Energies

17 pages, 2390 KiB

Open AccessArticle

Effects of Water Mist on the Initial Evolution of Turbulent Premixed Hydrogen/Air Flame Kernels

by Riccardo Concetti, Josef Hasslberger, Nilanjan Chakraborty and Markus Klein

Energies 2024, 17(18), 4632; https://doi.org/10.3390/en17184632 (registering DOI) - 16 Sep 2024

In this study, a series of carrier-phase direct numerical simulations are conducted on spherical expanding premixed hydrogen/air flames with liquid water addition. An Eulerian–Lagrangian approach with two-way coupling is employed to describe the liquid–gas interaction. The impacts of preferential diffusion, the equivalence ratio, [...] Read more.

In this study, a series of carrier-phase direct numerical simulations are conducted on spherical expanding premixed hydrogen/air flames with liquid water addition. An Eulerian–Lagrangian approach with two-way coupling is employed to describe the liquid–gas interaction. The impacts of preferential diffusion, the equivalence ratio, water loading, and the initial diameter of the water droplets are examined and analyzed in terms of flame evolution. It is observed that liquid water has the potential to influence flame propagation characteristics by reducing the total burning rate, flame area, and burning rate per unit area, attributed to flame cooling effects. However, these effects become discernible only under conditions where water evaporation is sufficiently intense. For the conditions investigated, the influence of preferential diffusion on flame evolution is found to be more significant than the interaction with liquid water. The results suggest that due to the slow evaporation rate of water, which is a result of its high latent heat of evaporation, the water droplets do not disturb the initial flame kernel growth significantly. This has implications for water injection concepts in internal combustion engines and for explosion mitigation. Full article

(This article belongs to the Special Issue Towards Climate Neutral Thermochemical Energy Conversion)

18 pages, 306 KiB

Open AccessArticle

Participation of Energy Communities in Electricity Markets and Ancillary Services: An Overview of Successful Strategies

by Emely Cruz-De-Jesús, Alejandro Marano-Marcolini and José Luis Martínez-Ramos

Energies 2024, 17(18), 4631; https://doi.org/10.3390/en17184631 (registering DOI) - 16 Sep 2024

Abstract

Energy communities are a transformative force in the electricity markets and ancillary services, reshaping the energy landscape through collective action. This paper explores the successful strategies adopted by these communities, highlighting real-world cases where they have participated directly in the market, or through [...] Read more.

Energy communities are a transformative force in the electricity markets and ancillary services, reshaping the energy landscape through collective action. This paper explores the successful strategies adopted by these communities, highlighting real-world cases where they have participated directly in the market, or through aggregators, or sold their energy to retailers, which is of paramount importance because it serves as a foundation for those countries that wish to implement these entities as part of their decarbonization plan. It also serves as a model for the development of future citizen initiatives that aim to turn citizens into active users of the electricity system. The paper examines collaborative dynamics within the energy sector, highlighting how these communities optimize resource sharing and contribute to a more resilient and sustainable energy system. The study emphasizes the potential of energy communities in driving innovation and fostering a participatory approach to energy management. The results show that some pilot projects are being developed and several electricity cooperatives, one of the most common forms of energy communities, are participating in energy trading with their members and other entities. More efforts are also needed for energy communities to participate more directly in the market and/or through aggregators. Full article

(This article belongs to the Special Issue Renewable Energy Systems for Energy Communities)

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19 pages, 662 KiB

Open AccessArticle

Comparison of Configurable Modular Two-Level and Three-Level Isolated Bidirectional DC–DC Converters for Super-Capacitor Charging in DC Shore Power Systems

by Wenqiang Xie, Mingming Shi, Yuying He, Chenyu Zhang and Ruihuang Liu

Energies 2024, 17(18), 4630; https://doi.org/10.3390/en17184630 (registering DOI) - 15 Sep 2024

Abstract

Compared to the AC counterpart, the DC shore power system provides a significant advantage of efficient power supply from renewable sources to ships and onshore loads. Super-capacitors serve as key energy storage units in such a system to buffer the power fluctuations and [...] Read more.

