Uncertainty Modeling in Operation of Multi-carrier Energy Networks

Abstract

Multi-carrier energy systems (MESs) provide various types of energy to customers like natural gas, electricity, cool, and heat. The interdependency among natural gas, heating, and power systems is rising due to the extensive growth of electrically powered heating facilities and cogeneration systems. Energy hub (EH) performs as a transitional agent amid consumers and suppliers. Therefore, multi-energy incorporation is a prevailing tendency and the EH is supposed to perform a pivotal role in allotting energy sources more effectively. The influence of MESs in distribution systems attracts more and more researchers. The MESs’ uncertainties need to be addressed using efficient methods. This book chapter introduces the interval optimization to deal with the uncertainties. The uncertainties are modeled as interval numbers. Pessimistic predilection ordering and EHs’ pessimism levels are implemented in the optimization in order to make the comparison of interval numbers. The interval optimization minimizes the total cost interval instead of the worst-case scenarios in the robust optimization. It performs computationally better than stochastic optimization, as well. In comparison with the stochastic optimization, a precise probability distribution of random variables is not needed in the interval optimization. Further, it can diminish computational complexity. In this chapter, the stochastic optimization and interval optimization methods are being conducted for evaluation.