System Capacity Factor Research Articles

Part-load analysis and preliminary annual simulation of a constant inventory supercritical CO2 power plant for waste heat recovery in cement industry

The present work investigates the part-load performance of a MW-scale sCO2 power plant designed as waste heat recovery unit for an existing cement plant located in Czech Republic, in the framework of the H2020 funded project CO2OLHEAT. The study first presents the selected power plant configuration and then focuses on the evaluation of its part-load operation due to variation of flue gas mass flow rate and temperature. The range of flue gas conditions at the outlet of the upstream process is retrieved from a preliminary statistical analysis of historical trends obtained through the cement plant monitoring. The numerical model developed for this study aims at providing realistic results thanks to the adoption of turbomachinery performance maps provided by the turbomachinery manufacturer of the project. Moreover, heat exchangers have been modelled through a discretized approach which has been validated against manufacturer data, while piping inventory and pressure losses have been assessed through a preliminary sizing that considers the actual distances to be covered in the cement plant. Performance decay is estimated for the whole range of flue gas conditions, reporting the most significant power cycle parameters, and identifying the main causes of efficiency loss. The part-load analysis is carried out considering a constant CO2 inventory, in order to reduce the system complexity and capital cost and simplify plant operation. Results show that the operation entails minor variation of the compressors operative points in the whole range of operating conditions of the cement plant, avoiding the risk of anti-surge bypass activation. Moreover, the plant is able to work close to the nominal thermodynamic cycle efficiency (20.5 %–23.0 %) for most of the year and benefits from part-load operation in terms of overall performance. In the last part of the work, a preliminary techno-economic analysis of the plant is also presented to highlight the potential advantages of sCO2 technology for waste heat recovery applications. The results of the part-load performance of the plant are combined with the flue gases data obtained from the preliminary statistical analysis and the cement plant historical monitoring. An annual electricity production equal to 13′909.7 MWh is obtained, corresponding to 6560 equivalent hours and a system capacity factor of 74.9 %. The investment cost of each CO2OLHEAT plant component is estimated by means of cost correlations obtained from literature and the non-discounted payback time is computed as a function of the electricity selling price. The results show that, even considering electricity prices before 2022, the payback time of the CO2OLHEAT plant is estimated to be lower than 8 years, justifying the industrial interest in the proposed technology.

A System Predictive Maintenance Framework for Advanced Reactors Using a Data-Driven Digital Twin

Advanced reactor designers are looking to maximize the system capacity factor to make advanced reactors more economically competitive and meet the projected energy demand. To achieve this goal, we propose a Dynamic Operation and Maintenance Optimization (DyOMO) framework to perform system-level predictive maintenance (PdM) using a dynamic Bayesian network and component-specific PdM using deep neural networks. At the system level, DyOMO detects the presence of anomalous phenomena, determines the most influential degradation mode, and estimates the remaining useful life (RUL) distribution for the system. At the component level, DyOMO summarizes the health state of key system components, determines the presence of an anomaly using a feedforward neural network, and predicts component RUL using a Bayesian neural network. To evaluate the overall performance of DyOMO, normal operations of a Pebble-Bed High-Temperature Gas-cooled Reactor (PB-HTGR) were simulated with realistic component degradation for the steam turbine and steam generator. Across the 20 independent reactor life simulations, it was found that maintenance was always performed before any safety limits were violated and before a component failed. Specifically, the system-level PdM suggested maintenance on the steam generator once the steam pressure approached its safety limit, and the component-specific PdM suggested maintenance on the steam turbine once the turbine blade hardness degraded. The results indicate that through the continuous monitoring of the system and individual components, the DyOMO framework improves safety and increases the availability of the reactor when compared to traditional maintenance philosophies.

Integration of Concentrating Solar Power With High Temperature Electrolysis for Hydrogen Production

Hydrogen has been identified as a leading sustainable contender to replace fossil fuels for transportation or electricity generation, and hydrogen generated from renewable sources can be an energy carrier for a carbon-free economy. Several hydrogen production methods are under development or deployment with various technical readiness levels and technoeconomic potentials. This study focuses on integrating concentrating solar thermal power (CSP) with high temperature electrolysis (HTE) using solid oxide electrolysis cells (SOEC). The CSP-HTE integration approach provides the benefits of thermal energy storage for continuous operation, improved capacity, and reduced thermal cycling for improved SOEC life. The CSP-HTE system analysis utilizes a Python-based system modeling program in connection with solar receiver thermal output derived from the NREL System Advisor Model (SAM) software. The system model facilitates component sizing, performance simulation, and evaluation of operation modes on an annual basis for various CSP-HTE configurations including CSP with thermal energy storage (TES). The SOEC operation conditions were simulated to assess component sizing and performance and to derive system capacity factors.