Compared to the AC counterpart, the DC shore power system provides a significant advantage of efficient power supply from renewable sources to ships and onshore loads. Super-capacitors serve as key energy storage units in such a system to buffer the power fluctuations and collect the regenerative energy. However, the ultra-wide voltage range of super-capacitors imposes a significant challenge in the topology selection and efficiency optimization of the interfacing isolated bidirectional DC–DC converter. To tackle this challenge, this paper analyzes and compares two promising converter topologies, which are a configurable modular two-level dual-active bridge (CM-2L-DAB) and a three-level dual-active bridge (3L-DAB). To facilitate an ultra-wide voltage range, extended phase-shift (EPS) modulation in conjunction with the topology reconfiguration is analyzed for the CM-2L-DAB, while a hybrid modulation scheme is proposed for the 3L-DAB. A unified design approach is provided for both topologies, which also yields to the power loss modeling. On this basis, the CM-2L-DAB and 3L-DAB are thoroughly compared in terms of the modulation schemes, current stress, soft-switching operation, power conversion efficiency, material usage, closed-loop control scheme, and reliability. A prominent conclusion can be drawn that the CM-2L-DAB provides a higher efficiency than the 3L-DAB over the whole voltage range, but it relies on additional relays to reconfigure its topology which results in lower reliability and dynamic performance than the 3L-DAB. Full article

(This article belongs to the Special Issue Optimization of DC Power Converter and the Applications)

16 pages, 4390 KiB

Open AccessArticle

Wind Farm Prediction of Icing Based on SCADA Data

by Yujie Zhang, Mario Rotea and Nasser Kehtarnavaz

Energies 2024, 17(18), 4629; https://doi.org/10.3390/en17184629 (registering DOI) - 15 Sep 2024

Abstract

In cold climates, ice formation on wind turbines causes power reduction produced by a wind farm. This paper introduces a framework to predict icing at the farm level based on our recently developed Temporal Convolutional Network prediction model for a single turbine using [...] Read more.

In cold climates, ice formation on wind turbines causes power reduction produced by a wind farm. This paper introduces a framework to predict icing at the farm level based on our recently developed Temporal Convolutional Network prediction model for a single turbine using SCADA data.First, a cross-validation study is carried out to evaluate the extent predictors trained on a single turbine of a wind farm can be used to predict icing on the other turbines of a wind farm. This fusion approach combines multiple turbines, thereby providing predictions at the wind farm level. This study shows that such a fusion approach improves prediction accuracy and decreases fluctuations across different prediction horizons when compared with single-turbine prediction. Two approaches are considered to conduct farm-level icing prediction: decision fusion and feature fusion. In decision fusion, icing prediction decisions from individual turbines are combined in a majority voting manner. In feature fusion, features of individual turbines are averaged first before conducting prediction. The results obtained indicate that both the decision fusion and feature fusion approaches generate farm-level icing prediction accuracies that are 7% higher with lower standard deviations or fluctuations across different prediction horizons when compared with predictions for a single turbine. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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18 pages, 2254 KiB

Open AccessArticle

Power Allocation Control Strategy of DC/DC Converters Based on Sliding Mode Control

by Wenwen Li, Jianwei Ji, Henan Dong, Miao He and Shubo Hu

Energies 2024, 17(18), 4628; https://doi.org/10.3390/en17184628 (registering DOI) - 15 Sep 2024

Abstract

In the DC microgrid system, the bidirectional DC/DC converter is one of the most important components; thus, research on its control strategy has attracted widespread attention. Firstly, the single bidirectional DC/DC converter based on a sliding mode (variable structure) control (SMC) strategy exhibits [...] Read more.

In the DC microgrid system, the bidirectional DC/DC converter is one of the most important components; thus, research on its control strategy has attracted widespread attention. Firstly, the single bidirectional DC/DC converter based on a sliding mode (variable structure) control (SMC) strategy exhibits an inherent contradiction between the reaching time and the chattering phenomenon. In order to address this problem, an SMC strategy based on the improved exponential reaching law was designed. This control strategy modifies the constant-speed reaching term and introduces the system state variable to indicate the chattering level, which not only improves the dynamic performance of the bidirectional DC/DC converter but also suppresses the chattering problem. Secondly, the bidirectional DC/DC converter group based on the traditional droop control strategy exhibits an inherent contradiction between load power allocation and bus voltage stabilization. In order to address this problem, an improved droop control strategy that takes the line impedance characteristics into account is proposed. This control strategy modifies the traditional droop control strategy by introducing virtual resistance and uses DC bus voltage information to replace the line impedance value. This ensures the accuracy of power allocation and stability of the DC bus voltage simultaneously. Finally, the stability of each designed strategy is verified individually. The combination of the two control strategies is applied to a group of bidirectional DC/DC converters group to conduct a semi-physical simulation experiment, and the results verify that the proposed control strategies are effective and feasible. Full article

