The power fluctuations and utilization of renewable energy sources (RESs) in green seaports call for more flexible facilities to reduce their overall operation costs and carbon emissions. This paper proposes a robustly coordinated operation strategy for the multiple types of energy storage systems in the green-seaport energy-logistics integrated system to minimize the daily operation cost and carbon emission under the carbon trading policy, considering the uncertain power of local loads (LLs), photovoltaics (PVs), as well as wind turbines (WTs). At the day-ahead decision stage, the power of all energy storages, electro-thermal conversion (ETC) unit, reefer containers, quay cranes (QCs), yard cranes (YCs) are optimized under the worst case. At the intra-day decision stage, the power of tie line (TL), PVs, and WTs are determined sequentially according to short-leading-time predictions of uncertain values. The day-ahead optimization is formulated as a robust optimization problem solved by column-and-constraint generation (C&CG) algorithm, whereas the intra-day optimization is solved as a deterministic optimization problem. Numerical simulations are carried out to verify the effectiveness of the proposed strategy. Simulating results show that the proposed strategy can achieve the lowest cost and guarantee the feasibility of the operation scheme under different scenarios.

It is significant to explore the flexible regulation ability of microgrids for accepting distributed renewable energy. This paper proposes a coordinated energy dispatch and flexibility support method for microgrids. Firstly, set up the aggregator to combine microgrids into the microgrid cluster. Then, the Stackelberg game model is constructed to analyze the interaction between microgrids and the microgrid cluster. As the leader, the aggregator guides microgrids to participate in demand-side response by using internal electricity price incentives. As followers, microgrids change their demand according to electricity prices and provide flexible peak-shaving services. By optimizing the electricity price, all participants in the game can obtain higher returns. Moreover, to improve the market competitiveness of flexibility services provided by the microgrid cluster, a real-time flexibility dispatching model is established, thereby reducing the main grid flexibility dispatch cost. Numerical results demonstrate that the proposed method can effectively enhance the system's flexibility and economy. Compared to directly trading with the superior power grid, the revenue of the microgrid cluster has increased by 2.37%, and the flexible supply capacity has improved by 11.88%.

The increasing penetration of renewable energy sources (RESs) in modern green seaports calls for more flexible management approaches that can minimize the daily seaport operation costs and RES curtailments. This paper establishes an optimal strategy in two-time intervals for flexible operations of energy storage systems and combined electric-thermal power demands of reefer containers in the coordinated green-seaport energy-logistics systems (ELS). For the day-ahead operation, a multi-stage stochastic optimization model is established to minimize the expected ELS operation cost according to the 24-hour-ahead forecasts. Uncertainties of RES power outputs, load demands, electricity prices, and ambient temperatures are considered in the optimization of day-ahead operation. For the intra-day operation, hydrogen, battery, and thermal storage systems as well as reefer containers operations are optimized based on the short-lead-time forecasts. Numerical simulations are carried out based on the Jurong seaport operation in Singapore to verify the effectiveness of the proposed optimal operation strategy for the coordinated green-seaport ELS. Simulation results reveal that the proposed strategy can achieve the lowest operation cost and the lowest RES curtailment in a green-seaport.

The neglect of the history depreciation imbalance in the conventional equalization strategies may aggravate the lifetime depreciation of the multi-battery energy storage systems (MBESSs) and overuse the high-history-depreciation batteries (HHDBs). This paper proposes an equalization strategy using maximum consistency tracking algorithm of the conditional depreciation to solve the stated problem. Conditional depreciation is innovatively defined to evaluate the operation equitability of the MBESSs. The maximum consistency tracking algorithm consists of two searching levels: the global searching level and the range searching level. A sequential approximation method is utilized at the global searching level to find the variation range consisting of the most equitable conditional depreciation. The newton downhill method is adopted at the range searching level to find the exact value of the most equitable conditional depreciation. The proposed equalization strategy is validated by a hardware-in-the-loop simulation system. Test results show that the proposed equalization strategy minimizes the imbalance of batteries' conditional depreciations and decreases the HHDBs' sharing power. Compared to the conventional equalization strategies, the proposed equalization strategy will protect the HHDBs from intermittent overuse and extend the lifetime of the MBESSs.