Being multivariable in nature, voltage and current control loops have controllers in the forward and cross-coupling paths. Most methods discussed in the literature focus on tuning the controllers in the forward paths to reduce the dq coupling. A modified pole-zero cancellation (MPZC) technique has recently been discussed, which uses the concepts of pole-zero cancellation and particle swarm optimization to effectively tune the forward path controllers. However, given the fixed gains in the cross-coupling paths, it is not possible to realize a superior transient response from this technique. Therefore, to achieve enhanced vector control of VSIs under transient conditions, this paper proposes a hybrid MPZC (HMPZC) method, which incorporates multivariable control along with the MPZC technique for both voltage/current control loops. In the proposed HMPZC method, the MPZC method is used to tune the forward path controllers, and multivariable control-based PI controllers are assigned in the cross-coupling paths of dq-axes loops rather than fixed gains. In this paper, these multivariable control-based PI controllers are designed using direct synthesis method-based internal model control (IMC). From the simulation results, it is verified that the proposed HMPZC method has reduced the coupling between the d- and q-axes loops of the current/voltage, leading to the improved transient response and power delivery capability of VSIs.
电压和电流控制回路具有多变量性质，在前向和交叉耦合路径中都有控制器。文献中讨论的大多数方法都侧重于调整前向路径中的控制器，以减少 dq 耦合。最近讨论了一种改进的极零消除（MPZC）技术，它利用极零消除和粒子群优化的概念来有效调整前向路径控制器。然而，由于交叉耦合路径的增益是固定的，这种技术无法实现卓越的瞬态响应。因此，为了实现瞬态条件下 VSI 的增强型矢量控制，本文提出了一种混合 MPZC（HMPZC）方法，该方法将多变量控制与 MPZC 技术结合在一起，用于电压/电流控制回路。在所提出的 HMPZC 方法中，MPZC 方法用于调整前向路径控制器，基于多变量控制的 PI 控制器被分配到 dq 轴环路的交叉耦合路径中，而不是固定增益。本文使用基于直接合成法的内部模型控制（IMC）设计了这些基于多变量控制的 PI 控制器。仿真结果证明，所提出的 HMPZC 方法降低了电流/电压 d 轴和 q 轴环路之间的耦合，从而提高了 VSI 的瞬态响应和功率输出能力。
{"title":"Multivariable Control-Based dq Decoupling in Voltage and Current Control Loops for Enhanced Transient Response and Power Delivery in Microgrids","authors":"Mandarapu Srikanth, Yellapragada Venkata Pavan Kumar, Challa Pradeep Reddy, Rammohan Mallipeddi","doi":"10.3390/en17153689","DOIUrl":"https://doi.org/10.3390/en17153689","url":null,"abstract":"Being multivariable in nature, voltage and current control loops have controllers in the forward and cross-coupling paths. Most methods discussed in the literature focus on tuning the controllers in the forward paths to reduce the dq coupling. A modified pole-zero cancellation (MPZC) technique has recently been discussed, which uses the concepts of pole-zero cancellation and particle swarm optimization to effectively tune the forward path controllers. However, given the fixed gains in the cross-coupling paths, it is not possible to realize a superior transient response from this technique. Therefore, to achieve enhanced vector control of VSIs under transient conditions, this paper proposes a hybrid MPZC (HMPZC) method, which incorporates multivariable control along with the MPZC technique for both voltage/current control loops. In the proposed HMPZC method, the MPZC method is used to tune the forward path controllers, and multivariable control-based PI controllers are assigned in the cross-coupling paths of dq-axes loops rather than fixed gains. In this paper, these multivariable control-based PI controllers are designed using direct synthesis method-based internal model control (IMC). From the simulation results, it is verified that the proposed HMPZC method has reduced the coupling between the d- and q-axes loops of the current/voltage, leading to the improved transient response and power delivery capability of VSIs.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zeyi Wang, Yao Wang, Li Xie, Dan Pang, Hao Shi, Hua Zheng
Virtual power plants (VPPs) integrate diverse energy resources using advanced communication technologies and intelligent control strategies. This integration enhances the utilization and efficiency of distributed generation. This paper explores the incorporation of VPPs into load frequency control (LFC) systems. It includes an analysis of VPP-aggregated resources’ frequency regulation characteristics and a VPP-inclusive LFC model. Additionally, a decentralized automatic generation control strategy is proposed to distribute power outputs effectively, enabling swift grid frequency adjustments. This study uses MATLAB simulations to demonstrate the benefits and efficacy of VPPs in LFC, underscoring their role in advancing grid management and stability.
