Power Storage Research Articles

Hydrogen Production via Off-Sun Solar-Thermal Supercritical Water Gasification and Membrane Reforming of Piggery Waste

Supercritical water gasification (SCWG) represents an emerging technology for liquid fuel synthesis, offering large potential in significantly improving the efficiency and environmental impact of clean fuel production. Compared to conventional gasification, SCWG proceeds at much lower temperatures, allowing char and tar-free gasification of biomass and for low-quality and high-moisture content biomass to be used. As the thermochemical processes involved in SCWG and steam methane reforming (SMR) are highly endothermic, combining them with concentrated solar power (CSP) and thermal energy storage (TES) could allow the process to be driven solely by renewable energy. As such, this work models an off-sun SCWG/SMR system using novel molten salt, proposed to reach up to 600°C [1], which overcomes the previously limiting molten salt temperature of 550°C. Using an off-sun configuration, it deals with the on-sun configuration’s issues of degraded lifetime and creep-fatigue, allowing for uniform heating and a reduced load on the reactors. The novel technology of an integrated Pd-based membrane reactor, highly selective to H₂, was chosen given its ability to carry out SMR at temperatures in the viable range of new molten salts. The system uses a waste feedstock, piggery waste, to provide the dual benefit of reducing the environmental cost associated with piggery waste’s release of CH4. From the model created in Aspen Plus, a plant output of 7.2 kmolH₂/h (1,135 Nm³/h of H₂), was obtained with a flow rate of 150 kg/h of dry piggery waste, a membrane area of 131.8 m², and a 73% CH4 conversion from the feed.

Analysis of Partial Load Loss of the PCS and Internal Storage Battery Loss in Residential PV Power Generation and Storage Battery Systems

Analysis of Partial Load Loss of the PCS and Internal Storage Battery Loss in Residential PV Power Generation and Storage Battery Systems

Research on energy coordinated control strategy for offshore wind power based on distributed consistency algorithm

Offshore wind power is clean and has a large capacity, making it an important component of the development of new power systems. However, the randomness of offshore wind power affects the stability of the power grid. A coordinated control strategy of offshore wind power and multi-source energy based on a distributed consistency algorithm is proposed for offshore wind farms’ energy coordination management and optimization. By constructing a source network storage load model and analyzing the output and load fluctuations of offshore wind power, energy storage, and power grid, the constraint equation and balance equation of source network load storage power are derived. An adaptive distributed consistency methodology is employed based on a proportional utilization micro growth function to preserve the stability of offshore wind power and the power grid. It can enhance the power distribution of offshore wind power, energy storage, and distribution networks. The outcomes of the simulation show that the suggested approach may quickly equalize power, decrease frequency variations of offshore wind power, and enhance the commercial viability of offshore wind power.

Rock Mass Structure Classification of Caves Based on the 3D Rock Block Index

In large-scale water conservancy and hydropower projects, complex rock structures are considered to be the main factor controlling the stability of hydraulic structures. The classification of rock mass structure plays an important role in the safety of all kinds of large buildings, especially underground engineering buildings. As a quantitative classification index of rock mass, the rock block index is very common in the classification of borehole and dam foundation rock mass structures. However, there are few studies on the classification of underground engineering rock masses. Moreover, their classification criteria have disadvantages in spatial dimension. Therefore, this paper takes the long exploratory cave CPD1 in the water transmission and power generation system of the Qingtian pumped storage power station in Zhejiang Province as the research object and launches a study on the structural classification of the rock mass of a flat cave based on the 3D rock block index. According to the group distribution of joints, the sections are statistically homogeneous. Additionally, the Monte Carlo method is used to carry out random simulations to generate a three-dimensional joint network model. The virtual survey lines are arranged along the center of the shape of the three different orthogonal planes of the 3D joint network model to represent the boreholes, and the RBI values of the virtual survey lines on each orthogonal plane are counted to classify the rock mass structure of the flat cave in a refined manner using the rock block index of the rock mass in 3D. The above method realizes the application of the 3D rock block index in underground engineering and overcomes the limitations of traditional rock mass classification methods in terms of classification index and dimension. The results show that: (1) Three-dimensional joint network simulations built on statistical and probabilistic foundations can visualize the structure of the rock mass and more accurately reflect the structural characteristics of the actual rock mass. (2) Based on the 3D rock block index, the rock mass structure of the long-tunnel CPD1 is classified, from that of a continuous structure to a blocky structure, corresponding to the integrity of the rock mass from complete to relatively complete. The classification results are consistent with the evaluation results of horizontal tunnel seismic wave geophysical exploration. (3) Based on the 3D joint network model, it is reasonable and feasible to use the 3D rock block index as a quantitative evaluation index to determine the structure type of flat cave rock masses. The above method is helpful and significant in the classification of underground engineering rock mass structures.

