Spring-assisted triboelectric nanogenerators (S-TENGs) have emerged as effective energy harvesters of low-frequency, low-amplitude vibrations via resonance tuning, amplified relative motion, and enhanced contact force between triboelectric layers. Unlike conventional triboelectric nanogenerators (TENGs), S-TENGs uniquely harness elastic resonance through integrated spring structures to efficiently harvest low-frequency and subtle mechanical vibrations that are otherwise difficult to convert into electricity, thereby enhancing overall energy conversion efficiency. Recent innovations in triboelectric materials, electrode designs, and structures have enabled the development of high-performance TENGs for sustainable green energy. This review highlights the pivotal role of spring elements in improving S-TENG performance and provides design insights for constructing robust, self-powered, and maintenance-free sensing platforms. Diverse architectures include linear and multi-degree-of-freedom systems, as well as cantilever, tower, helical, magnetic, and composite designs. Each is engineered to optimize vibration response and maximize output performance, enabling it to be used as an independent power source. Hybrid triboelectric-electromagnetic integration, negative-stiffness mechanisms, and mechanical frequency regulation further extend the adaptability of S-TENGs to real-world conditions. Industrial equipment monitoring, wireless carbon dioxide sensing, omnidirectional vibration harvesting, and motor fault detection in unmanned aerial vehicles demonstrate the versatility and practical impact of S-TENGs.

With the continuous and rapid growth of global photovoltaic (PV) installed capacity, the fluctuation, intermittence, and randomness of its output aggravate the inertia loss of traditional power systems, which poses severe challenges to grid voltage stability, frequency regulation, and safe operation of equipment. Stability control of PV power stations has become a necessary aspect of technical support for the construction of new power systems (NPSs). In this paper, a technical analysis framework of stability control of photovoltaic power stations is systematically constructed. First, the core stability problems of photovoltaic systems are sorted out. Then, a technical review of the three control levels, namely the equipment, system, and grid, is carried out. At the same time, the application potential of emerging technologies such as data-driven and AI control, digital twin predictive control, and advanced grid-forming (GFM) inverters is described. Based on existing reviews, this paper proposes an equipment–system–grid hierarchical analysis framework and explicitly integrates emerging technologies with classical methods. This framework provides references for the selection, engineering deployment, and future research directions of stability control technologies for photovoltaic power plants, while also offering technical support for the safe and efficient operation of high-penetration renewable energy power grids.

Green hydrogen production and the use of fuel cells (FCs) in microgrid (MG) systems have become viable and feasible solutions due to their continuous cost reduction and advancements in technology. Furthermore, green hydrogen electrolyzers and FC can mitigate fluctuations in renewable energy generation and various demand-related disturbances. Proper incorporation of electrolyzers and FCs can enhance load frequency control (LFC) in MG systems. However, they are subjected to multiple false data injection attacks (FDIAs), which can deteriorate MG stability and availability. Moreover, most existing LFC control schemes—such as conventional PID-based methods, single-degree-of-freedom fractional-order controllers, and various optimization-based structures—lack robustness against coordinated and multi-point FDIAs, leading to significant degradation in frequency regulation performance. This paper presents a new, modified, multi-degree-of-freedom, cascaded fractional-order controller for green hydrogen-based MG systems with high fluctuating renewable and demand sources. The proposed LFC is a cascaded control structure that combines a 1+TID controller with a filtered fractional-order PID controller (FOPIDF), namely the cascaded 1+TID/FOPIDF LFC control. Furthermore, another tilt-integrator derivative electric vehicle (EV) battery frequency regulation controller is proposed to benefit from EVs installed in MG systems. The proposed cascaded 1+TID/FOPIDF LFC control and EV TID LFC methods are designed using the powerful capability of the exponential distribution optimizer (EDO), which determines the optimal set of design parameters, leading to guaranteed optimal performance. The effectiveness of the newly proposed cascaded 1+TID/FOPIDF LFC control and design approach employing multi-generational-based two-area MG systems is studied by taking into account a variety of projected scenarios of FDIAs and renewable/load fluctuation scenarios. In addition, performance comparisons with some featured controllers are provided in the paper. For example, in the case of fluctuation in RESs, the measured indices are as follows: ISE (1.079, 0.5306, 0.3515, 0.0104); IAE (15.011, 10.691, 9.527, 1.363); ITSE (100.613, 64.412, 53.649, 1.323); and ITAE (2120, 1765, 1683, 241.32) for TID, FOPID, FOTID, and proposed, respectively, which confirm superior frequency deviation mitigation using the proposed optimized cascaded 1+TID/FOPIDF and EV TID LFC control method.