{"title":"Load Frequency Control of Multiarea Power Systems with Virtual Power Plants","authors":"Zeyi Wang, Yao Wang, Li Xie, Dan Pang, Hao Shi, Hua Zheng","doi":"10.3390/en17153687","DOIUrl":"https://doi.org/10.3390/en17153687","url":null,"abstract":"Virtual power plants (VPPs) integrate diverse energy resources using advanced communication technologies and intelligent control strategies. This integration enhances the utilization and efficiency of distributed generation. This paper explores the incorporation of VPPs into load frequency control (LFC) systems. It includes an analysis of VPP-aggregated resources’ frequency regulation characteristics and a VPP-inclusive LFC model. Additionally, a decentralized automatic generation control strategy is proposed to distribute power outputs effectively, enabling swift grid frequency adjustments. This study uses MATLAB simulations to demonstrate the benefits and efficacy of VPPs in LFC, underscoring their role in advancing grid management and stability.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141802240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yan Li, A. Gambelli, Yizhi Rao, Xuejian Liu, Zhenyuan Yin, F. Rossi
Carbon dioxide (CO2) hydrates have garnered significant interest as a promising technology for CO2 capture and storage due to its high storage capacity and moderate operating conditions. The kinetics of CO2 hydrate formation is a critical factor in determining the feasibility of hydrate-based CO2 capture and storage technologies. This study systematically investigates the promotional effects of the amino acid L-tryptophan (L-trp) on CO2 hydrate formation kinetics and morphology under stirred and unstirred conditions. In the stirred system, experiments were conducted in a high-pressure 100 mL reactor with 0.05, 0.10, and 0.30 wt% L-trp solution. CO2 gas uptake kinetics and morphological evolution were monitored using a high-resolution digital camera. Results showed that L-trp promoted CO2 hydrate formation kinetics without delay, with rapid CO2 consumption upon nucleation. Morphological evolution revealed rapid hydrate formation, wall-climbing growth, and dendritic morphology filling the bulk solution. Under unstirred conditions, experiments were performed in a larger 1 L reactor with 0.1 wt% and 0.5 wt% L-trp solutions to assess the influence of additive concentration on hydrate formation thermodynamics and kinetics. Results demonstrated that L-trp influenced both thermodynamics and kinetics of CO2 hydrate formation. Thermodynamically, 0.1 wt% L-trp resulted in the highest hydrate formation, indicating an optimal concentration for thermodynamic promotion. Kinetically, increasing L-trp concentration from 0.1 wt% to 0.5 wt% reduced formation time, demonstrating a proportional relationship between L-trp concentration and formation kinetics. These findings provide insights into the role of L-trp in promoting CO2 hydrate formation and the interplay between additive concentration, thermodynamics, and kinetics. The results can inform the development of effective hydrate-based technologies for CO2 sequestration, highlighting the potential of amino acids as promoters in gas hydrate.