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

To address the impact of wind-power fluctuations on the stability of power systems, we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system. First, we employ a strategy that restricts long- and short-term power output deviations to smoothen wind power fluctuations in real time. Second, we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise (SW-ICEEMDAN) strategy to achieve real-time decomposition of the energy storage power, facilitating internal power distribution within the hybrid energy storage system. Finally, we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components. Through simulation validation, we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power. Compared with traditional empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) decomposition strategies, the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal. Additionally, the state-of-charge of energy storage components fluctuates within a reasonable range, enhancing the stability of the power system and ensuring the secure operation of the energy storage system.

Research and application of relay protection setting calculation for SFC system of pumped storage power station

Pumped storage is a key way to meet the regulatory needs of the power system. Currently, SFC starting has become the main starting method for large pumped storage power plants. This article introduces the typical structure and operation principle of SFC in pumped storage power plants. Based on existing guidelines, the relay protection configuration and setting principles of the SFC system in pumped storage power plants are elaborated. Starting from engineering practice, a relay protection setting calculation scheme for SFC input and output transformers is proposed and put into operation on site, ensuring the reliable and stable operation of the SFC system in pumped storage power plants.

Bursting oscillation behaviors of a multi-time scales pumped storage power station with governor subsystem nonlinearity

Pumped-storage power station (PSPS) play a crucial role in supporting the grid integration of intermittent energy and require frequent regulation to balance fluctuations. Eliminating potential stability risks under the strong nonlinear and complex multi-scale coupling characteristics to ensure the stability of PSPS is crucial for new power systems. Although governor nonlinear elements have been studied in previous studies, the effects and potential risks of their non-smooth characteristics on the stability of different subsystems have not been reported. In this study, a mathematical model of PSPS considering the non-smooth characteristics of governor is established by introducing a segmentation function. Then the influence laws of their effect on important variables in different subsystems are studied through the time waveforms and phase trajectories. Additionally, sensitivity analysis is employed to identify key parameters affecting stability at various stages. Finally, the risk of bursting oscillation caused by the nonlinear elements is revealed. The results show that the nonlinear elements have less effect on the hydraulic subsystem, but their non-smooth characteristic induces state switching in mechanical subsystems, which poses a risk for frequency oscillations. Adjusting the deadband has an inhibiting effect on both oscillations caused by nonlinear elements and improves stability in hydraulic and mechanical subsystems. This work provides fresh perspectives and theoretical basis for minimizing the risk of bursting oscillations while improving Pumped-storage plant stability.

Smart Grid Operation with Hybrid Renewable Resources and Electric Vehicle

The utilization of renewable energy resources will significantly increase to achieve clean and sustainable electricity generation. The management of the continuous growth share of variable renewable resources, integration of electric vehicles (EVs) and regulation of grid frequency require effective communication facilities of recent smart grids. In this respect, smart converters can provide efficient power conditioning devices to extract maximum power from renewable resources. In addition, the batteries of EVs could be used as distributed storage and discharge power back into the grid to compensate power deficit and flactuation. Modeling and controlling of the hybrid resources within smart grid were carried out in this paper. The smart converter is switched to track the maximum power point MPPT of the solar panels. In addition, the pitch angle control and DFIG regulation are used to extracte the maximum power under different wind speed and tidal stream velocities. The deployment of EVs can compensate power fluctuations and regulate the frequency deviations in the grid based on the proposed PID controller. In this paper, the integral minimization of time-weighted absolute error (ITAE) is used for on-line tuning of the PID controller parameters. Using Matlab/Simulink package, the smart grid is modeled and simulated using the weather data of Kuwait and then the grid performance is assessed under system disturbances and load excursions.

