Semimonthly

ISSN 1000-1026

CN 32-1180/TP

+Advanced Search 中文版
Modeling Method of Load Combination Optimization for Electricity Retailer Considering Coordination of Power Generation and Consumption
Author:
Affiliation:

1.Electric Power Research Institute of China Southern Power Grid Co., Ltd., Guangzhou 510080, China;2.School of Electrical Engineering, Southeast University, Nanjing 210096, China

Abstract:

Under the environment of power market, it is an important research topic how to make optimization strategy to maximize electricity benefits for electricity retailers according to electricity consumption characteristics of users. Aiming at the electricity retailers considering the coordination of power generation and consumption in medium- and long-term markets, the model of load combination optimization considering the benefits of electricity purchase and sale for electricity retailers is put forward. The demand response technology is further considered to optimize the integrated load characteristics of users. The benefits of electricity purchase and sale for electricity retailers is maximized in the market environment. At the same time, aiming at the load rebound problem of the demand response, a three-stage load rebound model is adopted. And a improved rolling optimization model considering load rebound is constructed to readjust the load value of demand response for users, which improves the load characteristics of demand response for combined users with the load rebound of demand response. Finally, the proposed model and strategy are simulated and analyzed based on the load data of industrial user group in a city of China in 2017, which verifies the effectiveness of the model

Keywords:

Foundation:

This work is supported by China Southern Power Grid Co., Ltd. (No. ZBKJXM20170079).

Get Citation
[1]XIAO Yong, WANG Yan, QIAN Bin, et al. Modeling Method of Load Combination Optimization for Electricity Retailer Considering Coordination of Power Generation and Consumption[J]. Automation of Electric Power Systems,2020,44(20):148-156. DOI:10.7500/AEPS20200628013
Copy
Share
History
  • Received:June 28,2020
  • Revised:July 23,2020
  • Adopted:
  • Online: October 16,2020
  • Published: