A novel bi-level robust game model to optimize a regionally integrated energy system with large-scale centralized renewable-energy sources in Western China

To improve the economics and scheduling flexibility of regionally integrated energy system (RIES) with large-scale centralized renewable energy, a bi-level robust game model is proposed. The model relies on the CCHP units and virtual energy-plant, uses their complementary of various energy to stabilize the uncertainty of power generation and consumption. The revenue and loss risk for coupling multiple uncertain is considered, and the uncertain set is constructed by robust theory, which can be flexibly adjusted its boundaries. Aim at the above-mentioned complex model, such as multi-objective, non convex, strong constraint, large-scale decision variables, and irregular Pareto front shape, a multi objective whale optimization algorithm is proposed. Finally, a modified IEEE-33 bus distribution system and the Hami power grid (in Western China) are used for cases. The sensitivity for scheduling results is quantitatively analyzed, under the influence of power generation and consumption uncertainty. The results show that the strategy can balance the economy and robustness, improve the profit benefit of RIES by 15.67% with the traditional robustness, virtual energy-plant can increase the profit by 1.9%. This paper provides theoretical guidance for the optimal scheduling of RIES with large-scale renewable energy. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

A bi-level robust game model is proposed in this paper to improve the economics and scheduling flexibility of regionally integrated energy system with large-scale centralized renewable energy. By utilizing the complementary of various energy sources to stabilize the uncertainty of power generation and consumption, the strategy can balance the economy and robustness, leading to an increase in profit benefit for RIES.