Search Results (251)

In this work, the synthesis and structural characterization of the smallest possible member of the family of bis-functionalized {MnMo₆O₂₄} Anderson–Evans polyoxometalates (POMs) is reported. The synthesis of the title compound TBA₃{[HC(CH₂O)₃]₂MnMo₆O₁₈} (1) was accomplished by using trimethylolmethane as the capping unit (TBA: tetra(n-butyl)ammonium, n-B_u4N⁺). The molecular structure of the organic–inorganic POM gave rise to yet undisclosed ¹H-NMR features, which are discussed thoroughly. Single-crystal X-ray diffraction (XRD) analysis revealed a highly regular 3D packing of the polyoxoanions within a matrix of TBA cations. The hybrid POM is of particular interest regarding potential applications in photocatalysis (i.e., hydrogen evolution) and energy storage. Thus, the electrochemical and thermal properties of 1 are also analyzed. Full article

The West Africa Power Pool (WAPP) Interconnected Transmission System (WAPPITS) has faced challenges with frequency control due to limited primary frequency control reserves (PFRs). Battery Energy Storage Systems (BESSs) have been identified as a possible solution to address frequency control challenges and to support growing levels of variable renewable energy in the WAPPITS. This paper uses a dynamic PSS/E grid simulation to evaluate the effectiveness of BESSs and conventional power plants for the maximum N-1 contingency scenario in WAPPITS—the loss of 400 MW of generation. BESSs outperform conventional power plants in fast frequency response; a BESS-only PFR mix produces the best technical performance for the metrics analyzed. However, this approach does not have the best marginal cost; a balanced mix of BESSs and conventional reserves achieves adequate performance on all metrics to meet grid requirements. This hybrid approach combines BESSs’ rapid power injection with the lower cost of conventional units, resulting in improved nadir frequencies (e.g., 49.70–49.76 Hz), faster settling times (1.00–2.20 s), and cost efficiency. The study indicates that an optimal approach to frequency control should include a combination of regulatory reforms and coordinated reserve procurement that includes BESS assets. Regulatory reforms should require or incentivize conventional plant to provide PFRs, possibly through creation of a (new to WAPPITS) market for ancillary services. While not a comprehensive analysis of all variables, these findings provide critical insights for policymakers and system operators. Full article

This paper proposes a ladder carbon trading-based low-carbon economic dispatch model for integrated energy systems (IESs), incorporating flexible load optimization and hybrid energy storage systems consisting of battery and thermal energy storage. First, a ladder-type carbon trading mechanism is introduced, in which the carbon trading cost increases progressively with emission levels, thereby providing stronger incentives for emission reduction. Second, flexible loads are categorized and modeled as shiftable, transferable, and reducible types, each with distinct operational constraints and compensation mechanisms. Third, both battery and thermal energy storage systems are considered to improve system flexibility by storing excess energy and supplying it when needed. Finally, a unified optimization framework is developed to coordinate the dispatch of renewable generation, gas turbines, waste heat recovery units, and multi-energy storage devices while integrating flexible load flexibility. The objective is to minimize the total system cost, which includes energy procurement, carbon trading expenditures, and demand response compensation. Three comparative case studies are conducted to evaluate system performance under different operational configurations: the proposed comprehensive model, a carbon trading-only approach, and a conventional baseline scenario. Results demonstrate that the proposed framework effectively balances economic and environmental objectives through coordinated demand-side management, hybrid storage utilization, and the ladder-type carbon trading market mechanism. It reshapes the system load profile via peak shaving and valley filling, improves renewable energy integration, and enhances overall system efficiency. Full article

