4.7 Article

Techno-economic analysis of a coal-fired CHP based combined heating system with gas-fired boilers for peak load compensation

Journal

ENERGY POLICY
Volume 39, Issue 12, Pages 7950-7962

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.enpol.2011.09.050

Keywords

Techno-economic analysis; Combined heat and power; Combined heating system

Funding

  1. Eleventh Five-Year-Plan of China [2006BAJ01A04]
  2. China Scholarship Council (CSC)

Ask authors/readers for more resources

Combined heat and power (CHP) plants dominate the heating market in China. With the ongoing energy structure reformation and increasing environmental concerns, we propose gas-fired boilers to be deployed in underperforming heating substations of heating networks for peak load compensation, in order to improve both energy efficiency and environmental sustainability. However, due to the relatively high price of gas, techno-economic analysis is required for evaluating different combined heating scenarios, characterized by basic heat load ratio (beta). Therefore, we employ the dynamic economics and annual cost method to develop a techno-economic model for computing the net heating cost of the system, considering the current state of the art of cogeneration systems in China. The net heating cost is defined as the investment costs and operations costs of the system subtracted by revenues from power generation. We demonstrate the model in a real-life combined heating system of Daqing, China. The results show that the minimum net heating cost can be realized at beta=0.75 with a cost reduction of 16.8% compared to coal heating alone. Since fuel cost is the dominating factor, sensitivity analyses on coal and gas prices are discussed subsequently. (C) 2011 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available