Hongjie Jia
Tianjin University
345 Papers
899 Citations
Hongjie Jia is an academic researcher from Tianjin University. The author has contributed to research in topics: Electric power system & Computer science. The author has an hindex of 39, co-authored 284 publications. Previous affiliations of Hongjie Jia include United Laboratories.
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Papers
Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles
TL;DR: In this article, an efficient power plant model of EVs (E-EPP) is developed for the active power regulation of the power system with large-scale wind farms based on the EV data base provided by the EU MERGE project, a generic V2G model (GVGM) is established.
82
A Continuous Time Markov Chain Based Sequential Analytical Approach for Composite Power System Reliability Assessment
TL;DR: The results indicate that sequential reliability assessment can be performed by the proposed CTMC based sequential analytical approach, which is more efficient, especially in small scale or very reliable power systems.
81
Aggregation and Bidirectional Charging Power Control of Plug-in Hybrid Electric Vehicles: Generation System Adequacy Analysis
TL;DR: In this article, a bidirectional charging power control method, based on the time series model of PHEV charging, is developed to ensure that PHEVs achieve full-charge before the users' desired disconnecting time, and allows the spare time during users desired charging horizons to be used to manage PHEVcharging power and to respond to the generation capacity shortage signal.
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A spatial-temporal charging load forecast and impact analysis method for distribution network using EVs-traffic-distribution model
Yinchi Shao,Yunfei Mu,Xiaodan Yu,Xiaohong Dong,Hongjie Jia,Jianzhong Wu,Yuan Zeng +6 more
- 20 Sep 2017
TL;DR: A method for the forecast of charging load of electric vehicles (EVs) under “EVs-Traffic-Distribution” (ETD) system was developed to precisely manifest the spatial-temporal characteristics of large scale EV charging load in urban area and to evaluate the impact of the load on urban distribution network.
77
Optimal Integration of Building Heating Loads in Integrated Heating/Electricity Community Energy Systems: A Bi-Level MPC Approach
TL;DR: Numerical studies show that the bi-level MPC method can obtain a balanced scheduling scheme between the energy costs of consumers in buildings and the ICES operator's profits, and can ensure higher profits of the ICes operator and simultaneously, lower energy costs in buildings.