(This article belongs to the Special Issue Emerging Challenges and Solutions in Cyber–Physical Security of Smart Grids)

31 pages, 1948 KiB

Open AccessArticle

Experimental Assessment of a Novel Irradiance Sensorless Intelligent Control Scheme for a Standalone Photovoltaic System under Real Climatic Conditions

by Jialan Sun and Jinwei Fan

Energies 2024, 17(18), 4627; https://doi.org/10.3390/en17184627 (registering DOI) - 15 Sep 2024

Abstract

The efficiency of standalone photovoltaic (PV) systems heavily relies on the effectiveness of their maximum power point tracking (MPPT) controller. This study aims to improve the operational efficiency and reliability of standalone PV systems by introducing a novel control scheme, the Immersion and [...] Read more.

The efficiency of standalone photovoltaic (PV) systems heavily relies on the effectiveness of their maximum power point tracking (MPPT) controller. This study aims to improve the operational efficiency and reliability of standalone PV systems by introducing a novel control scheme, the Immersion and Invariance Neural Network (II-NN). This innovative system integrates a nonlinear estimator of solar irradiance with a neural network (NN) model, eliminating the need for direct irradiance measurements and associated costly sensors. The proposed methodology uses the Immersion and Invariance algorithm to design a nonlinear estimator that leverages the real-time measurements of PV current and voltage to estimate the incident irradiance. The NN then processes this estimated irradiance to determine the MPP voltage accurately. A robust nonlinear controller ensures the PV system operates at the MPP. This approach stands out by managing the nonlinearities, parametric uncertainties, and dynamic variations in PV systems without relying on direct irradiance measurements. The II-NN system was rigorously tested and validated under real climatic conditions, providing a realistic performance assessment. The principal results show that the II-NN system achieves a mean error of 0.0183V and a mean absolute percentage error of 0.3913%, with an overall MPPT efficiency of up to 99.84%. Comparisons with the existing methods, including perturb and observe, incremental conductance, and three other recent algorithms, reveal that the II-NN system outperforms these alternatives. The major conclusion is that the II-NN algorithm significantly enhances the operational efficiency of PV systems while simplifying their implementation, making them more cost-effective and accessible. This study substantially contributes to PV system control by advancing a robust, intelligent, and sensorless MPPT control scheme that maintains high performance even under varying and unpredictable climatic conditions. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

18 pages, 1515 KiB

Open AccessArticle

Energy and Economic Assessment of Oxy-Fuel Combustion CO₂ Capture in Coal-Fired Power Plants

by Yuyang Yuan, Lei Wang, Yaming Zhuang, Ying Wu and Xiaotao Bi

Energies 2024, 17(18), 4626; https://doi.org/10.3390/en17184626 (registering DOI) - 15 Sep 2024

Abstract

Oxy-fuel combustion technology replaces air with a mixture of pure O₂ and recycled flue gas for coal combustion, which leads to difficulties in the waste heat recovery of flue gas in the boiler tail of coal-fired power plants. This paper proposes a [...] Read more.

Oxy-fuel combustion technology replaces air with a mixture of pure O₂ and recycled flue gas for coal combustion, which leads to difficulties in the waste heat recovery of flue gas in the boiler tail of coal-fired power plants. This paper proposes a new integration scheme for waste heat recovery of flue gas in coal-fired power plants with oxy-fuel combustion CO₂ capture. By introducing an oxygen preheater, a recycled flue gas preheater, and a low-pressure economizer, the waste heat of flue gas is fully recovered to preheat oxygen, recycled flue gas, and feed water, respectively. The proposed scheme simultaneously ensures the safe operation of the recycled fan and improves the thermal performance of the coal-fired power plants. Compared to the air combustion configuration, the boiler’s efficiency and gross power efficiency in the oxy-fuel combustion configuration are increased by 0.42% and 1.29%, respectively. Due to power consumption for the added equipment, the net power efficiency is reduced by 10.41%. A techno-economic analysis shows that the cost of electricity for oxy-fuel combustion in coal-fired power plants has increased from USD 46.45/MWh to USD 80.18/MWh, and the cost of the CO₂ avoided reaches USD 43.24/t CO₂. Full article

