Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introdu...Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.展开更多
This paper investigates the distributed continuoustime aggregative optimization problem for second-order multiagent systems,where the local cost function is not only related to its own decision variables,but also to t...This paper investigates the distributed continuoustime aggregative optimization problem for second-order multiagent systems,where the local cost function is not only related to its own decision variables,but also to the aggregation of the decision variables of all the agents.By using the gradient descent method,the distributed average tracking(DAT)technique and the time-base generator(TBG)technique,a distributed continuous-time aggregative optimization algorithm is proposed.Subsequently,the optimality of the system's equilibrium point is analyzed,and the convergence of the closed-loop system is proved using the Lyapunov stability theory.Finally,the effectiveness of the proposed algorithm is validated through case studies on multirobot systems and power generation systems.展开更多
In this study, a new method for a comprehensive evaluation of air quality in urban agglomerations was developed based on a prototype used to solve the spatial Steiner-Weber point. With this method, the air quality inf...In this study, a new method for a comprehensive evaluation of air quality in urban agglomerations was developed based on a prototype used to solve the spatial Steiner-Weber point. With this method, the air quality information of each city in the city group is aggregated into an optimal gathering point, and then the air quality of the city group is then dynamically evaluated each year. According to the relevant data of the China Statistical Yearbook 2018, we applied this method to aggregate the air quality indices of the major cities in the Beijing-Tianjin-Hebei urban agglomeration from 2014 to 2017. Using the plant growth simulation algorithm (PGSA), the optimal assembly points were calculated to be of a higher accuracy, compared to the traditional mean value aggregation method. Finally, the air quality of the Beijing-Tianjin-Hebei urban agglomeration during each year was evaluated dynamically based on the obtained assembly points. The results show that the air quality of the urban agglomeration is ranked as follows: <span>Y2016<img src="Edit_28ddcae1-12ec-4d20-a4e9-77309c996766.bmp" alt="" /></span><span></span><span>Y2015<img src="Edit_5f164e96-55aa-4e37-98e1-6833665979d1.bmp" alt="" /></span><span></span><span>Y2017<img src="Edit_cfc0da49-7e3a-4aa8-82ac-ede99621d1ec.bmp" alt="" /></span><span></span><span>Y2014.</span>展开更多
In this paper,the authors propose a distributed gradient tracking algorithm with compressed communication to address an aggregative optimization problem under communication constraints.The problem involves minimizing ...In this paper,the authors propose a distributed gradient tracking algorithm with compressed communication to address an aggregative optimization problem under communication constraints.The problem involves minimizing the sum of local cost functions,where each cost function depends on both local and global state variables.The authors aim to solve this optimization problem through local computation and efficient communication among agents in a network,without the need for a central coordinator.The proposed algorithm combines the variable tracking method to estimate global state variables and a compressed communication scheme to reduce communication costs during the optimization process.Among which,the compressed scheme can encompass both biased and unbiased compressors.Despite the loss of some transmitting information due to quantization,the proposed algorithm can still achieve the exact optimal solution with a linear convergence rate.The authors validate the theoretical results through simulation experiments on an optimal placement problem.展开更多
With advances in modern agricultural parks,the rural energy structure has undergone profound change,leading to the emergence of an agricultural energy internet.This integrated system combines agricultural energy utili...With advances in modern agricultural parks,the rural energy structure has undergone profound change,leading to the emergence of an agricultural energy internet.This integrated system combines agricultural energy utilization,the information internet,and agricultural production.Accordingly,this study proposes a regulation flexibility assessment approach and optimal aggregation strategy of greenhouse loads(GHLs)for modern agricultural parks.First,taking into account the operational characteristics of typical GHLs,refined load demand models for lighting,humidification,and temperature-controlled loads are established.Secondly,the recursive least squares method-based parameter identification method is designed to accurately determine key GHL model parameters.Finally,based on the regulation flexibility of quantitatively evaluated GHLs,GHLs are optimally aggregated into multiple flexible aggregators considering minimal operational cost and greenhouse environmental constraints.The results indicate that the proposed regulation flexibility assessment approach and optimal aggregation strategy of GHLs can alleviate the peak regulation pressure on power grids by flexibly shifting the load demands of GHLs.展开更多
基金funded by the Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme(FRGS/1/2024/ICT02/UCSI/02/1).
文摘Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.
