The Distributed Photovoltaic Demand Response Model Based on Security and Economy in Active Distribution Network
Automation, Control and Intelligent Systems
Volume 4, Issue 3, June 2016, Pages: 53-58
Received: Jun. 7, 2016;
Published: Jun. 8, 2016
Views 3421 Downloads 101
Li Lin, School of Electric Engineering and Automation, Hefei University of Technology, Hefei, China; CSG Smart Grid Electrical Technology CO., Ltd., Hefei, China
Cao Jun, CSG Smart Grid Electrical Technology CO., Ltd., Hefei, China
Tao Weiqing, School of Electric Engineering and Automation, Hefei University of Technology, Hefei, China
The technology of demand side response introduced in distributed photovoltaic power supply was proposed in this paper. Analyzing the applicability of demand response which established by distributed photovoltaic, presenting system implementation architecture and basic technical requirements. Without considering the input of energy storage equipment, establishing the demand response model in the active distributed network based on combination of power prediction, load forecasting and weather mode prediction. The technical characteristics of system power, load and environment was analyzed, and the security and economy of distributed generation integration was followed by analyzed. The model will improve the performance of renewable energy operation and consumption, the reliable and economic access capability of large-scale distributed photovoltaic system in the active distribution network.
The Distributed Photovoltaic Demand Response Model Based on Security and Economy in Active Distribution Network, Automation, Control and Intelligent Systems.
Vol. 4, No. 3,
2016, pp. 53-58.
Fan Mingtian, Zhang Zuping, Su Aoxue, et al. Enabling technologies for active distribution systems [J]. Proccedings of the CSEE, 2013, 33(22): 12-18.
Wang Chengshan, Sun Chongbo, Li Peng. Review and perspective on the optimization of active distribution network [J]. Electric Power Construction, 2015, 36(1): 8-15.
Liu Rui, Yang Jingfei, Cheng Haozhong, et al. Comprehensive evaluation of grid-connected distributed generation [J]. Proceedings of the CSU-EPSA, 2013, 25(1): 34-39.
Ding Ming, Wang Weisheng, Wang Xiuli, et al. A review on the effect of large-scale PV generation on powersystems [J]. Proceedings of the CSEE, 2014, 34(1): 1-14.
Yu Jiancheng, Chi Fujian, Xu Ke. Analysis of the impact of distributed generation on power grid [J]. Proceedings of the CSU-EPSA, 2012, 24(1): 138-141.
Zhao Yonghua, Fang Yongyi, Wang Na, et al. Research on the impacts on feeder automation by inverter-based distribution generation connected to the distribution network [J]. Power System Protection and Control, 2013, 41(24): 117-122.
Liu Jian, Zhang Xiaoqing, Tong Xiangqian, et al. Fault location for distribution systems with distributed generations [J]. Automation of Electric Power Systems, 2013, 37(2): 36-42.
Wang Fei, Duan Jiandong, Liu Wuji, et al. Protection for distribution network lines connected with multi distributed generations containing wind farm [J]. Power System Protection and Control, 2013, 41(10): 68-73.
Zhang Qian, Liao Qingfen, Tang Fei, et al. Steady state voltage stability assessment method of distribution network considering inter-connection of distributed generators [J]. Automation of Electric Power Systems, 2015, 39(15): 42-48.
Wang Xuqiang, Liu Guangyi, Zeng Yuan, et al. Analysis on the effects of Volt/Var control method considering distributed generation [J]. Power System Protection and Control, 2014, 42(1): 47-53.
Zhong Qing, Gao Xinhua, Yu Nanhua, et al. Accommodating capacity and mode of distributed generation under harmonic constraint in active distribution networks [J]. Automation of Electric Power Systems, 2014, 38(24): 108-113.
Liu Jian, Huang Wei. Analysis on grid-connectible capacity of distributed PV generation in case of PV generation distribution close to load distribution [J]. Power System Technology, 2015, 39(2): 299-306.
Huang Wei, Liu Jian, Wei Haokun, et al. Extreme capacity limitations of photovoltaic generators in distribution grids [J]. Power System Protection and Control, 2015, 43(3): 22-28.
Anand M P, Ongsakul W, Singh J G, et al. Impact of economic dispatch in a smart distribution network considering demand response and power market[C]// Energy Economics and Environment (ICEEE), 2015 International Conference on. IEEE, 2015: 1-6.
Soroudi A, Siano P, Keane A. Optimal DR and ESS Scheduling for Distribution Losses Payments Minimization Under Electricity Price Uncertainty[J]. IEEE Transactions on Smart Grid, 2015.
Zhao Huiying, Liu Guangyi, Jia Hongjie, et al. Analysis of demand response program based on refined models [J]. Power System Protection and Control, 2014, 42(1): 62-68.
Liu Guangyi, Zhang Kai, Shu Bin. Six actives and key technologies of active distribution network [J]. Electric Power Construction, 2015, 36(1): 33-37.
Zeng Ming, Han Xu, Li Bo. Study of demand response safeguard mechanism for active [J]. Electric Power Construction, 2015, 36(1): 110-114.
Zeng Bo, Yang Yongqi, Duan Jinhui, et al. Key issues and research prospects for demand-side response in alternate electrical power systems with renewable energy sources [J]. Automation of Electric Power System, 2015, 39(17): 10-18.
Wang Xifan, Xiao Yunpeng, Wang Xiuli. Study and analysis on supply-demand interaction of power system under new circumstances [J]. Proceedings of the CSEE, 2014, 34(29): 5018-5028.
Wang Z, Gu C, Li F, et al. Active Demand Response Using Shared Energy Storage for Household Energy Management [J]. Smart Grid IEEE Transactions on, 2013, 4(4): 1888-1897.
Zhu Lan, Yan Zheng, Yang Xiu, et al. Integrated resources planning in microgrid based on modeling demand response [J]. Proceedings of the CSEE, 2014, 34(16): 2621-2628.
Ge Shaoyun, Guo Jianyi, Liu Hong, et al. Impacts of electric vehicle’s ordered charging on power grid load curve considering demand side response and output of regional wind farm and photovoltaic generation[J]. Power System Technology, 2014, 38(7): 1806-1811.
Li Chunyan, Xu Zhong, Ma Zhiyuan. Optimal time-of-use electricity price model considering customer demand response [J]. Proceedings of the CSU-EPSA, 2015, 27(3): 11-16.
Liu Jidong, Han Xueshan, Han Weiji, et al. Model and algorithm of customers’ responsive behavior under time-of-use proce [J]. Power System Technology, 2013, 37(10): 2973-2978.
Dong Kaisong, Ding Yan, Xie Yongtao, et al. Market optimization model for microgrid with demand response [J]. High Voltage Apparatus, 2015, 51(6): 122-126.
Zhang Liying, Meng Lingjia, Wang Zezhong. Photovoltaic power station output power prediction based on the double BP neural network [J]. Electrical Measurement & Instrumentation, 2015, 52(11): 31-35.
Zhu Yongqiang, Tian Jun. Application of least square support vector machine in photovoltaic power forecasting [J]. Power System Technology, 2011, 35(7): 54-59.
Ding Ming, Xu Ningzhou. A method to forecast short-term output power of photovoltaic generation system based on markovchain [J]. Power System Technology, 2011, 35(1): 152-157.
Jayaweera D, Islam S. Security assessment in active distribution networks with change in weather patterns[C]// International Conference on Probabilistic Methods Applied To Power Systems. IEEE, 2014.
Zhou Chao, Xing Wenyang, Li Yulong. Summarization on load forecasting method of electrical power system [J]. Journal of Power Supply, 2012(6): 32-39.