(This article belongs to the Topic Final Sinks of Carbon Capture, Utilization and Storage (CCUS))

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20 pages, 6683 KiB

Open AccessArticle

A Novel Estimating Algorithm of Critical Driving Parameters for Dual-Motor Electric Drive Tracked Vehicles Based on a Nonlinear Observer and an Adaptive Kalman Filter

by Zhaomeng Chen, Songhua Hu, Haoliang Lv and Yimeng Fu

Energies 2024, 17(18), 4625; https://doi.org/10.3390/en17184625 (registering DOI) - 15 Sep 2024

Abstract

High-speed dual-motor electric drive tracked vehicles (DDTVs) have emerged as a research hotspot in the field of tracked vehicles in recent years due to their advantages in fuel economy and the scalability of electrical equipment. The emergency braking of a DDTV at high [...] Read more.

High-speed dual-motor electric drive tracked vehicles (DDTVs) have emerged as a research hotspot in the field of tracked vehicles in recent years due to their advantages in fuel economy and the scalability of electrical equipment. The emergency braking of a DDTV at high speed can lead to slipping or even yawing (which is caused by a large deviation of forces at each track directly), posing significant challenges to the vehicle’s stability and safety. Therefore, the accurate real-time acquisition of critical driving parameters, such as the longitudinal force and vehicle speed, is crucial for the stability control of a DDTV. This paper developed a novel estimating algorithm of critical driving parameters for DDTVs equipped with conventional sensors such as rotary transformers at PMSMs and onboard accelerometers on the basis of their dynamics models. The algorithm includes a sensor signal preprocessing module, a longitudinal force estimation method based on a nonlinear observer, and a speed estimation method based on an adaptive Kalman filter. Through hardware-in-loop experiments based on a Speedgoat real-time target machine, the proposed algorithm is proven to estimate the longitudinal force of the track and vehicle speed accurately, whether the vehicle has stability control functions or not, providing a foundation for the further development of vehicle stability control algorithms. Full article

(This article belongs to the Topic Advanced Electric Vehicle Technology, 2nd Volume)

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20 pages, 12015 KiB

Open AccessArticle

Probabilistic Assessment of the Impact of Electric Vehicle Fast Charging Stations Integration into MV Distribution Networks Considering Annual and Seasonal Time-Series Data

by Oscar Mauricio Hernández-Gómez and João Paulo Abreu Vieira

Energies 2024, 17(18), 4624; https://doi.org/10.3390/en17184624 (registering DOI) - 15 Sep 2024

Abstract

Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid [...] Read more.

Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid requires considering annual and seasonal variations in EV fast-charging energy consumption. Neglecting these variations can lead to either underestimating or overestimating the impacts of FCSs on the networks. This paper introduces a probabilistic method to assess voltage profile violations, overload capacity, and increased power losses due to FCSs. By incorporating annual and seasonal time-series data, the method accounts for uncertainties related to EV fast charging. Applied to an MV feeder in Brazil, our evaluations highlight the impact of annual power consumption seasonality on EV-grid integration studies. Considering seasonal dependency is crucial for precise impact assessments of MV distribution networks. The proposed method aids utility engineers and planners in quantifying and mitigating the effects of EV fast charging, contributing to more reliable MV grid integration strategies. Full article

(This article belongs to the Special Issue Innovations and Recent Trends in Power Systems: Smart Grids, Energy Storage Systems and Electric Vehicle Integrations)

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16 pages, 4876 KiB

Open AccessArticle

Application of the ALRW-DDPG Algorithm in Offshore Oil–Gas–Water Separation Control

by Xiaoyong He, Han Pang, Boying Liu and Yuqing Chen

Energies 2024, 17(18), 4623; https://doi.org/10.3390/en17184623 (registering DOI) - 14 Sep 2024

Abstract

With the offshore oil–gas fields entering a decline phase, the high-efficiency separation of oil–gas–water mixtures becomes a significant challenge. As essential equipment for separation, the three-phase separators play a key role in offshore oil–gas production. However, level control is critical in the operation [...] Read more.

