Published October 2014 | Version v1
Journal article

A study on the characteristics, predictions and policies of China's eight main power grids

  • 1. School of Statistics, Dongbei University of Finance and Economics, Dalian 116025 (China)
  • 2. School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China)
  • 3. Department of Statistics, Florida State University, Tallahassee, FL 32306-4330 (United States)

Description

Highlights: • Indian blackout is analyzed as a warning for China's power system. • Issues and recommendations of China's eight power grids are presented. • Five models are employed for scenario analysis on power generation and consumption. • The optimized combined model outperforms other models. • Methods towards balancing power generation and environmental impacts are proposed. - Abstract: Electricity is an indispensable energy source for modern social and economic development. However, large-scale blackouts can cause incalculable loss to society. In 2012, three major Indian power grids collapsed, resulting in the interruption of the electricity supply to over 600 million people. To avoid an event like that, China needs to forecast the power generation and consumption of eight power grids effectively. This paper first analyzes the characteristics of eight power grids and then proposes a combined model based on three improved grey models optimized by a differential evolution algorithm to predict electricity production and consumption of each power grid. The optimized combined forecasting model provides a better prediction than other models, and it is also the most workable and satisfactory model. Experiment results show electricity production and consumption would increase. In consideration of the real situation and existing problems, some suggestions are proposed. The government could decrease thermal power and exploit renewable energy power, like hydroelectric power, wind power and solar power, to ensure the safe and reliable operation of China's major power grids and protect environment

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2014.06.045

Additional details

Identifiers

DOI
10.1016/j.enconman.2014.06.045;
PII
S0196-8904(14)00570-6;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
86
Journal Page Range
p. 818-830
ISSN
0196-8904
CODEN
ECMADL

Optional Information

Copyright
Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.