{"title":"Unraveling the Role of Amino Acid L-Tryptophan Concentration in Enhancing CO2 Hydrate Kinetics","authors":"Yan Li, A. Gambelli, Yizhi Rao, Xuejian Liu, Zhenyuan Yin, F. Rossi","doi":"10.3390/en17153702","DOIUrl":"https://doi.org/10.3390/en17153702","url":null,"abstract":"Carbon dioxide (CO2) hydrates have garnered significant interest as a promising technology for CO2 capture and storage due to its high storage capacity and moderate operating conditions. The kinetics of CO2 hydrate formation is a critical factor in determining the feasibility of hydrate-based CO2 capture and storage technologies. This study systematically investigates the promotional effects of the amino acid L-tryptophan (L-trp) on CO2 hydrate formation kinetics and morphology under stirred and unstirred conditions. In the stirred system, experiments were conducted in a high-pressure 100 mL reactor with 0.05, 0.10, and 0.30 wt% L-trp solution. CO2 gas uptake kinetics and morphological evolution were monitored using a high-resolution digital camera. Results showed that L-trp promoted CO2 hydrate formation kinetics without delay, with rapid CO2 consumption upon nucleation. Morphological evolution revealed rapid hydrate formation, wall-climbing growth, and dendritic morphology filling the bulk solution. Under unstirred conditions, experiments were performed in a larger 1 L reactor with 0.1 wt% and 0.5 wt% L-trp solutions to assess the influence of additive concentration on hydrate formation thermodynamics and kinetics. Results demonstrated that L-trp influenced both thermodynamics and kinetics of CO2 hydrate formation. Thermodynamically, 0.1 wt% L-trp resulted in the highest hydrate formation, indicating an optimal concentration for thermodynamic promotion. Kinetically, increasing L-trp concentration from 0.1 wt% to 0.5 wt% reduced formation time, demonstrating a proportional relationship between L-trp concentration and formation kinetics. These findings provide insights into the role of L-trp in promoting CO2 hydrate formation and the interplay between additive concentration, thermodynamics, and kinetics. The results can inform the development of effective hydrate-based technologies for CO2 sequestration, highlighting the potential of amino acids as promoters in gas hydrate.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ben Sonpon, Shoaib Usman, Joseph D. Smith, Sarah Kovaleski, Jason Wibbenmeyer
Many regulatory requirements add significant delay in the licensing of new nuclear power stations. One area of particular interest is the environmental impact of potential atmospheric release. The purpose of this research is to demonstrate effectiveness of meteorological data mining and synthesis from offsite locations to reduce need for onsite data, hence allowing rapid licensing. The automated procedures tested for data mining and extraction of meteorological data from multiple offsite sources and the data analytic tool developed for data fusion are presented here. Three important meteorological parameters from regulatory compliance are considered for this analysis: wind velocity, wind direction, and atmospheric stability. Callaway Nuclear Power Plant (CNPP) is used as our reference site. CNPP uses the ΔTΔz approach while we use the Vogt method to estimated stability for the offsite locations. Stability classification correlation coefficients between the reference plant and Columbia Regional Airport range from −0.087 to 0.826 for raw with an average of 0.317 ± 0.313. With travel time, correction changed slightly, i.e., a 10 m observation 0.064 ± 0.249 and 0.028 ± 0.123 and a 60 m observation 0.103 ± 0.265 and 0.063 ± 0.155 for the wind from the reference plant to the airport and vice versa, respectively. For Jefferson City Memorial Airport, raw data correlation was from −0.083 to 0.771, with an average of 0.358 ± 0.321. With travel time, correction changed slightly, i.e., 10 m observation 0.075 ± 0.208 and −0.073 ± 0.255 and 60 m observation 0.018 ± 0.223 and −0.032 ± 0.248 for wind from the reference plant to the airport and vice versa, respectively. Stability classification correlation coefficients between the reference plant and St. Louis Lambert International Airport ranged from −0.083 to 0.763 for raw with an average of 0.314 ± 0.295. With travel time, correction changed slightly, i.e., 10 m observation −0.003 ± 0.307 and −0.030 ± 0.277 and 60 m observation −0.030 ± 0.193 and −0.005 ± 0.215 for wind from the reference plant to the airport and vice versa, respectively. It is important to observe that mathematically. stability class correlation coefficients were not great, but in most cases the predicted and observed values were only off by one stability class. Similar correlations were calculated for wind direction and velocities. Our result, when applied to a proposed nuclear power station, can significantly reduce time and effort to prepare a robust environmental protection plan required for license application.