Source Network Load Storage Access to Power Wireless Private Network Technology Based on 5G Ultra Dense Networking

We make the source network load storage access power wireless private network, this paper proposes a source network load storage access power wireless private network technology based on 5G ultra dense network. The multiple rotation scheduling and self-organizing learning methods are used to establish the deployment model of the source network load storage access node of the power wireless private network under the 5G communication mode. According to the routing control algorithm design of the 5G ultra dense networking node, combined with the integration analysis of the access load parameters, the source network load storage access model of the 5G ultra dense networking under the dynamic load distributed control mode is established. Through the method of optimal control of reactive power and voltage of distribution network, the transmission link equilibrium structure model of 5G source network load storage access to power wireless private network is constructed. Combined with the coverage analysis of link topology structure and the benefit maximization constraint analysis of production and consumption users, the active and reactive capacity analysis of transaction between production and consumption user groups and multiple production and consumption users is adopted. Combined with the energy storage characteristics analysis and power flow parameter calculation of the source network load storage access power, the 5G ultra dense networking and private network access to the source network load storage access power are realized. The test shows that this method has better power balance dispatching ability and larger output power gain when it is applied to the design of source network load storage access power wireless private network.

Renewable energy production over the Iberian Peninsula: Optimizing power plants location and energy reservoirs.

In this paper we present a methodology for obtaining a energy production system based on renewable energy able to generate the energy demand supported by hydro electric pumped storage. This model is based on the minimization of the variance of the differences between energy demand and production. The minimization procedure uses the simulated annealing, and looks for the complementarity (spatial and temporal) of solar and wind resources. The minimized variance is controlled by the use of pumped-storage hydroelectricity. The renewable energy time series are obtained by using pseudo-real climatological series coming from a Regional Climate hindcast (10km spatial resolution, 1 hour temporal resolution) for the period 1959-2007 over the Iberian Peninsula. Once the optimal series are obtained, it is analysed the requirements that the hydro-electrical system must have. The exercise here presented gives an idea of the relationships between the renewable energy production, hydro-electrical power (pumping) and energy storage needed to guarantee the energy demand at long-term under the consideration of no loss of energy.

DESIGN OF HIGHLY EFFICIENT WATER PASSAGE OF PUMP-TURBINE

The problem of the need to develop renewable energy sources as a way to save the energy supply and energy independence of Ukraine by changing the consumption of carbohydrates is considered. It is shown that the development of Ukrainian renewable energy must occur in parallel with the development of energy storage systems and balancing of the energy system. The most effective system for storing energy and balancing the energy system is pumped storage power stations (PSPS). The work shows that the design of a highly effective equipment of a hydroelectric power plant depends on the correct selection of the element geometry of the pump-turbine water passage. Therefore, it is possible to ensure the necessary level of energy characteristics of hydraulic equipment. A method of dimensionless average parameters was established, which allows even at the initial stages of designing new reversible hydraulic machines to determine the optimal geometry of the watter passage elements. This method showed good results during the numerical research of Francis hydraulic turbines at a wide range of heads, as well as reversible hydromachines at heads of 300–500 m. Using expressions that establish the connection of hydrodynamic characteristics with dimensionless complexes, three variants of the flow part of the high-pressure pump-turbines (ORO500) were investigated. Based on the obtained results, a significant influence of the geometry on the hydraulic indicators of the machine was noted. The distribution of energy losses in the inlet, blade system and outlet was analyzed. The greatest energy losses occur in the inlet of the pump-turbines. To increase the energy and kinematic indicators of the ORO500 pump-turbines, the geometry of the feed elements, as well as the spiral casing and stator, was changed. Variants for improving the parameters in the elements of the supply of the water passage of the pump-turbine are proposed.

Difficulties and Solutions in the Application of New Battery Power Storage System

Difficulties and Solutions in the Application of New Battery Power Storage System

Analysis of power dispatching decisions with energy storage systems using the optimal probability distribution model of renewable energy

Effectively managing the inherent unpredictability and fluctuation attributes of renewable energy sources within scheduling systems has emerged as a critical matter demanding immediate attention. The incorporation of energy storage technology offers notable advantages by mitigating fluctuations in wind power generation and curtailing peak shaving costs in scheduling systems through economical utilization of energy storage. This study employs the adjustment of energy storage’s reserve capacity function to modify the economic gains and losses arising from fixed spinning reserve. This approach tailors the reserve capacity function by formulating the uncertainty inherent in wind power generation. The paper presents an enhanced selection method for calculating optimal bandwidth within the framework of least squares approximation probability density function scenarios. The fusion of least squares approximation and optimal bandwidth computation permits precise refinement of bandwidth in non-parametric kernel density estimation approaches. Consequently, the study puts forth a comprehensive model for coordinated scheduling and regulation of a multi-scale energy storage power system. Finally, the stability and economy of the proposed method in the scheduling operation process were verified through simulation, and the research results can provide a theoretical basis for future uncertain wind power scheduling.

