The rising demand for green energy to reduce carbon emissions is accelerating the integration of renewable energy sources (RESs) like wind and solar power. However, this shift presents significant challenges due to the inherent variability and intermittency of RESs, which impact power system stability and reliability. As a result, there is a growing need for enhanced flexibility to maintain stable and reliable operations. This study reviews recent advancements in power system flexibility enhancement, particularly concerning the integration of RESs, with a focus on the critical role of energy storage systems (ESSs) in mitigating these challenges. ESSs play a vital role in addressing the variability of RESs, supporting grid stability, and enabling energy consumption time shifting. While existing studies discuss power system flexibility, each typically addresses specific aspects. This comprehensive review evaluates flexibility measures for renewable-based electricity in terms of reliability and stability, highlighting the importance of ESSs in transmission, distribution networks, and end-user applications like residential buildings and vehicle-to-grid technologies to enhance overall system flexibility. Additionally, we identify recent challenges, such as the increased risk of grid congestion, frequency deviations, and the need for real-time supply and demand balancing, which necessitate innovative ESS applications. We propose future directions, including a transition pathway to promote the large-scale deployment of diverse ESS technologies to support grid modernization, enhance resilience, and foster sustainable power supply development. Our findings emphasize the growing research into optimizing power system stability and reliability, offering valuable guidance for future research and practical implementation.

This paper presents a novel coordinated energy management approach for hybrid AC/DC distribution system with microgrid clusters considering multiple market players, which is modeled as a bi-level optimization problem by using non-cooperative game theory and robust optimization. The hybrid AC/DC distribution network and each microgrid are regarded as different entities, which are in the upper/lower level of the model, respectively. Considering the uncertainty of renewable energy, two-stage robust optimization is added in the bi-level optimization problem to suppress the influence of uncertainty on power interaction and achieve the minimum operation costs of each entity under uncertainty. Furthermore, In the upper level model, hybrid AC/DC distribution network can control power flow in real time, promote power interaction between entities, and reduce operation cost under uncertainty by using effective control of converter station and diesel generator. And each microgrid has dealt with the impact of uncertainty on the power interaction by reasonably managing the charge/discharge of energy storage, which realizes its own minimum operation cost. The proposed model can be transformed into mathematical programming with complementarity constraints (MPCC) by using Karush-Kuhn-Tucker conditions. Finally, numerical cases on an improved IEEE 33-bus hybrid AC/DC distribution system show the effectiveness of the proposed method.

Linear droop control can realize power sharing among generators in DC microgrid without relying on critical communication links. However, the droop relationship between output power and voltage magnitude of renewable power generate system is nonlinear with uncertainties and disturbances from renewable sources and loads in practical DC microgrid. A novel droop scheme is proposed for an isolated DC microgrid to solve the nonlinear problem. The control strategy is proposed by using the Takagi-Sugeno (T-S) fuzzy model and sliding mode algorithm. The nonlinear droop characteristics can be represented by T-S model through taking advantage of locally measured output variables. The sliding mode droop controller is designed for compensating the uncertainties and disturbances to derive accurate power sharing based on T-S fuzzy model. The proposed scheme is proved to be effective under variable operating conditions through PSIM/Matlab simulation.

Wind power plays an important role for the development of renewable energy. Due to the variable wind power, parameter uncertainties and system disturbances, the voltage deviation of wind-diesel power system may become larger, which can lead to the unstable operation of power system. Therefore, the novel control strategy is proposed for the load side converter (LSC) of double-fed induction generator (DFIG) to improve the stability in the power system, which is designed by taking advantage of adaptive sliding mode (SM) method and sliding mode observer (SMO). Moreover, the SMO is constructed to estimate the LSC state variables according to the established mathematical state model. In addition, the reactive power controller including two parts is constructed for LSC based on the estimated state variable through adaptive SM algorithm. One is the designed SM controller using the estimated state variables and state control model. The other part is micro-regulated part and the control signal is provided by using fuzzy algorithm on basis of the system voltage deviation online. Experiment studies are performed by using RTDS to validate the effectiveness of the proposed strategy for isolated wind-diesel hybrid power system under different operating conditions.