With the offshore oil–gas fields entering a decline phase, the high-efficiency separation of oil–gas–water mixtures becomes a significant challenge. As essential equipment for separation, the three-phase separators play a key role in offshore oil–gas production. However, level control is critical in the operation of three-phase gravity separators on offshore facilities, as it directly affects the efficacy and safety of the separation process. This paper introduces an advanced deep deterministic policy gradient with the adaptive learning rate weights (ALRW-DDPG) control algorithm, which improves the convergence and stability of the conventional DDPG algorithm. An adaptive learning rate weight function has been meticulously designed, and an ALRW-DDPG algorithm network has been constructed to simulate three-phase separator liquid level control. The effectiveness of the ALRW-DDPG algorithm is subsequently validated through simulation experiments. The results show that the ALRW-DDPG algorithm achieves a 15.38% improvement in convergence rate compared to the traditional DDPG algorithm, and the control error is significantly smaller than that of PID and DDPG algorithms. Full article

(This article belongs to the Special Issue Advances in Ocean Energy Technologies and Applications)

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17 pages, 12363 KiB

Open AccessArticle

Enhanced MPPT in Permanent Magnet Direct-Drive Wind Power Systems via Improved Sliding Mode Control

by Huajun Ran, Linwei Li, Ao Li and Xinquan Wang

Energies 2024, 17(18), 4622; https://doi.org/10.3390/en17184622 (registering DOI) - 14 Sep 2024

Abstract

Addressing the challenges of significant speed overshoot, stability issues, and system oscillations associated with the sliding mode control (SMC) strategy in maximum power point tracking (MPPT) for permanent magnet synchronous wind power systems, this paper introduces a fuzzy sliding mode control (FSMC) method [...] Read more.

Addressing the challenges of significant speed overshoot, stability issues, and system oscillations associated with the sliding mode control (SMC) strategy in maximum power point tracking (MPPT) for permanent magnet synchronous wind power systems, this paper introduces a fuzzy sliding mode control (FSMC) method employing an innovative exponential convergence law. By incorporating a velocity adjustment function into the traditional exponential convergence law, a novel convergence law was designed to mitigate oscillations during the sliding phase and expedite the convergence rate. Additionally, a fuzzy controller was developed to implement a fuzzy adaptive SMC strategy, optimizing the MPPT for permanent magnet synchronous wind power generation systems. Simulation results indicated that this approach offered a faster response and superior interference rejection capabilities, compared to conventional and modified SMC strategies. The improved FSMC strategy demonstrated a swift, dynamic response and excellent steady-state performance, improving the efficiency of MPPT, thus confirming the effectiveness of the proposed method. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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16 pages, 4440 KiB

Open AccessArticle

Comparison of the Energy Contributions of Different Types of Ground Heat Exchangers Related to Cost in a Working Ground Source Heat Pump System

by Christakis Christou, Iosifina I. Stylianou, Lazaros Aresti, Georgios A. Florides and Paul Christodoulides

Energies 2024, 17(18), 4621; https://doi.org/10.3390/en17184621 (registering DOI) - 14 Sep 2024

Abstract

Geothermal systems face adoption challenges due to their high initial investment cost. Accurate cost analyses and a more precise understanding of updated prices could assist geothermal industry projects in obtaining investment financing and better money management with the right equipment. As the cost [...] Read more.

Geothermal systems face adoption challenges due to their high initial investment cost. Accurate cost analyses and a more precise understanding of updated prices could assist geothermal industry projects in obtaining investment financing and better money management with the right equipment. As the cost of geothermal installations can vary widely depending on case and location, it seems essential to clarify the factors and parameters that determine the cost of the system. These include the type of loop system, the ground conditions, the type of heat pump, the system size, and the geographical location. The scope of this study is to compare the operation of various types of ground heat exchangers (GHEs) present in a Ground Source Heat Pump (GSHP) system installed in the coastal area of the Mediterranean climate zone of Cyprus. The highlight of this work is that it presents real installation cost data as well as recorded total energy contributed by the GHEs to the GSHP system of a HP cooling and heating capacities of 101 kW and 117 kW, respectively. The input contribution from the GHEs to the HP is 85,650 kWh (308,340 MJ) in summer and 25,880 kWh (93,168 MJ) in winter. It is shown that, among the three groups of GHEs investigated, the open-well GHE complex has the lowest cost per kWh ratio (0.32 EUR/kWh), followed by the vertical GHE complex (1.05 EUR/kWh), and lastly by the helical coil GHE (2.77 EUR/kWh). This clearly suggests that when underground water is available, the open-well GHE is much more favorable than other GHE types. Full article