{"title":"Meteorological Data Mining and Synthesis for Supplementing On-Site Data for Regulatory Compliance","authors":"Ben Sonpon, Shoaib Usman, Joseph D. Smith, Sarah Kovaleski, Jason Wibbenmeyer","doi":"10.3390/en17153691","DOIUrl":"https://doi.org/10.3390/en17153691","url":null,"abstract":"Many regulatory requirements add significant delay in the licensing of new nuclear power stations. One area of particular interest is the environmental impact of potential atmospheric release. The purpose of this research is to demonstrate effectiveness of meteorological data mining and synthesis from offsite locations to reduce need for onsite data, hence allowing rapid licensing. The automated procedures tested for data mining and extraction of meteorological data from multiple offsite sources and the data analytic tool developed for data fusion are presented here. Three important meteorological parameters from regulatory compliance are considered for this analysis: wind velocity, wind direction, and atmospheric stability. Callaway Nuclear Power Plant (CNPP) is used as our reference site. CNPP uses the ΔTΔz approach while we use the Vogt method to estimated stability for the offsite locations. Stability classification correlation coefficients between the reference plant and Columbia Regional Airport range from −0.087 to 0.826 for raw with an average of 0.317 ± 0.313. With travel time, correction changed slightly, i.e., a 10 m observation 0.064 ± 0.249 and 0.028 ± 0.123 and a 60 m observation 0.103 ± 0.265 and 0.063 ± 0.155 for the wind from the reference plant to the airport and vice versa, respectively. For Jefferson City Memorial Airport, raw data correlation was from −0.083 to 0.771, with an average of 0.358 ± 0.321. With travel time, correction changed slightly, i.e., 10 m observation 0.075 ± 0.208 and −0.073 ± 0.255 and 60 m observation 0.018 ± 0.223 and −0.032 ± 0.248 for wind from the reference plant to the airport and vice versa, respectively. Stability classification correlation coefficients between the reference plant and St. Louis Lambert International Airport ranged from −0.083 to 0.763 for raw with an average of 0.314 ± 0.295. With travel time, correction changed slightly, i.e., 10 m observation −0.003 ± 0.307 and −0.030 ± 0.277 and 60 m observation −0.030 ± 0.193 and −0.005 ± 0.215 for wind from the reference plant to the airport and vice versa, respectively. It is important to observe that mathematically. stability class correlation coefficients were not great, but in most cases the predicted and observed values were only off by one stability class. Similar correlations were calculated for wind direction and velocities. Our result, when applied to a proposed nuclear power station, can significantly reduce time and effort to prepare a robust environmental protection plan required for license application.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The automotive industry is experiencing radical changes under the pressure of institutions that are increasingly reducing the limits on CO2 and pollutant emissions from road vehicles powered by internal combustion engines (ICEs). A way to decarbonize the transport sector without disrupting current automotive production is the adoption of alternative fuels for internal combustion engines (ICEs). Hydrogen is very attractive, thanks to the zero-carbon content and very high laminar flame speed, allowing for extending the lean burn limit. Other alternative fuels are methanol and ethanol. This work deals with the conversion of a small-sized passenger car powered by a three-cylinder spark ignition (SI) engine for the use of alternative fuels. In particular, the spark timing has been optimized to improve the fuel economy under every operating condition. The optimization procedure is based on the MATLAB/Simulink® R2024a-GT-Power co-simulation analysis and minimizes the fuel consumption by varying the spark timing independently for each cylinder. In particular, at full load, the algorithm reduces the spark timing only for the cylinder in which knock is detected, reducing fuel consumption by about 2% compared to the base calibration. This approach will be adopted in future activities to understand how the use of alternative fuels affects the ignition control strategy.
