Probabilistic multi-energy flow calculation method for integrated heat and electricity systems considering correlation of source–load power

Abstract

There are many types of sources and loads in the electricity-heating coupling integrated energy system, and there are correlation characteristics between different energy sources, between loads, and between energy sources and loads, and the uncertainty of source and load is becoming more and more significant. In this regard, a calculation method of electricity-heating coupling probabilistic multi-energy flow considering the correlation and uncertainty of input variables is proposed in this paper. Firstly, the uncertainty probability models of wind power generation, photovoltaic generation, solar heat pump, heat load, and electricity load are established respectively; Secondly, the triangular fuzzy number is proposed to describe the correlation between variables, and the fuzzy correlation model of random variables of source and load is established by means of Gauss–Hermite integral and Nataf inverse transformation; Finally, the output state variables are fitted using the cumulant method and Cornish–Fisher series expansion to obtain the probability distribution of the output variables. The feasibility and effectiveness of the proposed method is verified by using an electricity-heating coupling integrated energy system. At the same time, the influence of fuzzy correlation intervals and coefficient changes on the probability distribution of output variables, and the influence of heat load fluctuations on the nodal voltage probability distribution of the power supply system are analyzed.

Keywords

• Electricity-heating coupling multi-energy flow system
• Gaussian mixture model
• Fuzzy correlation
• Probabilistic multi-energy flow distribution
• Nataf transformation
• Cumulant method