Optimal operation of combined heat and power system based on forecasted energy prices in real-time markets

Chenghong Gu, Da Xie, Junbo Sun, Xitian Wang, Qian Ai

Research output: Contribution to journalArticlepeer-review

21 Citations (SciVal)
145 Downloads (Pure)


This paper develops a discrete operation optimization model for combined heat and powers (CHPs) in deregulated energy markets to maximize owners' profits, where energy price forecasting is included. First, a single input and multi-output (SIMO) model for typical CHPs is established, considering the varying ratio between heat and electricity outputs at different loading levels. Then, the energy prices are forecasted with a gray forecasting model and revised in real-time based on the actual prices by using the least squares method. At last, a discrete optimization model and corresponding dynamic programming algorithm are developed to design the optimal operation strategies for CHPs in real-time. Based on the forecasted prices, the potential operating strategy which may produce the maximum profits is pre-developed. Dynamic modification is then conducted to adjust the pre-developed operating strategy after the actual prices are known. The proposed method is implemented on a 1 MW CHP on a typical day. Results show the optimized profits comply well with those derived from real-time prices after considering dynamic modification process.

Original languageEnglish
Pages (from-to)14330-14345
Number of pages16
Issue number12
Early online date18 Dec 2015
Publication statusPublished - Dec 2015


  • Combined heat and power (CHP)
  • Discrete optimization
  • Dynamic programming
  • Price forecasting
  • Real-time market


Dive into the research topics of 'Optimal operation of combined heat and power system based on forecasted energy prices in real-time markets'. Together they form a unique fingerprint.

Cite this