Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch

The electric power, gas, and heat systems work on different but complementary time and space scales. Multiple energy systems (MES) yields an increase on the efficiency and flexibility of energy supply. The coupling between different forms of energy bring difficulties in the planning of the overall energy system. This paper proposes a novel optimal planning method for a community level MES that jointly determines the optimal generation, conversion and delivery of electricity, heat, cooling, and other services. First, configuration planning of a community level MES is introduced and defined using the energy hub (EH) concept. Then, the planning problem is presented with the objective of minimizing the sum of the investment and operating costs, with variables that represent the selection of energy converters or storage and their relationships. The model is then formulated as a mixed-integer linear programming (MILP) problem based on graph theory. The proposed model does not requires any pre-assumptions on the configurations of the EH so that it can plan the MES starting from scratch. Finally, an illustrative example is provided to describe the functioning of our proposed method. A numerical case study for the planning of a subsidiary administrative center in Beijing, China is presented to demonstrate the effectiveness and superiority of the proposed method.