(This article belongs to the Section J1: Heat and Mass Transfer)

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17 pages, 2820 KiB

Open AccessArticle

Transient Active Power in Two-Terminal Networks

by Konrad Hawron, Bartosz Rozegnał and Maciej Sułowicz

Energies 2024, 17(18), 4620; https://doi.org/10.3390/en17184620 (registering DOI) - 14 Sep 2024

Abstract

This article presents the hitherto unknown concept of transient active power in two-terminal networks. This phenomenon occurs when current and voltage signals are not sinusoidal but quasi-sinusoidal—in the case of an approximation of transient state. The modification of Parseval’s formula and the power–immittance [...] Read more.

This article presents the hitherto unknown concept of transient active power in two-terminal networks. This phenomenon occurs when current and voltage signals are not sinusoidal but quasi-sinusoidal—in the case of an approximation of transient state. The modification of Parseval’s formula and the power–immittance relations are presented in this paper. To illustrate the phenomenon, a simulation is included for several types of transient states, and their influence on transient active power waveform is shown. The article also contains a comparison of transient active power and classical active power and highlights situations where it is impossible to use classical theory but where transient active power yields measurable results. In the article, an analysis of an idealized case and measurement data obtained from a modeled voltage sag in a laboratory setup is conducted. The impact of disturbance power on the total power in the case of disturbances that may occur in the real power network is demonstrated. Full article

(This article belongs to the Special Issue Thermo-Mechanical and Electrical Measurements for Energy Systems)

17 pages, 5269 KiB

Open AccessArticle

Independent Pitch Adaptive Control of Large Wind Turbines Using State Feedback and Disturbance Accommodating Control

by Yingming Liu, Yi Wang and Xiaodong Wang

Energies 2024, 17(18), 4619; https://doi.org/10.3390/en17184619 (registering DOI) - 14 Sep 2024

Abstract

Wind turbines experience significant unbalanced loads during operation, exacerbated by external disturbances that challenge the stability of the pitch control system and affect output power. This paper proposes an independent pitch adaptive control strategy integrating state feedback and disturbance accommodating control (DAC). Initially, [...] Read more.

Wind turbines experience significant unbalanced loads during operation, exacerbated by external disturbances that challenge the stability of the pitch control system and affect output power. This paper proposes an independent pitch adaptive control strategy integrating state feedback and disturbance accommodating control (DAC). Initially, nonlinear wind turbine dynamics are globally linearized, and DAC is applied to mitigate the impact of wind disturbances dynamically. Subsequently, the entire range of wind speeds is segmented, and controllers are individually designed to optimize gain settings according to specific control objectives at each wind speed interval. Scheduling parameters such as collective pitch angle and tower fore-aft displacement are identified and trained using Radial Basis Function Neural Networks (RBFNN). Finally, based on the output gain values determined by RBFNN, the full-state feedback controller group is adaptively adjusted, and the optimal controller is selected for the final output. Simulations conducted on the NREL 5MW reference wind turbine model using FAST and Simulink demonstrate that compared to the ROSCO controller, the proposed strategy ensures smoother output power and effectively reduces blade and tower loads, thereby extending the turbine’s operational lifespan. Full article

(This article belongs to the Special Issue Wind Generators Modelling and Control: 2nd Edition)

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18 pages, 2627 KiB

Open AccessArticle

Numerical Simulation Study on Rotary Air Preheater Considering the Influences of Steam Soot Blowing

by Youfu Chen, Yaou Wang, Bo Chen, Hongda Zhu and Lingling Zhao

Energies 2024, 17(18), 4618; https://doi.org/10.3390/en17184618 (registering DOI) - 14 Sep 2024

Abstract

The ash deposition is a general problem that needs to be solved effectively for the rotary air preheater of the coal-fired boiler. Taking the rotary air preheater of a 600 MW power station as the object, the mesh model of the flue gas [...] Read more.