The rapid growth of electric vehicle (EV) adoption necessitates advanced energy management strategies to ensure sustainable, reliable, and efficient operation of charging infrastructure. This study proposes a hybrid AI-based framework for optimizing residential EV charging systems through the integration of Reinforcement Learning (RL), Linear Programming (LP), and real-time grid-aware scheduling. The system architecture includes smart wall-mounted chargers, a 120 kWp rooftop solar photovoltaic (PV) array, and a 60 kWh lithium-ion battery energy storage system (BESS), simulated under realistic load conditions for 800 residential units and 50 charging points rated at 7.4 kW each. Simulation results, validated through SCADA-based performance monitoring using MATLAB/Simulink and OpenDSS, reveal substantial technical improvements: a 31.5% reduction in peak transformer load, voltage deviation minimized from ±5.8% to ±2.3%, and solar utilization increased from 48% to 66%. The AI framework dynamically predicts user demand using a non-homogeneous Poisson process and optimizes charging schedules based on a cost-voltage-user satisfaction reward function. The study underscores the critical role of intelligent optimization in improving grid reliability, minimizing operational costs, and enhancing renewable energy self-consumption. The proposed system demonstrates scalability, resilience, and cost-effectiveness, offering a practical solution for next-generation urban EV charging networks. Full article

Grid stability in microgrids represents a critical challenge, particularly with the increasing integration of variable renewable energy sources and the loss of systematic inertia. This study analyzes the use of vehicle-to-grid (V2G) technology and supercapacitors as complementary solutions to improve grid stability. A hybrid approach is proposed in which electric vehicles act as temporary storage units, supplying energy to regulate grid frequency. Supercapacitors, due to their rapid charging and discharging capabilities, are used to mitigate power fluctuations and provide immediate support during peak demand. The proposed management model integrates two strategies for frequency control, leveraging the linear relationship between power and frequency. Power smoothing is combined with Kalman filter-based frequency control, allowing for accurate estimation of the dynamic system state, even in the presence of noise or load fluctuations. This methodology improves grid stability and frequency regulation accuracy. A frequency variability analysis is also included, highlighting grid disturbance events related to renewable-energy penetration and demand changes. Furthermore, the effectiveness of the Kalman filter in improving grid stability control, ensuring an efficient dynamic response, is highlighted. The results obtained demonstrate that the combination of V2G and supercapacitors contributes significantly to reducing grid disturbances, optimizing energy efficiency, and enhancing system reliability. Full article

Off-grid renewable energy hydrogen production is a crucial approach to enhancing renewable energy utilization and improving power system stability. However, the strong stochastic fluctuations of wind and solar power pose significant challenges to electrolyzer reliability. While hybrid energy storage systems (HESS) can mitigate power fluctuations, traditional power allocation rules based solely on electrolyzer power limits and HESS state of charge (SOC) boundaries result in insufficient energy supply capacity and unstable electrolyzer operation. To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. In Stage I, hydrogen production power and HESS initial allocation are determined through the deep coupling of real-time electrolyzer operating conditions with reserved energy. Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. The proposed method enhances hydrogen production stability and HESS supply capacity while reducing renewable curtailment rates and average production costs. Case studies demonstrate its superiority over three conventional rule-based power allocation methods. Full article

To date, two-dimensional metal–organic frameworks (2D MOFs) have attracted much attention in many fields. Owing to their ultra-high porosity and specific surface area, great structural diversity and functional tunability, as well as feasible precision design at the molecular level, 2D MOFs have won rapid development in the field of energy storage. However, as a coordination compound, MOFs possess poor structural stability and are prone to structural collapse in electrochemical reactions, which seriously limits their electrochemical performance. Therefore, there is an urgent need to improve the structural stability of MOF electrode materials. In this study, a 2D MOF@Ti₃C₂T_X hybrid was constructed, in which urea pyrimidinone isocyanate (UPy-NCO) units were introduced via a condensation reaction with the active functional groups on MOFs, thus forming multiple hydrogen bonds among MOF frameworks to strengthen their structural stability. Importantly, 2,6-diaminopyridine was utilized to modulate the structure and properties. Initially, the mono-coordination model of the N atom on a pyridine ring with metal ions could create defects and form further pores. Two −NH₂ groups helped to improve the grafting reaction degree of UPy-NCO, leading to an increased ratio of forming quadruple hydrogen bonds (H-bonds), further strengthening the structure of the hybrid. As expected, the Cu-MOF@Ti₃C₂T_X-20%DAP-UPy hybrid exhibited a specific capacitance of 148 F g⁻¹ at 1 A g⁻¹, which is 45% higher than that of Cu-MOF@Ti₃C₂T_X-UPy (102 F g⁻¹). A good capacitance retention of 88% was obtained as the current density increased from 0.2 to 5 A g⁻¹. Moreover, excellent cycling stability (91.1%) was obtained at 1 A g⁻¹ after 5000 cycles. Full article

