Energy Storage Elements Research Articles

A single‐stage AC‐AC solid‐state transformer with ZVS operation

Solid-state transformer (SST) is an attractive concept, which provides galvanic isolation and voltage scaling by means of a medium-frequency link. In this paper, a single-stage alternative current (AC)-AC SST solution without bulky energy storage elements is presented. The front-end rectifier (FER) and rear-end inverter (REI) of the SST works at line-frequency, while the intermediate LLC series resonant converter (SRC) fulfils the tasks of galvanic isolating and regulating the output voltage. To achieve high efficiency and bidirectional power flow capability of the SST, the zero voltage switching (ZVS) condition of the LLC SRC is comprehensively analysed, and the parameters design method of the LLC SRC is developed, where the resonant currents are constructed by applying the same gating signals to the primary-side and secondary-side bridges and the dead-time is properly selected. Consequently, the presented SST has the merits of high conversion efficiency, naturally bidirectional power flow capability, potentially high power density and high reliability. The experimental results on a 1.5 kW SST prototype show that sinusoidal input and output current, ZVS operation over the full load range are achieved, and the peak efficiency is 97.63%. The experimental results verify the functionality and effectiveness of the developed methods.

Toward a More Renewable Energy-Based LFC Under Random Packet Transmissions and Delays With Stochastic Generation and Demand

The load frequency control (LFC) aims to keep the frequency fluctuation of the power grids within certain specified limits, under various load disturbances. However, with the increased usage of renewable energy sources (RESs) in smart grids, it is essential to regulate the conventional power plants, based on renewable energy penetration levels. Moreover, with the decentralized nature of the control operation in smart grids, the communication network between the control center and actuator faces the challenge of random communication delays and packet drops in the form of cyberattacks. In this article, the conventional thermal power plant operations within an LFC have been modified using energy storage elements with an emphasis on maximizing the RES utilization while tackling the problems associated with cyber-physical systems, such as packet drops and random time delays. A filtered proportional&#x2013;integral&#x2013;derivative (PID) controller is tuned in the LFC using the particle swarm optimization (PSO) algorithm, including random time delays and cyberattacks modeled as random packet drops. The tuned PID control performance in the LFC scheme is tested with synthetic stochastic as well as real profiles of RES and load demands. The numerical analysis has been conducted on two-area LFC model with Monte Carlo simulations of stochastic demand and generation profiles. <i>Note to Practitioners</i>&#x2014;We are moving toward more renewable energy-based cyber-physical power grids, and it is becoming increasingly important to understand the limits of the balance between more renewable energy integration versus changing the prime-mover in thermal power generation units to meet uncertain load demands. This article proposes a new load frequency control (LFC) scheme employing a nonlinear dead-zone element between the control signals and the actuators (prime movers), which allows the utilization of the available renewable energy sources (RESs) to meet the load and then send a set-point change command in the thermal power generators if the RES does not meet the load. The robustness of the smart grid stability is also verified with the denial-of-service (DoS)-type cyberattack, which is represented in the form of high probability of packet drops and stochastic time delays in the communication channels between the control center and the generation units. It is also essential to understand how different stochastic profiles may affect the stability and performance of the tuned LFC loops, under random time delays and packet dropouts. These are quantified using the uncertainty bounds of grid frequency, its rate of change, control inputs, and power exchange between the two areas that are analyzed using Monte Carlo simulations with different types of nonstationary load and RES profiles and also using real data to show the effectiveness of the LFC scheme with communication constraints and the resulting imperfections.

Tracking High Performance of an Isolated PV-Diesel System Without Energy Storage (Dept.E)

Abstract In this paper, a control scheme is proposed for three-phase isolated PV-diesel system without energy storage element. The scheme aims to: track maximum power from the PVA, regulate the load voltage, compensate the load unbalance viewed by the diesel generator, and to control the diesel engine speed. The first three tasks are achieved by controlling the PWM inverter interfacing the PV array to the system. The fourth is realized by a modified fuzzy logic controller of the diesel engine. The obstacles encountered on operating the system under certain probable loading conditions are addressed. Two strategies are proposed to adapt the control scheme to accommodate all loading scenarios maintaining excellent technical and economic performance. The system operation is investigated under a variety of conditions to prove the aptness of the proposed techniques.

