Generation Plants Research Articles

A data-driven regression model for predicting thermal plant performance under load fluctuations

The global energy demand is still primarily reliant on fossil-fueled thermal power plants. With the growing share of renewables, these plants must frequently adjust their loads. Maintaining, or ideally increasing operational efficiency under these conditions is crucial. Increasing the efficiency of such systems directly reduces associated greenhouse gas emissions, but it requires sophisticated models and monitoring systems. Data-driven models have proven their value here, as they can be used for monitoring, operational state estimation, and prediction. However, they are also sensitive to (1) the training approach, (2) the selected feature set, (3) and the algorithm used. Using operational data, we comprehensively investigate these model parameters for performance prediction in a thermal plant for process steam generation. Specifically, four regression algorithms are evaluated for the prediction of the highly fluctuating live steam flow with two training approaches and three feature subsets of the raw dataset. Furthermore, manual and automatic clustering methods are used to identify different states of operation regarding the fuel amounts used in the combustion chamber. Our results show that the live steam flow is predicted with excellent accuracy for a testing period of one month (R2=0.994 and NMAE=0.55%) when using a dynamic training approach and a comprehensive feature set comprised of 48 features representing the combustion process. It is also seen that the statically trained model predicts various load changes with strong accuracy and that the accuracy of the dynamically trained model can be approached by incorporating the cluster information into the static model. These models reflect the plant’s physical intricacies under varying loads, where deviations from the predicted live steam flow indicate unwanted long-term drifts. They can be directly implemented to help operators detect inefficiencies and optimize plant performance.

Regional Operation of Electricity-Hythane Integrated Energy System Considering Coupled Energy and Carbon Trading

The deepening implementation of the energy and carbon market imposes trading requirements on multiple regional integrated energy system participants, including power generation plants, industrial users, and carbon capture, utilization, and storage (CCUS) facilities. Their diverse roles in different markets strengthen the interconnections among these subsystems. On the other hand, the operation of CCUS, containing carbon capture (CS), power-to-hydrogen (P2H), and power-to-gas (P2G), results in the coupling of regional carbon reduction costs with the operation of electricity and hythane networks. In this paper, we propose a regional economic dispatching model of an integrated energy system. The markets are organized in a centralized form, and their clearing conditions are considered. CCUS is designed to inject hydrogen or natural gas into hythane networks, operating more flexibly. A generalized Nash game is applied to analyze the multiple trading equilibria of different entities. Simulations are carried out to derive a different market equilibrium regarding network scales, seasonal load shifts, and the ownership of CCUS. Simulation results in a 39-bus/20-node coupled network indicate that the regional average carbon prices fluctuate from ¥1078.82 to ¥1519.03, and the organization of independent CCUS is more preferred under the proposed market structure.

Design and simulation of a photovoltaic plant for maximum use of the solar resource in the Toluviejo municipality of Colombia

Currently, there are various technologies for constructing photovoltaic plants including monofacial and bifacial photovoltaic panels, centralized and string-type inverters, and fixed mounting structures with light followers, to build electrical energy generation systems. This work reviewed the advantages and disadvantages between these technologies, and the implementation of a photovoltaic plant in Toluviejo, Colombia was proposed. To justify and confirm the design, simulations were carried out with the PVsyst software, resulting in the bifacial panels, centralized inverters, and structures with light followers, the most effective solution, and with the highest production for the proposed photovoltaic power generation plant.

Optimizing building energy efficiency with a combined cooling, heating, and power (CCHP) system driven by boiler waste heat recovery