This paper proposes a supercapacitor-battery hybrid energy storage scheme based on a series-parallel hybrid compensation structure and model predictive control to address the increasingly severe power quality issues in oilfield microgrids. By adopting the series-parallel hybrid structure, the voltage compensation depth can be properly improved. The model predictive control with a current inner loop is employed for current tracking, which enhances the response speed and control performance. Applying the proposed hybrid energy storage system in an oilfield DC microgrid, the fault-ride-through ability of renewable energy generators and the reliable power supply ability for oil pumping unit loads can be improved, the dynamic response characteristics of the system can be enhanced, and the service life of energy storage devices can be extended. This paper elaborates on the series-parallel compensation topology, operational principles, and control methodology of the supercapacitor-battery hybrid energy storage. A MATLAB/Simulink model of the oilfield DC microgrid employing the proposed scheme was established for verification. The results demonstrate that the proposed scheme can effectively isolate voltage sags/swells caused by upstream grid faults, maintaining DC bus voltage fluctuations within ±5%. It achieves peak shaving of oil pumping unit load demand, recovery of reverse power generation, stabilization of photovoltaic output, and reduction of power backflow. This study presents an advanced technical solution for enhancing power supply quality in high-penetration renewable energy microgrids with numerous sensitive and critical loads. Full article

The implementation of renewable energy systems (RESs) in the agricultural sector has significant potential to mitigate the negative effects of fossil fuel-based products on the global climate, reduce operational costs, and enhance crop production. However, the intermittent nature of RESs poses a major challenge to realizing these benefits. To address this, thermal energy storage (TES) and hybrid heat pump (HHP) systems are integrated with RESs to balance the mismatch between thermal energy production and demand. In pursuit of clean energy solutions in the agricultural sector, a 3942 m² greenhouse in Yeoju-si, South Korea, is equipped with 231 solar thermal (ST) collectors, 117 photovoltaic thermal (PVT) collectors, four HHPs, two ground-source heat pumps (GSHPs), a 28,500 m³ borehole TES (BTES) unit, a 1040 m³ tank TES (TTES) unit, and three short-term TES units with capacities of 150 m³, 30 m³, and 30 m³. This study evaluates the long-term performance of the integrated hybrid renewable energy and thermal energy storage systems (HRETESSs) in meeting the greenhouse’s heating and cooling demands. Results indicate that the annual system performance efficiencies range from 25.3% to 68.5% for ST collectors and 31.9% to 72.2% for PVT collectors. The coefficient of performance (COP) during the heating season is 3.3 for GSHPs, 2.5 for HHPs using BTES as a source, and 3.6 for HHPs using TTES as a source. During the cooling season, the COP ranges from 5.3 to 5.7 for GSHPs and 1.84 to 2.83 for ASHPs. Notably, the HRETESS supplied 3.4% of its total heating energy directly from solar energy, 89.3% indirectly via heat pump utilization, and 7.3% is provided by auxiliary heating. This study provides valuable insights into the integration of HRETESSs to maximize greenhouse energy efficiency and supports the development of sustainable agricultural energy solutions, contributing to reduced greenhouse gas emissions and operational costs. Full article