Technical, Economic and Environmental Comparison of Three Different Grid-Connected PV Tracking Systems Power Plant Under Kurdistan Region/Iraq Climate Condition

In this paper, a 1 MW grid-connected PV system was performed and simulated numerically in Zakho city, using hourly meteorological data for three systems; fixed, single-axis, and dual-axis tracking systems for solar module. The analysis of this study is based on technical, economic, and environmental feasibility. The analysis based on the actual 3 PV solar panels using different tracking systems which installed on the roof of the Engineering college of Zakho University. The evaluation findings suggest that PV technology is quite promising in this location, with annual yield factors of (1416 kWh/kW), (1694 kWh/kW), and (1902 kWh/kW) for the three systems, respectively. Furthermore, the proposed system's capacity factors are 16.2 percent, 19.3 percent, and 21.70 percent. The economic growth of a 1MW grid-connected photovoltaic (PV) system adjusted for meeting the daily peak load in Zakho is analyzed and compared based on the cost of electricity (COE), net present value (NPV), payback period (PBP), and the energy payback time (EPBT) for three systems in the present work. The COE for the three proposed systems, fixed, 1st axis, and dual axes solar tracking systems, was 0.0826 USD/kWh, 0.0489 USD/kWh, and 0.0441 USD/kWh, respectively, which indicated the tracking system is economically feasible. The findings indicate a favorable trend, implying that large-scale photovoltaics of dual-axis systems might be a feasible option for addressing future power needs.

Energy, exergy, economic, environmental, advanced exergy and exergoeconomic (extended exergy) analysis of hybrid wind-solar power plant

Aiming to net-zero emissions, hybrid power generation through renewable means has gained substantial attention across the globe. Considering the stochastic nature of renewable energy resources, a comprehensive performance assessment is a must prior to project development. Present work is a novel multidimensional 6E analysis (energy, exergy, economic, environmental, advanced exergy, and exergoeconomic) to evaluate the performance of hybrid wind-solar energy systems. The analysis is performed using long-tern (41 years) high-resolution ERA5 reanalysis resource data and the mathematical modeling by means of MATLAB R2018a computation software. The long-term data facilitates reliable and precise predictions of resource availability, power generation, and system performance during the lifespan of the project. The performance of HWSES in terms of capacity factor and exergy efficiency is computed to be 9.6–35.5% and 4.7–10.4% respectively, whereas the extended exergy efficiency lies in the range of 3.39–5.79%. Hybridizing wind power projects with solar power enhances the overall system capacity factor, exergy efficiency, and extended exergy efficiency by 3.46%, 5.12%, and 2.87% respectively. Hence, the hybridization leads to superior year-round system performance with smaller power fluctuations than the standalone systems. Further, wind, solar and hybrid systems would annually reduce the Specific Emission Reduction of 1128 tone/kW, 1685 tone/kW, and 1407tone/kW respectively. The present research will be helpful to the policy-makers and the project developers in the project feasibility study of hybrid energy systems.

Determination of a Renewable Energy System Capacity Factor Using Machining Learning Algorithms

Across the world, machining learning (ML) algorithms, such as support vector machines (SVR) and artificial neural networks (ANN), are among scientific tools for the fourth industrial revolution, or Industry 4.0, campaign. These algorithms have wide engineering applications, but their potentials in energy management are still evolving. Hence, this study investigates the performance of SVR and ANN algorithms as predictive models for wind turbines capacity factor (CF) estimation. Five independent parameters-wind speed, power density, turbulence intensity, installed capacity, and wind shear - were used as input parameters for this estimation problem. Polynomial, radial basis function (RBF), and linear kernels were used to train an SVR model that estimates CF, while Adams was used to optimize the performance of a backpropagation ANN model. These models’ applicability was evaluated using data sets from eight locations. This study used correlation coefficient used to compared the model performance. The RBF trained SVR model performed better than the other kernels during model training, but the linear kernel trained SVR model performed better than the other kernels during testing model. When these kernels performances were compared with a single hidden layer ANN model, the ANN model results were better than these kernels results.