Minimal Series–Parallel Network Realizations of Bicubic Impedances

An important open problem in the synthesis of passive controllers is to obtain a passive network that realizes an arbitrary given impedance function and contains the least possible number of elements. This problem has its origins in electric circuit theory, and is directly applicable to the cost-effective design of mechanical systems containing the inerter. Despite a rich history, the problem can only be considered solved for networks that contain at most two energy storage elements, and in a small number of other special cases. In this article, we solve the minimal network realization problem for the class of impedances realized by series–parallel networks containing at most three energy storage elements. To accomplish this, we develop a novel continuity-based approach to eliminate redundant elements from a network.

Dynamic Voltage Restorer to Maintain Constant Voltage at Load

This paper is used for decrease the power quality problems in electrical distribution. Sometimes potential is not stable so it causes potential disturbances in power system then it produces harmonics in the system. Therefore, this gained with a concept called DVR. This controls the potential increase and decrease the distribution. Because of these problems, there is a possibility to draw more power and reduction in the devices. DVR saves the power with potential injections which cause effect phase and also the shapes of the input waveform. In this project, we are using a lead acid battery device as energy storage element and also PWM process useful for trigger the circuits. It will be operated in unsymmetrical potential conditions and remains ideal in normal conditions. It will set the potential into system at a rated value of the quantity and cycles per second. So that it is regained the receiving side potential to accurate range. This process is used to compare the decrease in potential, increase in potential and power frequencies in the system. To decreases economic problems this project is helpful. If the potential is highly changes, the machine will get destroy it can have a severe economic problem on residential areas and industries. Which is help to improve quality of powering issues in the future power system operations.

Scheduling optimization for smart microgrids considering twolevels transactions of electric vehicles and energy markets

Smart microgrid planning poses some challenges, including bi-directional energy flow both inside and outside the smart microgrid. This research studies at the internal flow level energy transactions with the internal resources of the microgrid, and at the external flow level the energy transactions with external stakeholders to the microgrid. Electric vehicles can operate bidirectionally and participate at the internal and external level of smart microgrids. In this context, this study analyzes electric vehicles both levels. (1) At the level of internal participation, electric vehicles operate in a residential area of a microgrid that is also connected to energy storage systems and elements with uncertainty, such as photovoltaic generation systems and residential loads. Prices are set by considering operating costs within the smart microgrid. (2) The level of external participation refers to an electric vehicle station that offers three services: charging, discharging and swapping battery. Prices are stochastic and come from the spot market prices of electric vehicles. Consequently, it is proposed that the aggregator must plan the optimal scheduling for the visit scenarios of two-level stochastic electric vehicles. The system can also trade energy that come from a local and wholesale energy market. Results demonstrate that two-level operation can help to evaluate the economic impact of electric vehicles.

Colossal permittivity of (Gd + Nb) co-doped TiO2 ceramics induced by interface effects and defect cluster

Material with high dielectric constant plays an important role in energy storage elements. (Gd + Nb) co-doped TiO2 (GNTO) ceramics with giant dielectric permittivity (>104), low dielectric loss, good temperature and frequency stability in broad range of 30–150 °C and 102–106 Hz have been systematically characterized. Especially, a low dielectric loss of 0.027 and a giant dielectric permittivity of 5.63 × 104 at 1 kHz are attained for the composition with x = 0.01. Results of complex impedance spectroscopy, I–V curve and frequency dependent dielectric constant under DC bias indicate that internal barrier layer capacitance (IBLC) effect, electrode effect and electron-pinned defect-dipole (EPDD) effect contribute to the colossal permittivity (CP) property simultaneously.

Parameter Optimization and Experimental Analysis of Passive Energy Storage Power-Assisted Exoskeleton

To address the occurrence of lumbar spine disease among labor workers who carry heavy objects, a passive energy storage based exoskeletal apparatus was designed to assist, using springs as energy storage elements and utilizing the change in energy that occurs when the human body is bent during the process of lifting objects. First, the mechanism of the exoskeleton was statically modeled; the spring stiffnesses and the locations of support points were used as design variables to optimize the model by optimizing the effective moment on the lumbar spine. Next, an optimized algorithm (Optdes-Sqp) based on the Newton method for solving quadratic programming subproblems was applied to optimize the stiffnesses of compression and extension springs and the positions of the upper support points of each spring. The accuracy of the simulated model was also verified using MATLAB software. Finally, the effect of optimization was verified, and the respiratory rates and heart rates of subjects before and after wearing the exoskeleton were analyzed. The experimental results show that the exoskeleton designed in this study assisted the subjects, and the results lay the foundation for follow-up designs and studies of exoskeletons.