基金supported by the National Key Research and Development Program of China(2025YFE0213100)the National Natural Science Foundation of China(62422315,62573348)+1 种基金the Natural Science Basic Research Program of Shaanxi(2025JC-YBMS-667)the“Shuang Yi Liu”Construction Foundation(25GH02010366)。
文摘This paper investigates the distributed continuoustime aggregative optimization problem for second-order multiagent systems,where the local cost function is not only related to its own decision variables,but also to the aggregation of the decision variables of all the agents.By using the gradient descent method,the distributed average tracking(DAT)technique and the time-base generator(TBG)technique,a distributed continuous-time aggregative optimization algorithm is proposed.Subsequently,the optimality of the system's equilibrium point is analyzed,and the convergence of the closed-loop system is proved using the Lyapunov stability theory.Finally,the effectiveness of the proposed algorithm is validated through case studies on multirobot systems and power generation systems.
文摘In this study, a new method for a comprehensive evaluation of air quality in urban agglomerations was developed based on a prototype used to solve the spatial Steiner-Weber point. With this method, the air quality information of each city in the city group is aggregated into an optimal gathering point, and then the air quality of the city group is then dynamically evaluated each year. According to the relevant data of the China Statistical Yearbook 2018, we applied this method to aggregate the air quality indices of the major cities in the Beijing-Tianjin-Hebei urban agglomeration from 2014 to 2017. Using the plant growth simulation algorithm (PGSA), the optimal assembly points were calculated to be of a higher accuracy, compared to the traditional mean value aggregation method. Finally, the air quality of the Beijing-Tianjin-Hebei urban agglomeration during each year was evaluated dynamically based on the obtained assembly points. The results show that the air quality of the urban agglomeration is ranked as follows: <span>Y2016<img src="Edit_28ddcae1-12ec-4d20-a4e9-77309c996766.bmp" alt="" /></span><span></span><span>Y2015<img src="Edit_5f164e96-55aa-4e37-98e1-6833665979d1.bmp" alt="" /></span><span></span><span>Y2017<img src="Edit_cfc0da49-7e3a-4aa8-82ac-ede99621d1ec.bmp" alt="" /></span><span></span><span>Y2014.</span>
基金supported by the National Key Research and Development Program of China under Grant No.2022YFA1004701the National Natural Science Foundation of China under Grant No.72271187+1 种基金the Fundamental Research Funds for the Central Universitiespartially by Shanghai Municipal Science and Technology Major Project under Grant No.2021SHZDZX0100。
文摘In this paper,the authors propose a distributed gradient tracking algorithm with compressed communication to address an aggregative optimization problem under communication constraints.The problem involves minimizing the sum of local cost functions,where each cost function depends on both local and global state variables.The authors aim to solve this optimization problem through local computation and efficient communication among agents in a network,without the need for a central coordinator.The proposed algorithm combines the variable tracking method to estimate global state variables and a compressed communication scheme to reduce communication costs during the optimization process.Among which,the compressed scheme can encompass both biased and unbiased compressors.Despite the loss of some transmitting information due to quantization,the proposed algorithm can still achieve the exact optimal solution with a linear convergence rate.The authors validate the theoretical results through simulation experiments on an optimal placement problem.
基金the Science and Technology Project of State Grid Corporation of China(No.1400-202224249A-1-1-ZN)the National Natural Science Foundation of China(No.52077075 and No.72271068)+2 种基金the Foundations of Shenzhen and Technology Committee(No.GJHZ20210705141811036 and No.GXWD20220811151845006)the Major Science and Technology Special Projects in Xinjiang Autonomous Region(No.2022A01007)the Fundamental Research Funds for the Central Universities(No.2023JC001).
文摘With advances in modern agricultural parks,the rural energy structure has undergone profound change,leading to the emergence of an agricultural energy internet.This integrated system combines agricultural energy utilization,the information internet,and agricultural production.Accordingly,this study proposes a regulation flexibility assessment approach and optimal aggregation strategy of greenhouse loads(GHLs)for modern agricultural parks.First,taking into account the operational characteristics of typical GHLs,refined load demand models for lighting,humidification,and temperature-controlled loads are established.Secondly,the recursive least squares method-based parameter identification method is designed to accurately determine key GHL model parameters.Finally,based on the regulation flexibility of quantitatively evaluated GHLs,GHLs are optimally aggregated into multiple flexible aggregators considering minimal operational cost and greenhouse environmental constraints.The results indicate that the proposed regulation flexibility assessment approach and optimal aggregation strategy of GHLs can alleviate the peak regulation pressure on power grids by flexibly shifting the load demands of GHLs.