The Design and Analysis of Large Solar PV Farm Configurations With DC-Connected Battery Systems

Typically, solar inverters curtail or “clip” the available power from the photovoltaic (PV) system when it exceeds the maximum ac capacity. This article discusses a battery system connected to the dc link of an inverter to recuperate this PV energy. Contrary to conventional approaches, which employ two dc–dc converters, one each for the battery and solar PV system, the proposed configuration utilizes a single dc–dc converter capable of simultaneously operating as a charge controller and a maximum power point tracking (MPPT) device. In addition to improving the overall system capacity factor, increasing the conversion efficiencies, and ensuring MPPT stability, the proposed configuration offers a simple solution for adding energy storage to existing PV installations. With this configuration, the excess power that will otherwise be curtailed due to inverter rating limitations is stored in the battery and supplied to the grid during periods of reduced irradiance. Moreover, a systematic methodology for sizing a dc-bus connected battery to minimize total PV energy curtailed was developed using an annual PV generation profile at the Louisville Gas and Electric and Kentucky Utilities E. W. Brown solar facility at Kentucky. The detailed behavior of the proposed system and its power electronics controls and operations were validated with case studies developed in PSCAD/EMTDC software for variable power generation and PV output power smoothing.

Challenges Facing the Implementation of Pico-Hydropower Technologies

840 million people living in rural areas across the world lack access to electricity, creating a large imbalance in the development potential between urban and rural areas. Pico-hydropower offers a cost-effective way of accessing electricity, where the resource exists. This paper discusses and critically examines several challenges that remain in implementing pico-hydropower systems, such as local manufacturing, maintenance and repair of turbines, low-head solutions, dealing with variation in the water flow between seasons, the ability to deal with income generating loads and low system power and capacity factor. The solutions to many of these problems exist; several low head turbine systems are appearing on the market, and new power electronic packages are able to improve the system capacity factor. Some turbines are now being designed for local construction using design for manufacturing rules, so only basic workshop tools and process are required to build turbine systems and components, and enabling turbines to be locally repaired. Through the commercialisation and implementation of these solutions, the proliferation of pico-hydropower systems can take place providing low cost sustainable electricity for remote communities, but this requires a stronger emphasis in social awareness and policy. Three critical enabling factors for the success of pico-hydropower projects are identified through this analysis: understanding the local context, financial sustainability and stakeholder awareness.

An economic ESS design method based on wind system capacity factor for island power grid

Background/Objectives: Energy storage device is being considered in many fields but many system owners do not actively apply this compensation device because of the uncertainty of its criteria.Methods/Statistical analysis: In this paper, an energy capacity calculation method based on the specific capacity factor of a wind farm is introduced. The calculation method has focused on the generated surplus power, which is the difference between the generated and consumed electric power quantities.Findings: The capacity calculating method when integrating wind system has not yet been formulated steadily even though its remarkable supplementation, and previous algorithms are not considered as clear solution for various wind characteristics. In order to calculate the capacity in advance, capacity factor based pre-estimating method has been considered. Including surplus power conditions, the case studies are based on independent power-system for handling realistic environmental option and network information of an island power grid.Improvements/Applications: The surplus power was compensated during simulated conditions. In the real power-system, a minimum load could be existed for short section, and the operation would be performed more appropriately.

Thermodynamic analysis of a solar–enhanced geothermal hybrid power plant using CO2 as working fluid

CO2-based Enhanced Geothermal Systems (EGS) and closed-loop supercritical CO2 Brayton cycles for solar thermal systems are both currently being developed for environmentally-friendly power plant systems. However, the recompressor needed in closed-loop supercritical CO2 Brayton cycles operates at high temperature and pressure with attendant higher manufacture and maintain cost. Here a solar thermal-EGS hybrid system is proposed where the geothermal power plant provides the base-load electrical power while the solar system increases the system capacity factor by generating additional electric power during peak demand hours. The two stand-alone systems and the hybrid system were modeled to predict the system efficiencies. It is found that comparison with the stand-alone CO2-EGS and CO2-solar thermal systems, the hybrid system has equal or even higher efficiency than the efficiency of the sum of two separate systems. Moreover, the operating pressure can be decreased and the recompression compressor can be removed in the hybrid system which reduces costs of the system installation and maintenance.