{"title":"Spark Timing Optimization through Co-Simulation Analysis in a Spark Ignition Engine","authors":"Ivan Arsie, E. Frasci, A. Irimescu, S. Merola","doi":"10.3390/en17153695","DOIUrl":"https://doi.org/10.3390/en17153695","url":null,"abstract":"The automotive industry is experiencing radical changes under the pressure of institutions that are increasingly reducing the limits on CO2 and pollutant emissions from road vehicles powered by internal combustion engines (ICEs). A way to decarbonize the transport sector without disrupting current automotive production is the adoption of alternative fuels for internal combustion engines (ICEs). Hydrogen is very attractive, thanks to the zero-carbon content and very high laminar flame speed, allowing for extending the lean burn limit. Other alternative fuels are methanol and ethanol. This work deals with the conversion of a small-sized passenger car powered by a three-cylinder spark ignition (SI) engine for the use of alternative fuels. In particular, the spark timing has been optimized to improve the fuel economy under every operating condition. The optimization procedure is based on the MATLAB/Simulink® R2024a-GT-Power co-simulation analysis and minimizes the fuel consumption by varying the spark timing independently for each cylinder. In particular, at full load, the algorithm reduces the spark timing only for the cylinder in which knock is detected, reducing fuel consumption by about 2% compared to the base calibration. This approach will be adopted in future activities to understand how the use of alternative fuels affects the ignition control strategy.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141800757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matheus Noschang de Oliveira, Letícia Rezende Mosquéra, Patrícia Helena dos Santos Martins, André Luiz Marques Serrano, Guilherme Dantas Bispo, Guilherme Fay Vergara, Gabriela Mayumi Saiki, Clóvis Neumann, V. P. Gonçalves
The use of biofuels represents a promising means of achieving a sustainable future and offers considerable economic and environmental benefits. Since they are derived from organic sources, such as vegetable oils and animal fats, biofuels can mitigate the effects of greenhouse gas emissions, improve air quality, support local agriculture, create employment opportunities, and enhance energy security by reducing dependence on fossil fuels. However, introducing these alternative fuels to the aviation sector remains a significant challenge. Thus, it is vital to investigate the potential of sustainable aviation fuel (SAF) and discover how to overcome the technological obstacles to its integration into mainstream aviation to attain broader decarbonization objectives. This article seeks to contribute to a discussion about SAF by examining how it has evolved and its connections to related patents. This article is a comprehensive study of biofuel innovation, highlighting the complex relationships between academia, industry, and other stakeholders. It is hoped that the findings from this study will provide a clearer understanding of the catalysts involved in SAF innovation and provide valuable insights for policymakers, academics, and professionals in the field who are committed to shaping the trajectory of sustainable energy technologies in the future.
生物燃料的使用是实现可持续未来的一个大有可为的手段，并能带来可观的经济和环境效益。由于生物燃料来自植物油和动物脂肪等有机来源，因此可以减轻温室气体排放的影响，改善空气质量，支持当地农业，创造就业机会，并通过减少对化石燃料的依赖来加强能源安全。然而，将这些替代燃料引入航空领域仍然是一项重大挑战。因此，研究可持续航空燃料（SAF）的潜力并探索如何克服其融入主流航空业的技术障碍以实现更广泛的去碳化目标至关重要。本文旨在通过研究 SAF 的演变过程及其与相关专利的联系，为有关 SAF 的讨论做出贡献。本文是对生物燃料创新的全面研究，强调了学术界、工业界和其他利益相关者之间的复杂关系。希望本研究的结果能让人们更清楚地了解 SAF 创新所涉及的催化剂，并为致力于塑造未来可持续能源技术发展轨迹的政策制定者、学者和该领域的专业人士提供有价值的见解。
{"title":"Tracking Biofuel Innovation: A Graph-Based Analysis of Sustainable Aviation Fuel Patents","authors":"Matheus Noschang de Oliveira, Letícia Rezende Mosquéra, Patrícia Helena dos Santos Martins, André Luiz Marques Serrano, Guilherme Dantas Bispo, Guilherme Fay Vergara, Gabriela Mayumi Saiki, Clóvis Neumann, V. P. Gonçalves","doi":"10.3390/en17153683","DOIUrl":"https://doi.org/10.3390/en17153683","url":null,"abstract":"The use of biofuels represents a promising means of achieving a sustainable future and offers considerable economic and environmental benefits. Since they are derived from organic sources, such as vegetable oils and animal fats, biofuels can mitigate the effects of greenhouse gas emissions, improve air quality, support local agriculture, create employment opportunities, and