Lihong Ma’s research while affiliated with Energy Research Institute and other places

As the key equipment for smooth load and reliability improvement of independent microgrids due to its high controllability, it is of great significance to adopt reasonable operation and maintenance strategies to improve the safety and reliability of energy storage equipment. The existing O&M strategy has not considered the impact of charge and discharge loss of energy storage batteries, and insufficient utilization of its operating data will lead to high overall O&M costs of equipment. This paper proposes an operation and maintenance strategy considering the number of charging and discharging and loss of energy storage batteries, and verifies the effectiveness of the operation and maintenance strategy proposed in this paper based on the historical history of on-site operation and maintenance of a microgrid energy storage power station.

As the penetration of renewable distributed generation (RDG) continues to grow, the stochastic and intermittent nature of its output imposes significant challenges on distribution networks (DNs), such as source–load mismatch and voltage fluctuations, which seriously affects the safety and reliability of the system. Thus, this paper presents a stochastic optimal allocation method for a battery energy storage system (BESS) in the DN, with the consideration of annual load growth, BESS degradation, and DN operation, aiming to minimize the overall cost of DNs and harvest more renewable energy. Based on the rainflow-counting concept, BESS degradation is efficiently modeled and linearized to improve solvability. Additionally, to address the uncertainties of RDG outputs and loads, a stochastic optimization (SO) method is adopted. Furthermore, considering that a large number of integer variables of the BESS allocation model may cause a heavy computational burden, a feasibility pump-based solution algorithm is introduced to accelerate the solving speed. Finally, the effectiveness of the proposed BESS allocation method and the solution algorithm is verified on a 33-bus DN system through comparative analyses, showing high efficiency and performance.

In order to improve the reliability of electrical equipment for isolated microgrids in tropical islands, it is necessary to accurately assess the health status of key equipment to carry out differentiated operation and maintenance. We propose a health status assessment model that comprehensively considers multi-dimensional information such as equipment operating parameters, meteorological environment, operation and maintenance history, and equipment resume. Based on D-S evidence theory, multi-source data is fused and analyzed, and the effectiveness of the assessment model is verified using a diesel generator as an example. The results show that the defects of diesel generators are mainly concentrated in five major functional systems, including fuel, startup, heat dissipation, electrical, and motive power systems. Among them, the number of defects involving power and electrical systems is relatively large and the severity of defects is higher. About 40% of the defects involving environmental impacts. According to the defect type and experience, the health status under different defects is given, and then the trust allocation function is preset. The credibility of the integrated assessment results of diesel generator's health status is significantly improved compared to using single assessment information. Our study can provide a reference for the differentiated operation and maintenance of microgrid equipment in tropical islands.

Tropical islands frequently face energy supply shortages due to limitations imposed by their natural environment. The utilization of a single microgrid structure often leads to power instability and even network-wide failures. Interconnecting multiple microgrids and operating them in a clustered manner can effectively enhance the reliability of power supply. However, during the process of integrating a specific microgrid into the cluster, voltage magnitude and phase imbalances at the common connection points can give rise to transient stability issues. To address the aforementioned challenges, a microgrid cluster synchronization and integration strategy based on pre-synchronization control is proposed. The voltage magnitude of inverter outputs and the voltage vector of the microgrid cluster are transformed into the rotational coordinate system using Clark and Park transformations, thereby obtaining the phase angle and magnitude deviations of the voltages. With PI control employed, compensatory values for grid frequency and grid voltage are individually determined to ensure consistent voltage phase and magnitude between the pre-synchronization side and the microgrid cluster side. This approach effectively resolves voltage and frequency fluctuations during mode transitions, enabling smooth switching between the islanded and grid-connected modes of microgrid operation. Finally, the effectiveness of the proposed control strategy is verified through simulation to be a feasible solution for the smooth integration of a microgrid into microgrid clusters.