Enhanced mechanical, electrical, thermal, and optical properties of poly(methyl methacrylate)/copper oxide nanocomposites for flexible optoelectronic devices via in‐situ polymerization technique

AbstractPolymethyl methacrylate (PMMA) with varied compositions of copper oxide (CuO) nanoparticles was synthesized using in‐situ free radical polymerization. UV–visible, FT‐IR, XRD, FE‐SEM, DSC, and TGA were employed to examine their structure, morphology, and thermal properties. The broadening and intensification of UV absorption, as well as the shift in IR peaks of PMMA with the addition of CuO, confirm their interactions. The reduction in optical bandgap values with the reinforcement of nanofillers confirms the existence of intermediate energy bands in nanocomposites. XRD indicated that polymerization with CuO reduced the amorphous nature of PMMA. The FE‐SEM image revealed that the dispersion of CuO altered the nonporous, rough surface of PMMA into a homogeneous shape. The reinforcement of CuO enhanced the thermal stability and glass transition temperature of PMMA. The mechanical strength, modulus, impact strength, and rigidity of PMMA were significantly improved through in‐situ polymerization. The electrical property analysis revealed that the AC conductivity increased with frequency, temperature, and filler content. The reduction in activation energy of AC conductivity with temperature points toward their semiconducting nature. PMMA/CuO nanocomposites with higher tensile strength, lower bandgap energy, higher conductivity, and thermal properties can be used to make flexible optoelectronic devices.Highlights A series of PMMA/CuO nanocomposites were synthesized and characterized. Enhanced optical property, thermal stability, and glass transition temperature. Possess excellent dielectric constant and AC conductivity. Mechanical strength and impact resistance of PMMA were greatly enhanced. A promising material for flexible optoelectronic and power storage applications.

Research on peak load shifting for hybrid energy system with wind power and energy storage based on situation awareness

The uncertainty of wind power and load fluctuations can elevate the peaking pressure on the power grid and influence the optimization strategy for peak load shifting. Additionally, there is a need to explore the trade-off and dynamic adjustment between economic considerations and the effectiveness of peak load shifting strategies. In this paper, based on the situation awareness theory, an optimization model on peak load shifting is proposed for a hybrid energy system with wind power and energy storage unit. First, in the situation perception stage, simulations that incorporate stochastic volatility are executed for renewable energy outputs and electric loads, leading to the establishment of uncertainty models for both wind power and electric load. During the situation comprehension stage, an optimization model with multi-objective is proposed to simulate the hybrid system situation, in which the mutual constraints and games are considered between peak load shifting effects and system economy. Then, in the stage of situation presentation and situation orientation, by setting quantitative indicators to analyze and judge the system situation, the problem of changing uncertainty from the weights of various attributes in multi-objective decision-making is transformed into the prediction problem of the adjustable factor, and a hybrid network model is proposed to realize the interval prediction of the adjustable factor, further balancing the goals of load leveling and system economy. Example simulations demonstrate that the proposed optimization model for peak load shifting can effectively reduce the peak-valley difference ratio of the net load by over 39.08 %, thereby smoothing the overall net load fluctuation. In the face of uncertainty, the model shows minimal impact on the peak-valley difference ratio of the net load, experiencing only 3.91 % and 7.13 % changes in response to wind power and load fluctuations, respectively. These findings underscore the model's sensitivity to different levels of uncertainty in both wind power and load scenarios. The MAML-LSTM-FC model can clarify the selection range of the adjustable factor according to the requirements of system quantitative indexes, thereby achieving dynamic coordination between the effects of peak load shifting and economics.

Eventually-consistent federated scheduling for data center workloads

Data center schedulers operate at unprecedented scales today to accommodate the growing demand for computing and storage power. The challenge that schedulers face is meeting the requirements of scheduling speeds despite the scale. To do so, most scheduler architectures use parallelism. However, these architectures consist of multiple parallel scheduling entities that can only utilize partial knowledge of the data center’s state, as maintaining consistent global knowledge or state would involve considerable communication overhead. The disadvantage of scheduling without global knowledge is sub-optimal placements—tasks may be made to wait in queues even though there are resources available in zones outside the scope of the scheduling entity’s state. This leads to unnecessary queuing overheads and lower resource utilization of the data center.In this paper, we extend our previous work on Thiyyakat et al. (2023), a federated decentralized data center scheduling architecture that uses eventual consistency. The architecture utilizes both parallelism and an eventually consistent global state in each of its scheduling entities to make fast decisions in a scalable manner. In our work, we compare Megha with 3 scheduling architectures — Sparrow, Eagle, and Pigeon, using simulation. We also evaluate Megha’s prototype on a 123-node cluster and compare its performance with Pigeon’s prototype using cluster traces. The results of our experiments show that Megha consistently reduces delays in job completion time when compared to other architectures.

