORC), and a combination of both (SRC + S-ORC + C-ORC). Among these configurations, the SRC + S-ORC + C-ORC configuration delivered the best performance, achieving a net power output of 3,532.14 kW and a thermal efficiency of 17.09 %. Economically, it demonstrated strong results with a net present value of €1.478 million, a payback period of 8.01 years, and a benefit-cost ratio of 1.32. This configuration also had the highest environmental impact, reducing CO2 emissions by 12,452.48 metric tons per year, equivalent to annual earnings of approximately €999,933.85 through carbon credits trading. The study also found that the evaporator experienced the most significant exergy destruction, suggesting opportunities for improving the highest exergy destruction area, leading to an increase in overall system efficiency. In conclusion, the SRC + S-ORC + C-ORC configuration offers the most promising combination of thermodynamic, economic, and environmental benefits for waste heat recovery systems.

Achieving zero liquid discharge through water recycle in Muara Karang Combine Cycle Power Plant

Abstract The study evaluates a water recycling program implemented at the Muara Karang Power Plant (MKPP), which plays a crucial role in reducing wastewater and enhancing the operational efficiency of the power plant. Water is an essential resource in power generation, but its quality has been declining over time, impacting plant performance. Regular checks on the boiler water at MKPP reveal that the plant collects around 1-1.4 m3/second, which was traditionally discarded after inspection. However, considering the quality and quantity of this water, the study explores its potential for recycling. Since 2023, approximately 2,741.46 m3 of water has been reused, improving efficiency by 160 m3 per month while reducing wastewater discharge. The program demonstrates that simple yet strategic water management interventions can significantly improve operational efficiency and environmental sustainability in power plants. By recycling boiler water within the system, the plant conserves valuable water resources and lowers pollution levels. This study introduces a pioneering approach to water recycling in power plant by utilizing boiler water that was previously discarded. This innovative approach not only reduces the environmental impact but also sets a new benchmark for sustainable water management in the energy sector, providing a model for other power plants to follow.

Development of a Large-Scale Integrated Solar-Biomass Thermal Facility for Green Production of Useful Outputs

The present paper develops a new multigeneration plant to produce multiple commodities from two combined renewable energy sources, solar thermal and biomass and considers a specific case study administered for the city of Al Lith in the Kingdom of Saudi Arabia. The plant generates power, heating, refrigeration, hydrogen, chlorine, concentrated sodium hydroxide, ammonia, urea, and fresh water, which are commodities at high demand in the area. The energy efficiency is determined to be 53% with an annual generation of over 1036 GWh of power and cogenerated 858 GWh of heating, nearly 23 GWh of refrigeration effect, over 11,300 tons of ammonia, almost 1800 tons of urea, over 113,000 tons of concentrated sodium hydroxide and over 905,000 m3 of fresh water. The exergy contents of heating, refrigeration, power and commodity products represent a total of 45% of the sources, which leads to a multigeneration platform's exergy efficiency. The system includes an integrated biomass gasification combined cycle with a biomass oxy-gasifier. The Aspen Plus simulations of the oxy-gasifier determined that the oxygen-to-biomass weight fraction should be set to 0.15, whereas the steam-to-biomass weight fraction is around 0.1. The exhaust gas recirculation is applied to enhance power generation rate and efficiency. The recirculation ratio of exhaust gas is found to be 0.21 if power generation efficiency is to be maximized and 0.28 if the power generation rate is to be maximized. The fluctuating and intermittent nature of the solar energy resource causes poor economics when this energy is to be captured in isolation or itself only. The current paper demonstrates that the hybridization of solar and biomass energy together with integrated processes for multiproduct generation enhances the overall competitivity of the renewable energy system. To address this aspect, the objective of the paper is to develop and assess a new integrated flowsheet for hybrid renewable resource multigeneration.