Time-of-use pricing model based on power supply chain for user-side microgrid

被引:44
作者
Zhou, Kaile [1 ,2 ,3 ]
Wei, Shuyu [1 ,2 ]
Yang, Shanlin [1 ,2 ]
机构
[1] Hefei Univ Technol, Sch Management, Hefei, Anhui, Peoples R China
[2] Hefei Univ Technol, Minist Educ, Key Lab Proc Optimizat & Intelligent Decis Making, Hefei, Anhui, Peoples R China
[3] City Univ Hong Kong, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Time-of-use pricing; User-side microgrid; Distributed energy storage; Power supply chain; DEMAND RESPONSE; OPTIMIZATION; MANAGEMENT; TRANSMISSION; SYSTEMS; STORAGE;
D O I
10.1016/j.apenergy.2019.04.076
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The user-side microgrid offers great potential for improving energy efficiency. This flexible and small-scale power system is characterized by multiple types of clean power supplies. The power supply chain can reveal the supply-demand relationships in the series of steps from power generation to consumption. However, electricity prices tend to vary and can significantly affect the actual energy costs to end-users and other entities in the power supply chain. In this study, we propose an optimization model of time-of-use pricing for the user-side microgrid from the perspective of power supply chain management. The objective of this model is to minimize the total cost of the power supply chain and optimize the charging-discharging behaviors of end-users. First, to reduce the impact of demand amplification and variation, we investigated the bullwhip effect of the power supply chain. Then, we considered distributed energy storage as an important component of the user-side microgrid and how electric power companies can utilize pricing strategies to optimize the charging-discharging behaviors of end-users. We performed experiments based on two scenarios that assumed end-users with and without distributed energy storage devices. A comparative analysis of the modelling results indicates that optimal time-of-use pricing can support the charging-discharging behaviors of residential users and reduce the cost of the entire electric power supply chain. The optimized time-of-use price is important for stability, flexibility, and efficiency improvement in both the user-side microgrid and the entire power supply chain.
引用
收藏
页码:35 / 43
页数:9
相关论文
共 51 条
[1]   A summary of demand response in electricity markets [J].
Albadi, M. H. ;
El-Saadany, E. F. .
ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (11) :1989-1996
[2]   Optimal Smart Home Energy Management Considering Energy Saving and a Comfortable Lifestyle [J].
Anvari-Moghaddam, Amjad ;
Monsef, Hassan ;
Rahimi-Kian, Ashkan .
IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (01) :324-332
[3]   Hierarchical Structure of Microgrids Control System [J].
Bidram, Ali ;
Davoudi, Ali .
IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (04) :1963-1976
[4]   Information Transmission and the Bullwhip Effect: An Empirical Investigation [J].
Bray, Robert L. ;
Mendelson, Haim .
MANAGEMENT SCIENCE, 2012, 58 (05) :860-875
[5]   Demand-Side Management System for Autonomous DC Microgrid for Building [J].
Chauhan R.K. ;
Phurailatpam C. ;
Rajpurohit B.S. ;
Gonzalez-Longatt F.M. ;
Singh S.N. .
Technology and Economics of Smart Grids and Sustainable Energy, 2 (1)
[6]   Modified penalty function method for optimal social welfare of electric power supply chain with transmission constraints [J].
Chen, Meng-Jen ;
Hsu, Yi-Fan ;
Wu, Yu-Chi .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 57 :90-96
[7]   Optimal scheduling of a microgrid in a volatile electricity market environment: Portfolio optimization approach [J].
Chen, Y. ;
Trifkovic, M. .
APPLIED ENERGY, 2018, 226 :703-712
[8]   Demand Side Management Using Time of Use and Elasticity Price [J].
Costa, A. ;
Galvis, J. C. .
IEEE LATIN AMERICA TRANSACTIONS, 2016, 14 (10) :4267-4274
[9]   Economic-energy-environment analysis of prospective sugarcane bioethanol production in Brazil [J].
de Carvalho, Ariovaldo Lopes ;
Antunes, Carlos Henggeler ;
Freire, Fausto .
APPLIED ENERGY, 2016, 181 :514-526
[10]   The optimization of demand response programs in smart grids [J].
Derakhshan, Ghasem ;
Shayanfar, Heidar Ali ;
Kazemi, Ahad .
ENERGY POLICY, 2016, 94 :295-306