Capacity Allocation in Distributed Wind Power Generation Hybrid Energy Storage Systems

Abstract The inherent variability and uncertainty of distributed wind power generation exert profound impact on the stability and equilibrium of power storage systems. In response to this challenge, we present a pioneering methodology for the allocation of capacities in the integration of wind power storage. Firstly, we introduce a meticulously designed uncertainty modeling technique aimed at optimizing wind power forecasting deviations, thus augmenting the controllability of distributed wind power variations. Subsequently, we establish a cutting-edge real-time dynamic optimization model for state of charge, which effectively mitigates the fluctuations associated with grid-connected wind power. Moreover, we employ a state-of-the-art distributed robust optimization algorithm to enhance the stability of the distributed wind power storage system. Through comprehensive simulation testing, our findings unequivocally demonstrate the efficacy of our approach in preserving a harmonious balance between wind power load and output demand, thereby assuring the unwavering operation of the entire system. Notably, our approach attains an exceptional capacity allocation efficiency of 91% in the rigorous wind power grid-smoothing test, outperforming comparable methodologies. Lastly, we proffer essential recommendations pertaining to attenuation optimization at the effective capacity level of the batteries, effectively safeguarding the long-term stability of the energy storage system.

A Comprehensive Review of Advancements in Green Internet of Things for an Intelligent Enterprise

Intelligent Enterprise is a key approach for applying technology and service paradigms for improving the business performance. Currently most of the enterprises are changing the way they fundamentally work using various technologies that unleash a value in business process. The concept of Internet of Things (IoT) has emerged by connecting the things to internet without human intervention. Hence IoT has become one of the notable innovations playing an important role in our daily lives. IoT is generally characterized by real world small things that are widely distributed but have limited storage and processing power. On a day to day basis, the data generated from IoT devices is huge in volume and the emerging IoT services introduced new challenges such as strict latency, constrained network bandwidth, ontribution towards green environment and security. Various experiments are conducted to observe the impact of data volume on greenhouse gas emissions, latency, network bandwidth and security with low power devices in IoT. It was observed that there is a necessity to optimize the volume of data to reduce the CO2 emissions and then provide security during data transmission to overcome the above challenges.

CFD Investigation of the Hydraulic Short-Circuit Mode in the FMHL/FMHL+ Pumped Storage Power Plant

The flexibility of the FMHL+ pumped storage power plants can be improved by extending the hydraulic short-circuit operating mode. CFD simulations of the flow in three bifurcations are performed to calculate the head losses and to investigate the flow topology in the pipes. A specific attention is paid to the influence of the curvature correction that has been developed for two-equation RANS turbulence models. For the T-junction considered, the activation of the curvature correction influences the head losses whereas for the two Y-junctions computed, no effect is observed. By comparing with the Y-junctions, the T-junction leads to higher head losses and helicity in the pipes downstream of the bifurcation. Compared to the current the intragroup hydraulic short circuit operation permitted, the intergroup and interplant hydraulic short circuit mode should provide better performances with possible gains until of −55% in head losses and −94% in helicity upstream of the turbines.

Lithium-ion battery-pumped storage control strategy for smoothing wind-photovoltaic power fluctuation

Abstract Wind, as well as photovoltaic (PV), is widely used. Like loads, its power cannot be predicted, which results in the grid having to bear the power imbalance between wind-PV and loads, and substantial power fluctuations are not tolerated. Hybrid energy storage systems (HESS) containing multiple storage methods are considered effective solutions. In this paper, pumped storage and lithium-ion battery storage are fully considered, as they are supposed to have excellent performance and are highly complementary. We categorize the power imbalance into low, medium, and high according to the magnitude of the power imbalance. When the power fluctuation is low, the battery dominates. In contrast, the pumped storage dominates when the power fluctuation is high. Most importantly, when the power fluctuation is medium, we utilize an optimized first-order low-pass filter to allocate the power between the pumped storage and the lithium-ion battery. We change the filtering time in real-time according to the battery’s state of charge (SOC) to reasonably allocate the power between the pumped storage and the lithium-ion battery and ensure the SOC fluctuates within a reasonable range. This paper confirms the feasibility of the proposed strategy, where the pumped storage power fluctuates very little, in contrast, the battery power fluctuates significantly, and the SOC is always within the set reasonable range. Most importantly, the strategy proposed in this paper is straightforward to implement, which is crucial for engineering applications.