Bi-Level Optimal Design of Integrated Energy System With Synergy of Renewables, Conversion, Storage, and Demand

Abstract

Integrated energy systems (IESs) that combine biogas, solar, and wind energy sources demonstrate considerable potential for effective utilization of renewable energy, which is instrumental for achieving carbon neutrality. The enhancement in their energetic and economic performances relies on optimal design methods that need to consider the combined optimization of capacity and operation and synergy between biogas production, energy conversion, storage, and demand. Therefore, this study proposes a bi-level optimal design method for a biogas–solar–wind IES. First, an exergy hub model is established to accurately describe the variations in the energy quantity and quality resulting from energy conversion processes. Then, the combined capacity and operation optimization problem of the IES is formulated as a bi-level iterative model, and a full-time-series clustering method based on multi-attribute weighting is employed to obtain typical source–load scenarios. The first level is designed to maximize the cost and exergy savings and determine the rated capacities of renewables, energy conversion and storage components; the second level synergistically optimizes the operation schemes of energy conversion, storage, and demand components by incorporating a thermodynamic model of biogas production along with an electrical demand response program. And the iterative optimization mechanisms between these two levels are established. Moreover, a hybrid algorithm combining a genetic algorithm and sequential quadratic programming method is developed to solve the bi-level model. Finally, the feasibility and effectiveness of the proposed method are verified through case studies.