Coordinated control strategies for frequency regulation in multi-area power grids with high proportion of hydropower

For the load frequency control (LFC) of a three-area hybrid power system, this study suggests an enhanced version of the Improved Parasitism Predation Algorithm (IPPA) method based on an adaptive type-2 fuzzy PID (AT2FPID) controller. The improved algorithm is first evaluated against the basic method in terms of execution time and solution quality using a few benchmark test functions. Additionally, an AT2FPID controller is set up to utilise the suggested method for regulating the frequency of the three-area hybrid system. When comparing the results of the proposed IPPA-based AT2FPID regulator with those of other existing approaches, the latter is more practical for frequency control. It is expected that, in terms of frequency control, the proposed hAOA-PS-based MSPID controller will perform better than traditional PID controllers. The proposed hAOA-PS-based MSPID controller achieves improvements of 27.82%, 60.02%, and 65.15% compared to the AOA-based MSPID, hAOA-PS-based PID, and AOA-based PID, respectively, shown in the simulation results.

The increasing integration of renewable energy systems (RESs) such as solar and wind into modern power grids using converter‐based, inertia‐less interfaces poses serious frequency stability challenges. This is due to reduced system inertia conventionally provided by synchronous generators. This paper proposes an innovative solution using an adaptive grid‐forming controller (AGFC), designed to emulate and adapt virtual inertia and damping in real time. The AGFC uniquely combines grid‐forming virtual inertia damping control with an adaptive DC link voltage regulation loop, coordinated by a genetic algorithm–optimized proportional integral (GA‐PI) controller. Key innovation lies in employing the GA‐PI control to dynamically manage DC link energy exchange during grid disturbances. Through optimized GA‐PI tuning, rapid adjustment of control parameters is achieved to maintain system stability during sudden load changes. MATLAB/Simulink simulations demonstrate that the proposed AGFC substantially mitigates frequency deviation, rate of change of frequency, and frequency settling time under transient conditions. Compared with conventional grid‐forming control without adaptive DC link management, the designed AGFC depicts superior resilience and adaptability to load disturbances. It enables inverters to autonomously establish voltage and frequency references while providing synchronous generator‐like stabilization. The results demonstrate that the proposed framework enhances the grid’s inertial response and dynamic stability for converter‐interfaced RES. Future research will explore scaling the AGFC for multiarea grids and applying advanced parameter optimization to larger systems. This is expected to further improve system‐wide frequency regulation and stability.

Fuzzy consensus controller for voltage and frequency regulation, power sharing, and SoC balancing in islanded AC microgrids

Hierarchical Flexibility Aggregation of Heterogeneous Demand-Side Energy Storages for Secondary Frequency Regulation

Coordinated fuzzy control of hybrid energy storage systems for enhanced secondary frequency regulation in power grids

Modified deep reinforcement learning for frequency regulation in active distribution systems with soft open points, storage units and electric vehicles

Analysis of Boiler Models for Primary Frequency Regulation Studies Considering Working Conditions

Online convex optimization strategy for frequency regulation of energy storage systems considering aging costs

Joint peak shaving and frequency regulation strategy for energy storage stations cluster considering battery dispatchable capacity

Virtual Power Plants for Frequency Regulation: A Learning-Based Method With Safety Guarantee