To address the frequency regulation requirements of hybrid energy storage (HES) in renewable-dominated power grids, this paper proposes an asymmetric droop control strategy based on an improved backpropagation (BP) neural network. First, a simulation model of HES (comprising supercapacitors for the power support and batteries for the energy balance) participating in primary frequency regulation is established, with a stepwise frequency regulation dead zone designed to optimize multi-device coordination. Second, an enhanced Sigmoid activation function (with controllable parameters a, b, m, and n) is introduced to dynamically adjust the power regulation coefficients of energy storage units, achieving co-optimization of frequency stability and State of Charge (SOC). Simulation results demonstrate that under a step load disturbance (0.05 p.u.), the proposed strategy reduces the maximum frequency deviation by 79.47% compared to scenarios without energy storage (from 1.7587 × 10⁻³ to 0.0555 × 10⁻³) and outperforms fixed-droop strategies by 44.33%. During 6-min continuous random disturbances, the root mean square (RMS) of system frequency deviations decreases by 4.91% compared to conventional methods, while SOC fluctuations of supercapacitors and batteries are reduced by 49.28% and 45.49%, respectively. The parameterized asymmetric regulation mechanism significantly extends the lifespan of energy storage devices, offering a novel solution for real-time frequency control in high-renewable penetration grids. Full article

This paper proposes a hybrid synchronization control modular multilevel converter-based hybrid energy storage system (HSC-MMC-HESS) that innovatively integrates battery units within MMC submodules (SMs) while connecting a supercapacitor (SC) to the DC bus. The configuration synergistically combines the high energy density of batteries with the high power density of SCs through distinct energy/power pathways. The operational principles and control architecture are systematically analyzed, incorporating a hybrid synchronization control (HSC) strategy to deliver system inertia, primary frequency regulation, fault-tolerant mode transition capabilities, and isolation control. A hierarchical control framework implements power distribution through filtering mechanisms and state-of-charge (SOC) balancing control for battery management. Hardware-in-the-loop experimental validation confirms the topology’s effectiveness in providing inertial support, enabling flexible operational mode switching and optimizing hybrid energy storage utilization. The demonstrated capabilities indicate strong application potential for medium-voltage distribution networks requiring dynamic grid support. Full article

In the field of mining transportation, methanol range-extended powertrain systems are emerging as the preferred solution to address heavy-duty transport challenges in mining areas, leveraging their low-carbon emissions and long-range endurance. However, conventional energy storage technologies face trade-offs between energy density, power density, and cycle life: lithium-ion batteries (Li-ion) have a high energy density but short cycle life, while supercapacitors (SCs) have a high power density and long cycle life but low energy density. To address these limitations, a hybrid energy storage system (HESS) combining Li-ion and supercapacitors (SCs) is proposed as the energy storage unit for the methanol range-extended mining truck (MRMT) in this study. Firstly, the power architecture of MRMT with HESS is designed. Then, the range-extender, Li-ion battery, and SCs are matched and selected based on the operating conditions of the mining truck. Finally, a whole vehicle energy management strategy is developed, and the vehicle power system performance is simulated by combining MATLAB/Simulink (R2022a) with AVL-Cruise (R2019.2). Comparison with conventional single Li-ion range-extender system reveals that the MRMT with HESS reduces methanol consumption by 6.4% and extends the cycle life of Li-ion by 353.4%. This study provides a technological path for the green transformation of mine transportation that is both economical and sustainable. Full article

