Energy Hub Sizing in Multi-carrier Energy Networks

The strategic use of natural gas, electric power, and heat in a cascading manner can yield synergistic effects, potentially leading to the development of integrated energy systems. In these infrastructures, the energy hub serves as the critical link among various energy systems, performing essential functions of energy production, conversion, and storage. The capacity of the energy hub significantly impacts the degree of integration among these systems and the flexibility of the overall system’s operations. This chapter introduces a data-driven two-stage distributionally robust model for energy hub capacity planning using an ambiguity set by the Kullback-Leibler divergence. The model aims to minimize the overall expenditure by reducing the construction cost and the expected life-cycle operating cost under the worst-case distribution confined within the ambiguity set. Leveraging duality theory and sampling average approximation, the proposed model is converted into an equivalent convex program with a nonlinear objective and linear constraints. This is then solved using an outer approximation algorithm, which only requires the solution of a linear programming problem. This chapter introduces the work in Cao et al. (2020).