Design and Experiment of FBG Sensors for Temperature Monitoring on External Electrode of Lithium-Ion Batteries

Lithium-ion (Li-ion) battery becomes a promising energy storage element in the power grid. Temperature monitoring is a key tool to guarantee the safe service and durable life of Li-ion batteries. In this study, an optical fiber sensor was proposed for the temperature monitoring of Li-ion batteries. The proposed sensor consists of a metal ring and a fiber Bragg grating (FBG), which is gloved on the external electrode of the cell. This installation is not only easy to assemble but also no interference to the circuit connection. The results of calibration test on proposed FBG sensors show good linearity (0.99) and high sensitivity (12 pm/°C). A comparison test illustrates the response of proposed FBG sensors has a good agreement with PT100 sensors. The FBG sensor can be fabricated as sensor arrays to monitor the temperature of multiple cells during charge/discharge cycles, simultaneously. The experimental results show that the FBG sensors have good repeatability during several cycles. FBG sensor arrays can be used to achieve distributed temperature measurement for multiple cells. It provides a solution to monitor the thermal behavior of each cell in battery packs and an available tool to improve the thermal management and safety of Li-ion batteries.

The survey of the combined heat and compressed air energy storage (CH-CAES) system with dual power levels turbomachinery configuration for wind power peak shaving based spectral analysis

From the wind power spectrum density, wind energy fluctuations include various components with different frequencies and amplitudes. The hybrid energy storage, in this context, is a good choice for mitigating the wind power fluctuations effectively. Combined heat and compressed air energy storage (CH-CAES) system as a new CAES concept, can enlarge the system power/energy level with fixed underground cavern volume. Indeed, the CH-CAES system can be considered as a type of hybrid energy storage technology in which the compressors and electric heater are the two kinds of complementary energy storage elements. In this paper, the feasibility of utilizing the CH-CAES concept into wind power system for a peak shaving purpose is proposed. Based on the low-frequency, high-amplitude and high-frequency, low-amplitude components in wind power fluctuations, the CH-CAES system employs compressors and electrical heater to handle these components, respectively. Moreover, the turbomachinery in CH-CAES possesses a dual power levels configuration. The off-design models of key components are established to explore the CH-CAES system behavior when it is integrated with fluctuating wind power. Meanwhile, the components capacity is determined by using the spectral analysis method. The simulation results show that the CH-CAES system with dual power levels turbomachinery configuration can smooth out the wind power fluctuation effectively.

Performance analysis of hydrogen aqua equaliser fuel-cell on AGC of Wind-hydro-thermal power systems with sunflower algorithm optimised fuzzy-PDFPI controller

ABSTRACT This article investigates the effect of hydrogen aqua equaliser (HAE) with hydrogen repository tank and fuel cell (FC) as an energy storage element for frequency control in an interconnected power system. The system under study consists of a combined structure of hydro – thermal along with wind, diesel and gas units as well as energy storage elements. An advanced fuzzy-based PDF plus PI controller is proposed and a Sunflower optimisation (SFO) technique is used to optimise the controller parameter. The superiority of the prospective SFO algorithm is demonstrated over other techniques like genetic algorithm (GA), differential evaluation (DE) & particle swarm optimisation (PSO). The projected FPDFPI controller is studied over PID and PDFPI controller to show its efficacy. The effect of the HAE-FC units in an interconnected power system is studied. Sensitivity analysis and OP-5700 OPAL-RT Hil module-based Hardware-in-the-Loop (HiL) real-time simulation has also been carried out.

Eddy current damper capable of collecting electric energy

This paper presents an eddy current damper model that can store electrical energy. The damper is mainly used under strong impact load. On the basis of generating sufficient electromagnetic damping force to resist the impact load, the generated eddy current is guided out of the device through the winding and connected to the energy storage components of the external circuit. In this way, it is realized that the eddy current damper has the function of resisting the impact load. And at the same time, the eddy current damper can convert a part of the impact energy into electric energy and store it in the energy storage element. After research, the theoretical scheme is completely feasible, and the single impact energy conversion efficiency can reach 2.33 %.

