To improve the utilization of flexible resources in microgrids and meet the energy storage requirements of the microgrids in different scenarios, a centralized shared energy storage capacity optimization configuration model for microgrids based on bi-level optimization is proposed. First, the response characteristics of the shared energy storage and controllable load in the resilience microgrid are analyzed, and the centralized shared energy storage operation mode meeting the regulatory demand of multi-scenarios is designed. Then, a bi-level optimal allocation model is constructed, which takes the maximum net income of centralized shared energy storage as the upper layer and the minimum payment cost of load in the microgrid as the lower layer. Furthermore, the multi-objective whale optimization algorithm is used to solve the bi-level optimization model. The results show that the shared energy storage can jointly meet the regulation demand of multi-scenarios by coordinating the transferable load and cuttable load in the microgrid and improving the utilization rate of shared energy storage.
Owing to the severe fossil energy shortage and carbon pollution, the extensive electrification of maritime transportation, represented by all-electric ships (AESs), has become an appealing solution to increase the efficiency and environmental friendliness of the industry. To improve energy utilization, not only renewable energy but also thermal energy has been introduced is used in AESs. However, various uncertainties that are associated with renewable energy and ship motions significantly inhibit and complicate the operation and navigation of multi-energy shipboard microgrids. Accordingly, a new coordination of optimal energy management and voyage scheduling is important in reducing both the costs and emissions of AESs. This overview characterizes shipboard microgrids and several emerging technical challenges related to joint power and voyage scheduling, and elucidates prospects for further research, based on a comprehensive survey of the relevant literature.
With the popularity of the electrification of marine transportation, strategic energy-saving and environment-friendly management is gaining more attention recently. This paper proposes a novel coordinated navigation routing and power generation scheduling model, which aims at making a compromise between investment cost, operation cost, and greenhouse gas emissions under the distributional robust ambiguity of photovoltaic. A maritime hybrid energy configuration that combines diesel generator (DG), battery energy storage system (BESS), fuel cell (FC), photovoltaic (PV), and the cold-ironing connection is presented with a real-world navigation routine from Dalian to Singapore, and the optimization problem is solved through a bi-level tri-objective differential evolution algorithm, where navigation parameters, ESS and FC capacity and weight between operation cost and emission functions, are optimized in the upper level and specific power generation scheduling is settled in the lower level. Six case studies are conducted to verify its effectiveness and accuracy, and the simulation results demonstrate the proposed method can further reduce the operation cost while minimizing air contamination.
Frontiers in Energy Research
Advanced Modeling and Methods for Renewable-dominated Power Systems Operations under Multiple Uncertainties