The ash deposition is a general problem that needs to be solved effectively for the rotary air preheater of the coal-fired boiler. Taking the rotary air preheater of a 600 MW power station as the object, the mesh model of the flue gas side of the air preheater, considering the influences of steam soot blowing, is established using the Gambit 2.4.6 software. Based on the SIMPLE algorithm, the velocity field and the temperature field in the air preheater under varied working conditions are simulated using the software of Ansys Fluent 2021R1, and the influences of the boiler load, the operation parameters of the steam soot blower, and the running and outage of the soot blower on the flue gas velocity distribution in the depth direction of the corrugated plates, the soot-blowing coverage area, the inlet flue gas velocity, and the inlet flue gas temperature of the corrugated plates are analyzed. Under the base working condition, the flue gas velocity on the axis of the steam nozzle first decreases rapidly with increasing the corrugated plate depth (Z < 1.0 m), and then it decreases slowly with an almost equal slope. The longitudinal flue gas velocity has a positive correlation with the boiler load. The longitudinal flue gas velocity obviously decreases when the boiler load is decreased, and its reduction increases as the corrugated plate depth increases. It is one reason that the ash deposition is prone to occur on the cold end surface of corrugated plates under the condition of low boiler load. The longitudinal flue gas velocity increases with the soot-blowing steam velocity increasing when the corrugated plate depth is less than 1.5 m, but after that, it is almost not affected by the change in soot-blowing steam velocity. The soot-blowing coverage area has a negative correlation with the boiler load but a slight positive correlation with the steam velocity of the soot blower on the whole. The inlet flue gas velocity of the corrugated plates has a positive correlation with the boiler load and the inlet steam velocity of the soot blower. The average inlet flue gas velocity decreases by 21.7% when the boiler load is reduced by 50%. For every 5 m/s variation in the inlet steam velocity, the inlet flue gas velocity changes by about 10–14% whether the steam soot blower is put into operation or not, which has an obvious effect on the inlet gas velocity of the corrugated plates. The inlet flue gas temperature of the corrugated plates is, respectively, positively correlated with the boiler load and the inlet steam temperature of the soot blower. When the boiler load is reduced from 100% BMCR to 50% BMCR, the average inlet flue gas temperature of the corrugated plates is reduced by 44.2 K; however, when the soot-blowing steam temperature varies by 20 K, the average inlet flue gas temperature of the corrugated plates varies by only about 1.8 K. It means that it is difficult to enhance the cold end flue gas temperature of the corrugated plates only by raising the soot-blowing steam temperature at low boiler load. Adding a soot blower using high-temperature steam or hot air at the outlet of the corrugated plates may be an option to solve the ash deposition of the corrugated plates. Full article

(This article belongs to the Section J: Thermal Management)

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18 pages, 2444 KiB

Open AccessReview

Opportunities and Threats for Supercapacitor Technology Based on Biochar—A Review

by Radosław Kwarciany, Marcin Fiedur and Bogdan Saletnik

Energies 2024, 17(18), 4617; https://doi.org/10.3390/en17184617 (registering DOI) - 14 Sep 2024

Abstract

This review analyzes in detail the topic of supercapacitors based on biochar technologies, including their advantages, disadvantages, and development potential. The main topic is the formation of precursors in the process of pyrolysis and activation, and the possibility of the application of biochar [...] Read more.

This review analyzes in detail the topic of supercapacitors based on biochar technologies, including their advantages, disadvantages, and development potential. The main topic is the formation of precursors in the process of pyrolysis and activation, and the possibility of the application of biochar itself in various fields is brought closer. The structure, division, and principle of operation of supercondensates are discussed, where their good and bad sides are pointed out. The current state of the scientific and legal knowledge on the topic of biocarbon and its applications is verified, and the results of many authors are compared to examine the current level of the research on supercapacitors based on biochar electrodes created from lignocellulosic biomass. Current application sites for supercapacitors in transportation, electronics, and power generation (conventional and unconventional) are also examined, as is the potential for further development of the technology under discussion. Full article

(This article belongs to the Special Issue Current Developments in the Biochar Sector)

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15 pages, 2912 KiB

Open AccessArticle

A Standardized Sky Condition Classification Method for Multiple Timescales and Its Applications in the Solar Industry

by Shukla Poddar, Merlinde Kay and John Boland

Energies 2024, 17(18), 4616; https://doi.org/10.3390/en17184616 (registering DOI) - 14 Sep 2024

Abstract

The deployment of photovoltaic (PV) systems has increased globally to meet renewable energy targets. Intermittent PV power generated due to cloud-induced variability introduces reliability and grid stability issues at higher penetration levels. Variability in power generation can induce voltage fluctuations within the distribution [...] Read more.