enhance energy security by reducing dependence on fossil fuels. However, introducing these alternative fuels to the aviation sector remains a significant challenge. Thus, it is vital to investigate the potential of sustainable aviation fuel (SAF) and discover how to overcome the technological obstacles to its integration into mainstream aviation to attain broader decarbonization objectives. This article seeks to contribute to a discussion about SAF by examining how it has evolved and its connections to related patents. This article is a comprehensive study of biofuel innovation, highlighting the complex relationships between academia, industry, and other stakeholders. It is hoped that the findings from this study will provide a clearer understanding of the catalysts involved in SAF innovation and provide valuable insights for policymakers, academics, and professionals in the field who are committed to shaping the trajectory of sustainable energy technologies in the future.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christos D. Korkas, Christos Tsaknakis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos
The increasing number of electric vehicles (EVs) necessitates the installation of more charging stations. The challenge of managing these grid-connected charging stations leads to a multi-objective optimal control problem where station profitability, user preferences, grid requirements and stability should be optimized. However, it is challenging to determine the optimal charging/discharging EV schedule, since the controller should exploit fluctuations in the electricity prices, available renewable resources and available stored energy of other vehicles and cope with the uncertainty of EV arrival/departure scheduling. In addition, the growing number of connected vehicles results in a complex state and action vectors, making it difficult for centralized and single-agent controllers to handle the problem. In this paper, we propose a novel Multi-Agent and distributed Reinforcement Learning (MARL) framework that tackles the challenges mentioned above, producing controllers that achieve high performance levels under diverse conditions. In the proposed distributed framework, each charging spot makes its own charging/discharging decisions toward a cumulative cost reduction without sharing any type of private information, such as the arrival/departure time of a vehicle and its state of charge, addressing the problem of cost minimization and user satisfaction. The framework significantly improves the scalability and sample efficiency of the underlying Deep Deterministic Policy Gradient (DDPG) algorithm. Extensive numerical studies and simulations demonstrate the efficacy of the proposed approach compared with Rule-Based Controllers (RBCs) and well-established, state-of-the-art centralized RL (Reinforcement Learning) algorithms, offering performance improvements of up to 25% and 20% in reducing the energy cost and increasing user satisfaction, respectively.
{"title":"Distributed and Multi-Agent Reinforcement Learning Framework for Optimal Electric Vehicle Charging Scheduling","authors":"Christos D. Korkas, Christos Tsaknakis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos","doi":"10.3390/en17153694","DOIUrl":"https://doi.org/10.3390/en17153694","url":null,"abstract":"The increasing number of electric vehicles (EVs) necessitates the installation of more charging stations. The challenge of managing these grid-connected charging stations leads to a multi-objective optimal control problem where station profitability, user preferences, grid requirements and stability should be optimized. However, it is challenging to determine the optimal charging/discharging EV schedule, since the controller should exploit fluctuations in the electricity prices, available renewable resources and available stored energy of other vehicles and cope with the uncertainty of EV arrival/departure scheduling. In addition, the growing number of connected vehicles results in a complex state and action vectors, making it difficult for centralized and single-agent controllers to handle the problem. In this paper, we propose a novel Multi-Agent and distributed Reinforcement Learning (MARL) framework that tackles the challenges mentioned above, producing controllers that achieve high performance levels under diverse conditions. In the proposed distributed framework, each charging spot makes its own charging/discharging decisions toward a cumulative cost