With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this prob...With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.展开更多
This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇...This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.展开更多
Digital twin is a cutting-edge technology in the energy industry,capable of predicting real-time operation data for equipment performance monitoring and operational optimization.However,methods for calibrating and fus...Digital twin is a cutting-edge technology in the energy industry,capable of predicting real-time operation data for equipment performance monitoring and operational optimization.However,methods for calibrating and fusing digital twin prediction with limited in-situ measured data are still lacking,especially for equipment involving complicated multiphase flow and chemical reactions like coal-fired boilers.In this work,using coal-fired boiler water wall temperature monitoring as an example,we propose a digital twin that reconstructs the water wall temperature distribution with high spatial resolution in real time and calibrates the reconstruction using in-situ water wall temperature data.The digital twin is established using the gappy proper orthogonal decomposition(POD)reduced-order model by fusing CFD solutions and measured data.The reconstruction accuracy of the digital twin was initially validated.And then,the minimum number of measured data sampling points required for precise reconstruction was investigated.An improved uniform data collection method was subsequently developed.After that,the computational time required for the digital twin and the traditional CFD was compared.Finally,the reconstruction method was further validated by in-situ measured temperature from the in-service boiler.Results indicate that the established digital twin can precisely reconstruct the water wall temperature in real time.Thirty-nine sampling points are sufficient to reconstruct the temperature distribution with the original data collection method.The proposed uniform data collection method further reduces the mean relative errors to less than 0.4%across four test cases,and with the constrained technique,the errors decrease to 0.374%and 0.345%for Cases 1 and 3,which had poor reconstructions using the original sampling point arrangement.In addition,the reconstruction time of the digital twin is also considerably reduced compared to CFD.Engineering application indicates that the reconstructed temperatures are highly consistent with in-situ measured data.The established water wall temperature digital twin is beneficial for water wall tube overheating detection and operation optimization.展开更多
基金supported by the Science and Technology Project from the State Grid Shanghai Municipal Electric Power Company of China (52094019006U)the Shanghai Rising-Star Program (18QB1400200)。
文摘With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.
基金Supported by the Fundamental Research Funds for the National Science Foundation of China(71573084)
文摘This paper built a combined heat and power（CHP） dispatch model for wind-CHP system with solid heat storage device（SHS） aiming at minimizing system coal consumption, and set system demand-supply balance and units＇ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.
基金supported by the Scientific and Technological Innovation Project of Carbon Emission Peak and Carbon Neutrality of Jiangsu Province(BE2023854)the New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘Digital twin is a cutting-edge technology in the energy industry,capable of predicting real-time operation data for equipment performance monitoring and operational optimization.However,methods for calibrating and fusing digital twin prediction with limited in-situ measured data are still lacking,especially for equipment involving complicated multiphase flow and chemical reactions like coal-fired boilers.In this work,using coal-fired boiler water wall temperature monitoring as an example,we propose a digital twin that reconstructs the water wall temperature distribution with high spatial resolution in real time and calibrates the reconstruction using in-situ water wall temperature data.The digital twin is established using the gappy proper orthogonal decomposition(POD)reduced-order model by fusing CFD solutions and measured data.The reconstruction accuracy of the digital twin was initially validated.And then,the minimum number of measured data sampling points required for precise reconstruction was investigated.An improved uniform data collection method was subsequently developed.After that,the computational time required for the digital twin and the traditional CFD was compared.Finally,the reconstruction method was further validated by in-situ measured temperature from the in-service boiler.Results indicate that the established digital twin can precisely reconstruct the water wall temperature in real time.Thirty-nine sampling points are sufficient to reconstruct the temperature distribution with the original data collection method.The proposed uniform data collection method further reduces the mean relative errors to less than 0.4%across four test cases,and with the constrained technique,the errors decrease to 0.374%and 0.345%for Cases 1 and 3,which had poor reconstructions using the original sampling point arrangement.In addition,the reconstruction time of the digital twin is also considerably reduced compared to CFD.Engineering application indicates that the reconstructed temperatures are highly consistent with in-situ measured data.The established water wall temperature digital twin is beneficial for water wall tube overheating detection and operation optimization.