In light of increasing challenges related to fossil fuel consumption, global warming, and rising energy costs, optimizing energy systems has become essential. This study introduces a multi-purpose system designed to capture and utilize waste heat from boiler flue gases at the Tous power plant for simultaneous power generation, cooling, and heating. The system integrates an Organic Rankine Cycle (ORC) for power generation and an Absorption Refrigeration Cycle (ARC) for cooling, with the added function of recovering waste heat to preheat natural gas for the boiler and power plant. The system's performance was rigorously analyzed through energy, exergy, and exergoeconomic assessments. To determine the optimal operating conditions, a multi-objective optimization was conducted using the TOPSIS technique, focusing on critical parameters such as flue gas exit temperature, natural gas inlet temperature, and turbine inlet pressures. The results identified optimal conditions with a flue gas exit temperature of 532.5 K, a natural gas inlet temperature of 285 K, and turbine inlet pressures of 2.54 MPa and 14.62 MPa for the first and second turbines, respectively. Under these conditions, the system achieved an exergy efficiency of 41.1 %, cooling capacity of 133.1 kW, power generation of 210.4 kW, heat transfer to natural gas of 979.6 kW, and operational costs of 8.53 $/h. This study highlights the potential of the proposed system to significantly enhance energy efficiency and reduce operational costs in practical applications, offering a sustainable solution for energy management.

Considering Embodied Greenhouse Emissions of Nuclear and Renewable Power Plants for Electrolytic Hydrogen and Its Use for Synthetic Ammonia, Methanol, Fischer-Tropsch Fuel Production.

Recent concerns surrounding climate change and the contribution of fossil fuels to greenhouse gas (GHG) emissions have sparked interest and advancements in renewable energy sources including wind, solar, and hydroelectricity. These energy sources, often referred to as "clean energy", generate no operational onsite GHG emissions. They also offer the potential for clean hydrogen production through water electrolysis, presenting a viable solution to create an environmentally friendly alternative energy carrier with the potential to decarbonize industrial processes reliant on hydrogen. To conduct a full life cycle analysis, it is crucial to account for the embodied emissions associated with renewable and nuclear power generation plants as they can significantly impact the GHG emissions linked to hydrogen production and its derived products. In this work, we conducted a comprehensive analysis of the embodied emissions associated with solar photovoltaic (PV), wind, hydro, and nuclear electricity. We investigated the implications of including plant-embodied emissions in the overall emission estimates of electrolysis hydrogen production and subsequently on the production of synthetic ammonia, methanol, and Fischer-Tropsch (FT) fuels. Results show that average embodied GHG emissions of solar PV, wind, hydro, and nuclear electricity generation in the United States (U.S.) were estimated to be 37, 9.8, 7.2, and 0.3 g CO2 e/kWh, respectively. Life cycle GHG emissions of electrolytic hydrogen produced from solar PV, wind, and hydroelectricity were estimated as 2.1, 0.6, and 0.4 kg of CO2 e/kg of H2, respectively, in contrast to the zero-emissions often used when the embodied emissions in their construction were excluded. Average life cycle emission estimates (CO2 e/kg) of synthetic ammonia, methanol, and FT-fuel from solar PV electricity are increased by 5.5, 16, and 49 times, respectively, compared to the case when embodied emissions are excluded. This change also depends on the local irradiance for solar power, which can result in a further increase of GHG emissions by 35-41% in areas of low irradiance or reduce GHG emissions by 21-25% in areas with higher irradiance.

Design, multi-aspect investigation and economic advantages of an innovative CCHP system using geothermal energy, CO2 recovery using a cryogenic process, and methanation process with zero CO2 footprint

The significance of devoting attention to environmental pollution control strategies is widely recognized as an effective means of mitigating the harmful environmental effects caused by fossil fuels in industrial and power plant sectors. Carbon dioxide (CO2) capture and recovery technologies have opened up the possibility of utilizing this pollutant gas. Hence, the current study suggests a methodology for the CO2 hydrogenation of the flue gas leaving a power plant. This approach facilitates methane generation via a methanation reactor, subsequently is utilized as fuel for a power plant. For this purpose, a cryogenic method using liquefied natural gas cold energy facilitates CO2 recovery. Moreover, the whole system utilizes geothermal energy to launch a power plant for power generation and supply the power demands of a hydrogen production unit, relying on a water electrolysis process. The hydrogen generated is employed for CO2 hydrogenation, while the oxygen produced is utilized for the combustion reaction. Heating provider units and an absorption chiller are also included in the design. The system is modeled utilizing Aspen HYSYS software. This study incorporates a sensitivity analysis alongside energy, exergy, environmental, and economic assessments. The energy and exergy efficiencies, as determined by the thermodynamic analysis, are 30.87% and 48.61%, respectively. Additionally, according to the economic study, the levelized energy cost amounts to 16.65 $/MWh, demonstrating a substantial reduction of 87.6% compared to the power generation mode. One notable merit of the suggested system lies in its zero CO2 footprint framework, showing a noteworthy supremacy when compared with previous studies.