reduction without sharing any type of private information, such as the arrival/departure time of a vehicle and its state of charge, addressing the problem of cost minimization and user satisfaction. The framework significantly improves the scalability and sample efficiency of the underlying Deep Deterministic Policy Gradient (DDPG) algorithm. Extensive numerical studies and simulations demonstrate the efficacy of the proposed approach compared with Rule-Based Controllers (RBCs) and well-established, state-of-the-art centralized RL (Reinforcement Learning) algorithms, offering performance improvements of up to 25% and 20% in reducing the energy cost and increasing user satisfaction, respectively.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bidhan Nath, Les Bowtell, Guangnan Chen, Elizabeth Graham, Thong Nguyen-Huy
The study of the thermokinetics of two types of wheat straw pellets, T1 (100% wheat straw) and T2 (70% wheat straw, 10% each of bentonite clay, sawdust, and biochar), under a nitrogen atmosphere (31–800 °C and 5, 10, and 20 °C/min heating rates) using model-free and model-based approaches by TG/DTG data, revealed promising results. While model-free methods were not suitable, model-based reactions, particularly Fn (nth-order phase interfacial) and F2 (second-order) models, effectively described the three-phase consecutive thermal degradation pathway (A→B, C→D, and D→E). The activation energy (Eα) for phases 2 and 3 (Fn model) averaged 136.04 and 358.11 kJ/mol for T1 and 132.86 and 227.10 kJ/mol for T2, respectively. The pre-exponential factor (lnA) varied across heating rates and pellets (T2: 38.244–2.9 × 109 1/s; T1: 1.2 × 102–5.45 × 1014 1/s). Notably, pellets with additives (T2) exhibited a higher degradable fraction due to lower Eα. These findings suggest a promising potential for utilizing wheat straw pellet biomass as a bioenergy feedstock, highlighting the practical implications of this research.
{"title":"Pyrolytic Pathway of Wheat Straw Pellet by the Thermogravimetric Analyzer","authors":"Bidhan Nath, Les Bowtell, Guangnan Chen, Elizabeth Graham, Thong Nguyen-Huy","doi":"10.3390/en17153693","DOIUrl":"https://doi.org/10.3390/en17153693","url":null,"abstract":"The study of the thermokinetics of two types of wheat straw pellets, T1 (100% wheat straw) and T2 (70% wheat straw, 10% each of bentonite clay, sawdust, and biochar), under a nitrogen atmosphere (31–800 °C and 5, 10, and 20 °C/min heating rates) using model-free and model-based approaches by TG/DTG data, revealed promising results. While model-free methods were not suitable, model-based reactions, particularly Fn (nth-order phase interfacial) and F2 (second-order) models, effectively described the three-phase consecutive thermal degradation pathway (A→B, C→D, and D→E). The activation energy (Eα) for phases 2 and 3 (Fn model) averaged 136.04 and 358.11 kJ/mol for T1 and 132.86 and 227.10 kJ/mol for T2, respectively. The pre-exponential factor (lnA) varied across heating rates and pellets (T2: 38.244–2.9 × 109 1/s; T1: 1.2 × 102–5.45 × 1014 1/s). Notably, pellets with additives (T2) exhibited a higher degradable fraction due to lower Eα. These findings suggest a promising potential for utilizing wheat straw pellet biomass as a bioenergy feedstock, highlighting the practical implications of this research.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The heat treatment temperature must precisely meet the required profile to ensure the quality of the workpiece. The model of the heat treatment furnace is not precisely known because it is nonlinear and complex. Considering this aspect, model-free temperature control methods are proposed, which are not based on a model of the process, but only on the input and output data acquired from the control system. Since the controlled temperature must accurately track the reference formed by the ramp and soak signals in the presence of disturbances, model-free iPI controllers were chosen due to the included double-integral component that ensures the steady-state performance for ramp signals. For the tuning of the iPI controller parameters, the iterative feedback tuning method is proposed, and the performance is compared with that obtained using the sliding mode control iPI variant. The proposed iPI control laws are tested for ramp and soak scenarios, using temperature suitable to thermal treatment technological processes, and performance is analyzed using both process-specific indices and classical criteria.
