Optimal Planning of Integrated Energy System Considering Convertibility Index

Abstract

Nowadays, developing an integrated energy system (IES) is considered as an effective pattern to improve energy efficiency and reduce energy supply costs. This study proposes a new index—convertibility index (CI)—to quantitatively assess the flexibility of the IES regarding the energy conversion processes between different energy flow types. Based on the CI constraint, a planning problem is modeled as a bi-level optimization problem. To solve the proposed bi-level problem, a hybrid genetic algorithm (GA)—MILP algorithm—is developed. A case study is carried out to verify the effectiveness of the proposed method. The results show that the total cost of the IES will increase with the CI constraint. For a given case study, the total cost increases by 26.2% when the CI decreases to 0.7 and increases by 3.7% when the CI increases to 1.6. Sensitivity analysis shows that the total numbers and capacities of conversion devices show an overall increasing trend with the increase in the CIs. Meanwhile, the total cost decreases quickly at first and then slightly increases, which, in a whole, shows a “Nike” shape. With different CI constraints, the IES MW per CI ranges from 31.8 to 37.5 MW, and the average cost increase is 2.229 million yuan (2.1%/0.1 CI).