In view of the coexistence of randomness and fuzziness for the natural gas based distributed combined cooling

heating and power(CCHP)system load

effective extraction of its uncertain characteristics is of great significance for system optimum scheduling and operation. A random and fuzzy modeling method is proposed. First

based on historical CCHP cold/heat/electricity load data

it has been found that the probability distribution characteristics can be described by weighted sum of n-stage normal distribution

and the probability density functions of electricity load and cold/heat load are obtained. Further

the function parameters are analyzed and found without complete statistical property but epistemically obscure. By extracting the characteristics of the membership function and the credibility density function of parameters

the electricity load and cold/heat load are defined as random-fuzzy variables. Based on following the thermal load(FTL)

the coupling characteristics between electric load and cool/heat load are analyzed

so the random-fuzzy model for daily exchange power of CCHP with power system is proposed and the corresponding random-fuzzy simulation method given. Case study is carried out based on operation and load data from a CCHP connected to a 10 kV bus in a city in Hunan Province

The effectiveness and validity of the proposed model is proved by simulation results. This work is supported by National Natural Science Foundation of China(No. 51277015)