Linear solvation energy relationships in micellar liquid chromatography and micellar electrokinetic capillary chromatography

Linear solvation energy relationships (LSERs) were used to evaluate and characterize chemical interactions that influence retention behavior in micellar liquid chromatography (MLC) and micellar electrokinetic capillary chromatography (MEKC). High correlations were found between solutes' capacity factors in MLC and in MEKC, as well as binding constants to micelles and their solvatochromic parameters using two anionic surfactants, sodium dodecyl sulfate (SDS) and sodium cholate (SC), and one cationic surfactant, tetradecyltrimethylammonium bromide (C 14TAB). Surprisingly, in the C 14TAB MLC system capacity factor ( k′) vs. solvatochromic parameters gives better correlation than log k′ vs. solvatochromic parameters, which is an opposite behavior to that observed in the SDS MLC system. The capacity factors in the C 14TAB MLC system were characterized using LSERs with and without organic modifiers. It was found that the addition of a small amount of short-chain alcohols (e.g., 7% 2-propanol or 5% butanol) does not significantly change the high correlations between k′ vs. solvatochromic parameters. The changes in the coefficients with the volume fraction of organic solvents were explained by comparing the differences in chemical natures between mobile phase and stationary phase. Stationary phase shows a significant effect on the chemical interactions in MLC through LSER study using a diphenyl column and a C 8 column. LSERs were also used to characterize retention behavior in MEKC. High correlations between the logarithm of solutes' capacity factors and their solvatochromic parameters were observed for a group of 25 uncharged substituted aromatic compounds and polycyclic aromatic hydrocarbons with SDS and SC micelles. It was found that solutes' size and basicity are the two dominant factors that influence the migration behavior in MEKC.

Sulfate determination: Ion chromatography

Publisher Summary This chapter discusses the ion chromatography (IC) used in sulfate determination. The determination of sulfate in complex biological mixtures is severely restricted by the relative insensitivity and nonspecificity of classical chemical methods. IC provides a new technology that is well suited to the assay of biological samples. Ion chromatography is a form of ion-exchange chromatography that incorporates a separator column, a background ion-suppressor column, and various eluents in a novel procedure using conductance as a mode of detection. Sulfate determinations can be carried out using a Dionex Model 2020I IC or equivalent high-performance liquid chromatographic (HPLC) system with a conductivity detector. The separator column should be a Dionex Model HPIC-AS4 or equivalent anion-exchange column. The life expectancy of the separator column can be extended by using a precolumn that contains the same resin as the separator column (Dionex Model HPIC-AG4 or equivalent). All physiological fluids should be centrifuged before making sulfate determinations that use IC. After centrifugation, serum samples are generally diluted 10-fold and urine samples 100-fold with the sodium bicarbonate eluent. To measure the performance of the chromatographic system for determining sulfate in physiological fluids, three parameters—:—column theoretical plate number (N), system capacity factor (K'), and column selectivity (α)—need to be examined to allow determination of the overall system resolution (RS).

Load management for power-system emergencies

A new approach to load management is outlined, having as a major objective, provision for the emergency operation of a power system. This load-management proposal would not inconvenience consumers, yet would be accessible to operators at any time. In an emergency, this immediate load control would greatly enhance the potential for safeguarding the system. This loadmanagement approach extends to individual consumers within distribution networks. Battery installations at selected consumers would back-up portions of the load under local microprocessor control. This control could be provided by a currently available credit and load-management unit (CALMU), which, with its remote interrogation facility, is already cost competitive with conventional metering. The proposal has been conceived as an important component of a systemprotection arrangement which would be capable of countering calamitous disturbances on major power systems. It has also the potential to substantially improve distribution-network security. The stored energy of the battery installations could extend the use of this proposal for normal operations. Not only would it reduce the need for peaking generators and improve the system capacity factor, but it would facilitate the introduction of renewable and alternative generation. Only the normal operational benefits would allow tariff incentives encouraging consumers to meet the capital costs of battery installations.With this policy, the proposal would allow electric utilities, with a modest capital outlay, to significantly raise security levels of their total power grid.

The Effect of Receiver Optical Properties on Solar Thermal Electric Systems

The importance of reducing the thermal emittance of the receiver surface on the cost effective operation of intermediate and high temperature (≥ 400 °C) solar thermal electric power plants is discussed. Computer codes for seven systems (point and line focus) are used to independently determine optimum operating conditions for selective (low emittance) and nonselective receiver surfaces. The detailed computer calculations show excellent agreement with numbers generated from a simplified analytical model indicating that system dynamics are a secondary effect in this sensitivity analysis. This study reveals that improvements in system cost effectiveness of 5 to 10 percent for desert environments can be produced by reducing receiver emittance from 0.95 to 0.3. The system operating temperature is determined not to be a critical parameter and little effect is observed on the system capacity factor.