Use of satellite data to determine the cloud optical depths present during overirradiance conditions

Abstract Overirradiance conditions can negatively impact the operation of photovoltaic systems if no protective measures have been implemented, leading to potential damages and economic losses in photovoltaic generation plants. Current simulation models attempt to understand the mechanism of overirradiance conditions. However, their observations still differ significantly from experimental ones, emphasizing the need to better understand the two main hypotheses that account for overirradiance events: reflection at the edges of thick clouds and Mie scattering in thin clouds. This paper studies the qualitative correlation between the global tilted irradiance measured by a spectroradiometer on the surface and the optical depth of the clouds measured by the GOES-16 satellite to shed more light on this phenomenon. Our results show a good qualitative correlation between the global tilted irradiance and the optical depth of the clouds present during overirradiance events. We also show that all overirradiance conditions occurred when thick clouds were present. These results indicate that the overirradiance events analyzed have been produced predominantly by reflections at the edges of thick clouds, supporting the hypothesis that the increase in global irradiance is mainly due to a substantial increase in direct irradiance.

Research of salt tolerance of genetically modified wheat plants with an additional copy of the ornithine-Δ-aminotransferase gene

Aim. To investigate the level of resistance to salt stress of T3 and T4 seed generation plants of genetically modified wheat (Triticum aestivum L.) with an additional copy of the ornithine-δ-aminotransferase (oat) gene and their original genotypes. Methods. Determination of the content of free L-proline (Pro) and physiological and morphometric parameters. Results. The level of Pro was studied and the morphometric and growth parameters of the offspring of transgenic plants and their original forms under normal / stress conditions were analyzed. Conclusions. T3 and T4 wheat plants under salinity conditions had a higher percentage and higher rate of seed germination compared to the original genotypes. During in vitro cultivation of seedlings, a stress state was observed at doses of 250 and 300 mM NaCl, at which the percentage of survival of transgenic variants was 83.3, non-transgenic only 33.3. Under conditions of in vivo salt stress, T3 and T4 plants had taller shoots and longer roots compared to the original forms. The survival rate of genetically modified plants was ~ 90 %, non-transgenic plants about 60 %. There was no significant difference in the accumulation of free L-proline between the investigated plant variants. It increased in transgenic seedlings on the 21st day of stress under conditions of artificially simulated salinity.

Impact of Soybean Biodiesel Blends with Mixed Graphene Nanoparticles on Compression Ignition Engine Performance and Emission: An Experimental and ANN Analysis

The extensive use of fuels in power generation plants, industries, and transportation has led to a scarcity of fossil fuels and has contributed to global warming. This has prompted researchers to focus on improving internal combustion engine performance, as the transportation system accounts for 50% of global fuel consumption. Soybean biodiesel plays a vital role in reducing emissions and fuel consumption in engines. In the current work, a blend of soybean oil is used as a biodiesel (B20, B40, and B60), with and without the addition of graphene nanoplatelets (GNPs) examined on a constant-speed compression ignition (CI) engine with respect to pure diesel. The blends are denoted as B20GNP10, B20GNP20, B20GNP40, B20GNP60, B20GNP80, and B20GNP100, according to their proposition of biodiesel and graphene nanoplatelets. Similar blends were prepared for B40 and B60 combinations with similar GNPs concentrations. The prepared blend properties were measured, and good thermophysical properties were found. The trial includes testing the engine emissions and performance at altering loads ranging from 0 to 12 kg for all blends. The artificial neural network (ANN) tool is used to forecast the accuracy of experimental results. Compared to pure diesel, the B60GNP100 blend at 12 kg load condition showed the lowest brake specific fuel consumption at 12.58 % and the highest brake thermal efficiency at 27.13%. Emissions were estimated using a gas analyzer, and the outcomes indicated that the biodiesel blends have controlled levels of CO, CO2, NOx, and HC compared to pure diesel. The ANN model with 99.99% accuracy was developed using experimental data, confirming the accuracy of the experimental results with lower simulation time and cost. Additionally, the B60GNP100 blend yielded better results compared to previous studies.