The deployment of photovoltaic (PV) systems has increased globally to meet renewable energy targets. Intermittent PV power generated due to cloud-induced variability introduces reliability and grid stability issues at higher penetration levels. Variability in power generation can induce voltage fluctuations within the distribution system and cause adverse effects on power quality. Therefore, it is essential to quantify resource variability to mitigate an intermittent power supply. In this study, we propose a new scheme to classify the sky conditions that are based on two common variability metrices: daily clear-sky index and normalized aggregate ramp rates. The daily clear-sky index estimates the cloudiness in the sky, and ramp rates account for the variability introduced in the system generation due to sudden cloud movements. This classification scheme can identify clear-sky, highly variable, low intermittent, high intermittent and overcast days. By performing a Chi-square test on the training and test sets, we obtain Chi-square statistic values greater than 3 with p-value > 0.05. This indicates that the distribution of the training and test clusters are similar, indicating the robustness of the proposed sky classification scheme. We have demonstrated the applicability of the scheme with diverse datasets to show that the proposed classification scheme can be homogenously applied to any dataset globally despite their temporal resolution. Using various case studies, we demonstrate the potential applications of the scheme for understanding resource allocation, site selection, estimating future intermittency due to climate change, and cloud enhancement effects. The proposed sky classification scheme enhances the precision and reliability of solar energy forecasts, optimizing system performance and maximizing energy production efficiency. This improved accuracy is crucial for variability control and planning, ensuring optimal output from PV plants. Full article

(This article belongs to the Special Issue Advances in Wind and Solar Farm Forecasting—3rd Edition)

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29 pages, 17461 KiB

Open AccessArticle

An Integrated CEEMDAN to Optimize Deep Long Short-Term Memory Model for Wind Speed Forecasting

by Yingying He, Likai Zhang, Tengda Guan and Zheyu Zhang

Energies 2024, 17(18), 4615; https://doi.org/10.3390/en17184615 (registering DOI) - 14 Sep 2024

Abstract

Accurate wind speed forecasting is crucial for the efficient operation of renewable energy platforms, such as wind turbines, as it facilitates more effective management of power output and maintains grid reliability and stability. However, the inherent variability and intermittency of wind speed present [...] Read more.

Accurate wind speed forecasting is crucial for the efficient operation of renewable energy platforms, such as wind turbines, as it facilitates more effective management of power output and maintains grid reliability and stability. However, the inherent variability and intermittency of wind speed present significant challenges for achieving precise forecasts. To address these challenges, this study proposes a novel method based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and a deep learning-based Long Short-Term Memory (LSTM) network for wind speed forecasting. In the proposed method, CEEMDAN is utilized to decompose the original wind speed signal into different modes to capture the multiscale temporal properties and patterns of wind speeds. Subsequently, LSTM is employed to predict each subseries derived from the CEEMDAN process. These individual subseries predictions are then combined to generate the overall final forecast. The proposed method is validated using real-world wind speed data from Austria and Almeria. Experimental results indicate that the proposed method achieves minimal mean absolute percentage errors of 0.3285 and 0.1455, outperforming other popular models across multiple performance criteria. Full article

(This article belongs to the Special Issue Advances in Wind and Solar Farm Forecasting—3rd Edition)

20 pages, 8565 KiB

Open AccessArticle

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

by Zheng Shi, Lu Yan, Yingying Hu, Yao Wang, Wenping Qin, Yan Liang, Haibo Zhao, Yongming Jing, Jiaojiao Deng and Zhi Zhang

Energies 2024, 17(18), 4614; https://doi.org/10.3390/en17184614 (registering DOI) - 14 Sep 2024

Abstract

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, [...] Read more.

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%. Full article

(This article belongs to the Special Issue Optimal Planning and Operation in RES-Rich Power Systems under Electricity and Carbon Emission Market Environment)

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