{"title":"Model-Free Temperature Control of Heat Treatment Process","authors":"A. Baciu, Corneliu Lazar","doi":"10.3390/en17153679","DOIUrl":"https://doi.org/10.3390/en17153679","url":null,"abstract":"The heat treatment temperature must precisely meet the required profile to ensure the quality of the workpiece. The model of the heat treatment furnace is not precisely known because it is nonlinear and complex. Considering this aspect, model-free temperature control methods are proposed, which are not based on a model of the process, but only on the input and output data acquired from the control system. Since the controlled temperature must accurately track the reference formed by the ramp and soak signals in the presence of disturbances, model-free iPI controllers were chosen due to the included double-integral component that ensures the steady-state performance for ramp signals. For the tuning of the iPI controller parameters, the iterative feedback tuning method is proposed, and the performance is compared with that obtained using the sliding mode control iPI variant. The proposed iPI control laws are tested for ramp and soak scenarios, using temperature suitable to thermal treatment technological processes, and performance is analyzed using both process-specific indices and classical criteria.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141800332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hosik Jeong, Kanghyuk Ko, Junsung Kim, Jongsoo Kim, Seongyong Eom, Sang-Kwon Na, Gyungmin Choi
In order to save the time and material costs associated with refrigeration system performance evaluations, a reduced-order model (ROM) using highly accurate numerical analysis results and some experimental values was developed. To solve the shortcomings of these traditional methods in monitoring complex systems, a simplified reduced-order system model was developed. To evaluate the performance of the refrigeration system compressor, the temperature of several points in the system where the compressor actually operates was measured, and the measured values were used as input values for ROM development. A lot of raw data to develop a highly accurate ROM were acquired from a VRF system installed in a building for one year, and in this study, specific operating conditions were selected and used as input values. In this study, the ROM development process can predict the performance of compressors used in air conditioning systems, and the research results on optimizing input data required for ROM generation were observed. The input data are arranged according to the design of experiments (DOE), and the accuracy of ROM according to data arrangement is compared through the experiment results.
为了节省与制冷系统性能评估相关的时间和材料成本，利用高精度的数值分析结果和一些实验值开发了一种简化阶模型（ROM）。为了解决这些传统方法在监测复杂系统方面的不足，我们开发了一个简化的降阶系统模型。为了评估制冷系统压缩机的性能，对系统中压缩机实际运行的几个点的温度进行了测量，并将测量值作为 ROM 开发的输入值。从安装在一栋建筑中一年的 VRF 系统中获取了大量用于开发高精度 ROM 的原始数据，并在本研究中选择了特定的运行条件作为输入值。在这项研究中，ROM 的开发过程可以预测空调系统中使用的压缩机的性能，并观察了生成 ROM 所需的输入数据的优化研究成果。根据实验设计（DOE）安排输入数据，并通过实验结果比较根据数据安排生成的 ROM 的准确性。
{"title":"Evaluation of Prediction Model for Compressor Performance Using Artificial Neural Network Models and Reduced-Order Models","authors":"Hosik Jeong, Kanghyuk Ko, Junsung Kim, Jongsoo Kim, Seongyong Eom, Sang-Kwon Na, Gyungmin Choi","doi":"10.3390/en17153686","DOIUrl":"https://doi.org/10.3390/en17153686","url":null,"abstract":"In order to save the time and material costs associated with refrigeration system performance evaluations, a reduced-order model (ROM) using highly accurate numerical analysis results and some experimental values was developed. To solve the shortcomings of these traditional methods in monitoring complex systems, a simplified reduced-order system model was developed. To evaluate the performance of the refrigeration system compressor, the temperature of several points in the system where the compressor actually operates was measured, and the measured values were used as input values for ROM development. A lot of raw data to develop a highly accurate ROM were acquired from a VRF system installed in a building for one year, and in this study, specific operating conditions were selected and used as input values. In this study, the ROM development process can predict the performance of compressors used in air conditioning systems, and the research results on optimizing input data required for ROM generation were observed. The input data are arranged according to the design of experiments (DOE), and the accuracy of ROM according to data arrangement is compared through the experiment results.","PeriodicalId":11557,"journal":{"name":"Energies","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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