Simultaneous costs minimizing in electricity and gas micro-grids with the presence of distributed generation

Distributed generation can actively participate in the day-ahead markets, real-time power balance, and wholesale gas markets to achieve various goals, such as supplying gas to various electric power generation plants. A multi-objective network with two types of loads is considered in this paper. The reason for the simultaneous optimization of these two networks is that these two energy carriers are dependent on each other and gas is needed to produce electricity, so this issue can be addressed with a multi-objective function. The simulation carried out in this article is coded in GAMS software as a mixed integer linear programming (MILP). The efficiency of gas turbines and fuel cells in this article is dependent on their working point, and considering the exact model of these resources and the relationships related to the calculation of their fuel consumption is non-linear. On the other hand, a binary variable has been used to show the charging and discharging state of the storage and the on-and-off state of the gas turbines. Therefore, the problem considered in this article is a MILP problem. The results of this article are the proper planning of charging and discharging of the energy storage system with the proper planning of the power generation of different energy sources considering the network loads in two optimized and non-optimized scenarios.

Characterization of Humic Acid Salts and Their Use for CO2 Reduction

The European Union aims to be climate neutral by 2050. To achieve this ambitious goal, net greenhouse gas emissions must be reduced by at least 55% by 2030. Post-combustion CO2 capture methods are essential to reduce CO2 emissions from the chemical industry, power generation, and cement plants. To reduce CO2, it must be captured and then stored underground or converted into other valuable products. Apromising alternative for CO2 reduction is the use of humic acid salts (HASs). This work describes a process for the preparation of potassium (HmK) and ammonium (HmA) humic acid salts from oxidized lignite (leonardite). A detailed characterization of the obtained HASs was conducted, including elemental, granulometric, and thermogravimetric analyses, as well as 1H-NMR and IR spectroscopy. Moreover, the CO2 absorption capacity and absorption rate of HASs were experimentally investigated. The results showed that the absorption capacity of the HASs was up to 10.9 g CO2 per kg. The CO2 absorption rate of 30% HmA solution was found to be similar to that of 30% MEA. Additionally, HmA solution demonstrated better efficiency in CO2 absorption than HmK. One of the issues observed during the CO2 absorption was foaming of the solutions, which was more noticeable with HmK.

Features of planning and managing power flows in distribution grids of megalopolises

The study examines the root causes of disruptions of normal operation of power distribution grids in large cities and metropolitan areas. The existing principles of scheduling and maintaining power flows in power distribution grids as well as ways of ensuring the reliability of their operation are analyzed. The integration of fuel-fired distributed generation facilities and renewable generation plants into distribution networks is shown to affect the ability to ensure transient stability during emergency disturbances. We establish evaluation criteria and provide upward margin values to determine the feasibility of the planned power flows. The study reveals general patterns in the calculation of the upward margin for power distribution grids of large cities and metropolitan areas. Test power flow analysis is performed for a real-world segment of a metropolitan area power distribution grid to identify possible overloads of power grid equipment and develop and implement a list of measures for the power flow to achieve the feasible region. The developed approach makes it possible to minimize load shedding or rule out load shedding altogether, ensuring reliable power supply to consumers in large cities and metropolitan areas in the event of an unexpected load growth.