The sub-synchronous oscillation (SSO) characteristics and suppression strategies of a hybrid system comprising doubly fed induction generator (DFIG)-based wind turbines and synchronous pumped storage units connected to the power grid via series-compensated transmission lines are analyzed. A modular modeling approach is used to construct a detailed system model, including the wind turbine shaft system, DFIG, converter control system, synchronous machine, excitation system, power system stabilizer (PSS), and series-compensated transmission lines. Eigenvalue calculation-based small-signal stability analysis is conducted to identify the dominant oscillation modes. Suppression measures are also developed using relative participation analysis, and simulations are carried out to validate the accuracy of the model and analysis method. The analysis results indicate that the SSO phenomenon is primarily influenced by the electrical state variables of the DFIG system, while the impact of the state variables of the synchronous machine is relatively minor. When the level of series compensation in the system increases, SSO is significantly exacerbated. To address this issue, a sub-synchronous damping controller (SSDC) is incorporated on the rotor side of the DFIG. The results demonstrate that this method effectively mitigates the SSO and significantly enhances the system’s robustness against disturbances. Furthermore, a simplified modeling approach is proposed based on relative participation analysis. This method neglects the dynamic characteristics of the synchronous machine while considering its impact on the steady-state impedance and initial conditions of the model. These findings provide theoretical guidance and practical insights for addressing and mitigating SSO issues in hybrid renewable energy systems composed of DFIGs and synchronous machines. Full article

The increasing integration of renewable energy sources has posed significant challenges to grid frequency stability. To maximize the advantages of energy storage in primary frequency regulation, this paper proposes a comprehensive control strategy for a hybrid energy storage system (HESS) based on supercapacitor battery. Firstly, considering the characteristics of the HESS and different control strategies, the battery responds to virtual droop control to reduce frequency deviation, while the supercapacitor responds to inertia control to suppress frequency drops and facilitate frequency recovery. Simultaneously, a reasonable dynamic dead zone is configured to prevent frequent actions of the battery and thermal unit while allowing flexible adjustments according to the load condition. Thirdly, an algebraic S-curve-based adaptive droop coefficient incorporating SOC is proposed, while the inertia coefficient additionally considers load type, enhancing adaptability. Furthermore, to better maintain the battery’s SOC, an improved adaptive recovery strategy within the battery dead zone is proposed, considering both SOC recovery requirements and system frequency deviation constraints. Finally, a simulation validation was conducted in MATLAB/Simulink. Compared to the conventional strategy, the proposed control strategy reduces the frequency drop rate by 17.43% under step disturbance. Under compound disturbances, the RMS of frequency deviation decreases by 13.34%, and the RMS of battery SOC decreases by 68.61%. The economic benefit of this strategy is 3.212 times that of the single energy storage scheme. The results indicate that the proposed strategy effectively alleviates sudden frequency disturbances, suppresses frequency fluctuations, and reduces battery output while maintaining the SOC of both the supercapacitor and the battery, thereby extending the battery lifespan and improving economic performance. Full article

We propose a coordinated control strategy for off-grid 10 kV wind–solar–hydrogen energy storage DC microgrid systems based on hybrid energy storage and controllable loads to improve their stability and accommodation level. First, mathematical models of each unit are established based on the operating characteristics of wind turbines, photovoltaic (PV) units, alkaline electrolyzers, fuel cells, and lithium batteries. Second, on the side of the electro-hydrogen hybrid energy storage DC/DC converter, the traditional dual-loop control is improved by proposing a control scheme combining an extended state observer with adaptive backstepping control (ESO-adaptive backstepping). On the load demand side, an electric spring incorporating adaptive fuzzy control (AFC) is introduced to adjust and compensate for the voltage. Finally, an actual case analysis is conducted using data from the Ningbo Cixi hydrogen–electric coupling DC microgrid demonstration project. The results demonstrate that the control method proposed in this study significantly outperforms the traditional double closed-loop control method. Specifically, the proposed method reduces the bus voltage fluctuation range in the presence of load disturbances by 24.07% and decreases the stabilization time by 56.92%. Additionally, the efficiency of the hydrogen fuel cell is enhanced by 31.88%. This control method can be applied to 10 kV DC microgrid systems with distributed energy resources. It aims to reduce the fluctuation amplitude of the DC bus voltage and enhance the system’s ability to withstand transient impact events. Full article