An inexact fixed-mix fuzzy-stochastic programming model for heat supply management in wind power heating system under uncertainty

• An inexact fixed-mix fuzzy-stochastic programming model is developed.
• Uncertainties are expressed as interval values, random variables and fuzzy sets.
• Solutions associated with degrees of plausibility have been obtained.
• Tradeoffs between system benefit and reliability risks could be addressed.

To better utilize electricity generated by wind power in northern China and ease the strain on local energy grids in the winter, the National Energy Administration (NEA) is committed to promoting the development of wind power heating projects in areas where conditions are suitable. However, multiple uncertainties and complexities that exist in the processes of wind power generation and heat supply present substantial challenges to the stability of wind power heating system and put its operation into risk. Therefore, an inexact fixed-mix fuzzy-stochastic programming (IFFSP) method was developed and applied to the heat supply management of an actual wind power heating system under uncertainties presented as interval values, random variables and fuzzy sets within a multi-stage context. Interval solutions associated with plausibility degrees of constraint violation can help decision makers identify the optimal heat supply management strategies and gain a comprehensive tradeoff between economic objectives and reliability risks of system. Moreover, the feasibility of wind power heating project in promoting wind power consumption and relieving wind curtailment is studied, and the results indicated that the effect is limited. Finally, suggestions aimed on resolving issues of integration and consumption of wind energy are proposed.