Financial Viability of Thermal Power Generation Plants in the Transition to Renewable Energy

The energy transition will occur due to the natural decline in profitability of thermal power generation assets, and their place in the energy matrix will be taken over by renewable energies. Ensuring electric supply security, a cornerstone of the energy trilemma, is a priority for both developed and developing countries. Nations heavily reliant on hydrological resources employ thermal energy as a backup, making the exploration of financial feasibility for such projects pertinent. This study introduces an economic valuation model for a dispatchable thermal power generation plant in the Colombian market. Associated uncertainty is assessed based on revenue from market sales, bilateral contracts, and firm power remuneration – elements constituting the cash flow and converging into profitability and risk analysis. These are calculated through the Monte Carlo simulation methodology. Additionally, a sensitivity analysis is conducted, accounting for variables such as the "Reliability Payment" settlement price, capacity factor, and costs linked to coal supply. The results emphasize the need for firm power remuneration as a crucial incentive for the success of such projects. Furthermore, the criticality of dispatch level in relation to profitability is verified. Finally, the impact of coal taxes and supply negotiations on financial feasibility is assessed.

Traditionally used medicinal plants for human ailments and their threats in Guraferda District, Benchi-Sheko zone, Southwest Ethiopia

BackgroundThe field of traditional medicine encompasses a wide range of knowledge, skills, and practices that are deeply rooted in the theories, beliefs, and experiences of different cultures. The research aimed to identify traditional medicinal plants used in Guraferda District and assess the threats they face.MethodA total of 96 individuals, 80 males and 16 females, were interviewed to gather ethnobotanical data. Statistical tests like independent t tests, ANOVA, correlation, and regression were conducted using R software version 4.3.2 to compare informant groups.ResultThe study found 81 medicinal plant species in the district from 71 genera and 38 families, with Asteraceae and Solanaceae families having the most species. Leaves were the most commonly used plant part for medicine. Significant differences in plant knowledge were observed across genders, age groups, education levels, and experiences. The highest ICF value was for Dermal and Cutaneous ailments, and Cissampelos mucronata A. Rich and Bidens pilosa L. had the highest fidelity levels.ConclusionThe study highlighted the importance of traditional medicinal plants in treating ailments but noted threats like overharvesting, habitat destruction, and climate change. Conservation efforts and sustainable harvesting practices are crucial to ensure the availability of these plants for future generations. Further research is needed to explore their potential for modern medicine and develop sustainable use strategies.

Determining Fault Location in Transmission Lines Using Differential Equation Algorithms

A transmission line, in the context of electrical engineering and power systems, is a high-voltage or high-tension line that is used to transmit electrical power over long distances from power generation sources (such as power plants) to substations, where the electricity is then distributed to homes, businesses, and industrial facilities. Transmission lines are the backbone of the electrical grid, serving as the highways for electricity delivery. Their efficient and reliable operation is essential for ensuring that electricity is generated, transmitted, and distributed effectively, meeting the needs of consumers while maintaining grid stability and resilience. Transmission line protection refers to a set of techniques and devices used in electrical power systems to detect and respond to faults or abnormal conditions that can occur in high-voltage transmission lines. These lines are a critical part of the electrical grid and are responsible for transporting electricity over long distances from power generation plants to distribution substations. This paper proposes a different differential equation algorithm to locate faulty section on transmission lines. As seen from performance curves, the proposed protection algorithm is able to distinguish normal and faulty conditions.

Experimental analysis of a pilot plant in Organic Rankine Cycle configuration with regenerator and thermal energy storage (TES-RORC)

Applying thermal energy storage in a Regenerative Organic Rankine Cycle system is a possible combination of energy storage for renewable and waste energy sources. This research presents an experimental analysis of a regenerative organic Rankine cycle pilot plant, incorporating a thermal energy storage chamber based on a phase change materials to obtain thermal inertia in the system. The primary heat source is the residual heat of combustion gases at a temperature of approximately 320 °C coming from a generating set that operates within a thermal power generation plant. The prototype uses a twin-screw expander modified to work as a turbine. Novec 649 was used as the working fluid which is an organic compound. The experimental evaluation of the regenerative organic Rankine cycle with thermal energy storage has been carried out through energy and exergetic efficiency analysis to verify the operation of the pilot plant. Values of 13.2 % were obtained for the exergetic efficiency and 2.67 % for the global efficiency of the cycle, with a maximum expander work of 11.8 kW. It was demonstrated that the thermal energy storage system provides energy in response to the plant's operating inertia for 17.5 min, sufficient time for the gradual shutdown of the plant equipment, maintaining the working power of the regenerative organic Rankine cycle.

