Distributionally robust energy-transportation coordination in coal mine integrated energy systems

In this paper, a coordinated operation approach is proposed for scheduling the energy-transportation coupled coal mine integrated energy system (CMIES) under diverse uncertainties. As the coupling equipment in the coal transportation network (CTN) and the CMIES, the belt conveyors are able to coordinate the coal delivery scheduling and energy management. However, lacking the CTN modelling remains an unsolved challenge. Firstly, this paper proposed a novel energy-transportation coordinated model, consisting of the radial CTN and second-order cone programming (SOCP) relaxed CMIES. To address uncertainties from renewable energy gen-eration output and raw coal production, the distributionally robust optimization (DRO) method is applied under the two-time scale operation framework to overcome the drawbacks of robust optimization and stochastic programming. The first timescale, i.e., the day-ahead scheduling, is focused on energy dispatching at long time intervals while the second scale i.e., the intra-day. scheduling, deals with uncertainties at short time intervals. Specifically, an event-wise Wasserstein ambiguity set is devised to handle the issue of probability distribution function information requirement, which is hard to obtain in practice. Finally, a real case of CMIES is simulated to validate the effectiveness of our proposed model and method. The results reveal that our method can effectively enhance the operational economy, realize decarbonization, and fulfill the coal transportation continuity compared to conventional methods.

Automated summary

In this paper, a coordinated operation approach is proposed for scheduling the energy-transportation coupled coal mine integrated energy system (CMIES) under diverse uncertainties. The belt conveyors in the coal transportation network (CTN) and the CMIES are used to coordinate coal delivery scheduling and energy management. A novel energy-transportation coordinated model is proposed, which consists of the radial CTN and second-order cone programming (SOCP) relaxed CMIES. The aim is to overcome the challenges of robust optimization and stochastic programming by applying the distributionally robust optimization (DRO) method.