Stochastic cooperation strategy of multi-wind farms with shared energy storage for primary frequency regulation considering wind cluster effect

Load frequency regulation in renewable integrated multi-area cyber-physical power system considering nonlinearities and resonance attacks

A Slice Puncturing Scheme of Energy Storage Batteries for Grid Frequency Regulation

Abstract- The increasing penetration of power export corridors and renewable generation has intensified concerns related to transient voltage and frequency stability in large-scale interconnected power systems. To address these challenges, extensive research has been reported on the application of Battery Energy Storage Systems (BESS) and Flexible AC Transmission System (FACTS) devices such as Static Synchronous Compensators (STATCOM). This paper presents a comprehensive review of existing studies focusing on the role of BESS and STATCOM in improving transient stability performance and enhancing power transfer capability between interconnected transmission networks. Particular emphasis is placed on control strategies adopted for BESS, including proportional–integral (PI), PI-lead, and lead–lag controllers, and their effectiveness in maintaining voltage and frequency regulation within permissible battery state-of-charge limits. Reported investigations based on benchmark transmission networks, including equivalent large-scale grids, are analyzed in the context of grid code compliance under various temporary and permanent fault conditions. Additionally, the impact of sequential disturbance events and increased power export levels on system stability is discussed. The comparative assessment highlights that BESS can provide effective support during severe disturbances, especially under scenarios involving reduced availability of reactive power compensation devices such as STATCOM. Furthermore, literature indicates that advanced control schemes for BESS exhibit superior transient response characteristics compared to conventional control approaches. The review identifies key research gaps and motivates further detailed simulation-based investigations for coordinated stability enhancement in modern power systems. Key Words: optics, photonics, light, lasers, stencils, journals

The shift to renewable energy sources is a radical change in the power generation paradigm in the world and is supported by the necessity to reduce greenhouse gas emissions and spontaneously decrease climate change. This critical analysis looks at how the solar and wind energy systems can be optimized by using sophisticated battery storage technology and planning the integration of the systems within the grid. The discontinuous aspect of the renewable sources of energy is also a serious technical problem to the stability, power quality, and reliability of the grid. The battery energy storage system has become one of the most important enablers of renewable energy integration offering such important services as frequency regulation, voltages, and load balancing. The current work is comprehensive research on the modern trends in energy storage solutions, smart grid designs, and optimization of renewable energy solutions. The article analyses the different optimization methods such as artificial intelligence, predictive control system, and demand response. The findings indicate that battery storage systems that are integrated can improve the level of penetration of the renewable energy considerably without compromising the stability of the grid and the quality of power. The gaps in the research found in the study are in the fields of long-duration energy storage, grid-forming inverter technologies, and virtual power plant coordination.

This study presents a novel application of the Golden Jackal Optimization (GJO) algorithm for load frequency control (LFC) in a multi-source, two-area interconnected power system. The LFC model comprises of thermal, hydro, nuclear, gas, wind, and solar PV energy units. Inspired by the cooperative hunting strategies and dynamic adaptability of golden jackals, the GJO algorithm mimics their social behaviour and communication tactics to efficiently solve complex optimisation problems. The proposed LFC framework addresses key control objectives of frequency and tie-line power regulation, achieving acceptable transient performance with reduced computational time and iterations. Comparative analysis with established optimisation algorithms such as particle swarm (PSO), whale optimization (WOA), salp swarm (SSA), ant lion (ALO), harris hawk (HHA), and teaching learning (TLO) reveals the effectiveness of GJO, demonstrating improvements of atleast 21.9% in rise time, 5.04% in peak time, 22.1% in overshoot, and 9.7% in settling time across both areas. The robustness of the design is validated under various scenarios, including variable step load changes, system parameter variation, and the presence of nonlinearities such as generation rate constraints (GRC) and governor dead bands (GDB). Frequency domain stability analysis using Bode plots further validates the system’s stability.