Performance analysis of IoT-enabled hydro-photovoltaic power systems considering electrical power mission chains

Synergistically and complementarily managing the operation of hydropower plants and other weather-dependent renewable energy generation plants (e.g., solar energy plants) provides an effective measure to improve the performance efficiency (PE) of renewable energy. However, environmental uncertainty and physical system unavailability pose challenges in assessing the PE of the power generation. This paper proposes an approach to synergistically and complementarily managing the operation of hydro-photovoltaic (HPV) power systems in IoT under uncertain environments and develops a mission chain-based PE model for quantifying the capacity of the fulfilment of a power supply mission to satisfy users’ demand for power. An importance measure-based restoration strategy is then proposed to enhance the PE of an HPV power system (PEPS). The approach is examined by taking a large-scale HPV in China in the case study. The results show that, in winters and in summers, the PEPS is higher than PE of a photovoltaic power system and a hydropower system, respectively, and the PEPS with the importance measure-based restoration strategy is higher than that under the random restoration strategy, respectively. The findings not only lay the foundation for the complementary operation of hybrid renewable energy power systems but also provide a reference for the restoration in case of power cuts.

An Improved Thermal Management of Lithium Based Batteries Employing Genetic Algorithm Optimization

Lithium-based battery systems (LBS) are used in various applications, from the smallest electronic devices to power generation plants. LBS energy storage technology, which can offer high power and high energy density simultaneously, can respond to continuous energy needs and meet sudden power demands. The lifetime of LBSs, which are seen as a high-cost storage technology, depends on many parameters such as usage habits, temperature and charge rate. Since LBSs store energy electrochemically, they are seriously affected by temperature. High-temperature environments increase the thermal stress on the LBS and cause its chemical structure to deteriorate much faster. In addition, the fast charging feature of LBSs, which is presented as an advantage, increases the internal temperature of the cell and negatively affects the battery life. The proposed energy management approach ensures that the ambient temperature affects the charging speed of the battery and that the charging speed is adaptively updated continuously. So, the two parameters that harm battery health absorb each other, and the battery has a longer life. A new differential approach has been created for the proposed energy management system. The total amount of energy that can be withdrawn from the LBS is increased by 14.18% compared to the LBS controlled with the standard energy management system using the genetic algorithm optimized parameters. In this way, the LBS replacement period is extended, providing both cost benefits and environmentally friendly management by LBSs turning into chemical waste later.

Holistic Analysis of the Impact of Power Generation Plants in Mexico during Their Life Cycle

Holistic Analysis of the Impact of Power Generation Plants in Mexico during Their Life Cycle

Energy Performance of Steam Generation Unit with Using Non-Renewable Fossil Fuel Like Imported (Indonesian) Coal at Spectrum Dyes and Chemicals Private Limited, Palsana-Surat

Now a day’s competition to became power fuel nation is increase industrialization and develop various process or methods for Energy sector. Due to increases energy demand with suitable use of Energy is important for any developing nation. The current case study work is an account of Energetic performance of steam generation unit like Boiler in the Spectrum Dyes and Chemicals Private Limited. The capacity of the Boiler for the steam generation 10 T/Hr. (2 Unit) and 6 T/hr. (1 Unit) coal fired boiler supplied by Rajdeep Boiler, Sachin. After completing the whole 1st law analysis of the Boiler plant has been presented The analysis carried out by using first law for a particular steam generation unit. There are useful assumption is required to analysis during calculations which is introduced in these performance calculations. Microsoft Excel is used for computer programs are developed for performance calculation energetic analysis of a steam generation plant. The PIE chart is graphical represent to energy flow in the system and the losses in the various components during normal operating condition have been identified. The analysis shows that the 1st law efficiency of Boiler Plant with solid Imported (Indonesian) coal fired boiler is 81.43%.