A Delta-Connected Modular Multilevel STATCOM With Partially-Rated Energy Storage for Provision of Ancillary Services

This paper proposes a delta-connected Modular Multilevel STATCOM with partially rated storage (PRS-STATCOM), capable of providing both reactive, and active power support. The purpose is to provide short-term energy storage enabled grid support services such as inertial, and frequency response, either alongside or temporarily instead of standard STATCOM voltage support. The topology proposed here contains two types of sub-modules (SM) in each phase-leg: standard sub-modules (STD-SMs), and energy storage element sub-modules (ESE-SMs) with a dc-dc interface converter between the SM capacitor, and the ESE. A control structure has been developed that allows energy transfer between the SM capacitor, and the ESE resulting in active power exchange between the converter, and the grid. Injecting <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{3}^{rd}$</tex-math></inline-formula> harmonic current into the converter waveforms can be used to increase the amount of power that can be extracted from the ESE-SMs, and so reduce the required ESE-SMs fraction in each phase-leg. Simulation results demonstrate that for three selected active power ratings, 1 pu, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{2}{3}$</tex-math></inline-formula> pu, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{1}{3}$</tex-math></inline-formula> pu, the fraction of SMs that need be converted to ESE-SMs are only 69%, 59% & 38%. Thus, the proposed topology is effective in adding real power capability to a STATCOM without a large increase in equipment cost.

Goal-Programming-Based Multi-Objective Optimization in Off-Grid Microgrids

Renewable-based off-grid microgrids are considered as a potential solution for providing electricity to rural and remote communities in an environment-friendly manner. In such systems, energy storage is commonly utilized to cope with the intermittent nature of renewable energy sources. However, frequent usage may result in the fast degradation of energy storage elements. Therefore, a goal-programming-based multi-objective optimization problem has been developed in this study, which considers both the energy storage system (battery and electric vehicle) degradation and the curtailment of loads and renewables. Initially, goals are set for each of the parameters and the objective of the developed model is to minimize the deviations from those set goals. Degradation of battery and electric vehicles is quantified using deep discharging, overcharging, and cycling frequency during the operation horizon. The developed model is solved using two of the well-known approaches used for solving multi-optimization problems, the weighted-sum approach and the priority approach. Five cases are simulated for each of the methods by varying weight/priority of different objectives. Besides this, the impact of weight and priority values selected by policymakers is also analyzed. Simulation results have shown the superiority of the weighted-sum method over the priority method in solving the formulated problem.

Bidirectional DC–DC Converter with Coupled Inductor Fordc-Bus Regulation in Microgrid Applications

&#x0D; This paper presents a theoretical analysis and the experimental results of the bidirectional coupled inductor dc-dc converter for dc-bus voltage regulation and power compensation in dc-microgrid applications. In dc-microgrids, a power distribution system requires a bidirectional converter to control the power flow between dc-bus and batteries. Furthermore, the dc-bus needs to be kept stabilized within certain limits and the converter handles a large range of voltage variation in the accumulators. The proposed topology is also relatively feasible for low-input-voltage applications for interfacing energy storage elements, such as batteries, ultracapacitors with the high voltage dc-bus in electric vehicles. The converter allows greater voltage gain compared to classic non-isolated topologies and can better deal with the wide range of voltage variation imposed by the source/load. The operation principles, the DC voltage gain, the design of the filters, the voltage/current stresses and a comparison are discussed. The experimental results confirmed and validated the theoretical study as well as the converter performance so that the measurements performed obtained from a 600 W laboratory prototype.&#x0D;

Deep Learning and Parallel Processing Spatio-Temporal Clustering Unveil New Ionian Distinct Seismic Zone

This research work employs theoretical and empirical expert knowledge in constructing an agglomerative parallel processing algorithm that performs spatio-temporal clustering upon seismic data. This is made possible by exploiting the spatial and temporal sphere of influence of the main earthquakes solely, clustering seismic events into a number of fuzzy bordered, interactive and yet potentially distinct seismic zones. To evaluate whether the unveiled clusters indeed depict a distinct seismic zone, deep learning neural networks are deployed to map seismic energy release rates with time intervals between consecutive large earthquakes. Such a correlation fails should there be influence by neighboring seismic areas, hence casting the seismic region as non-distinct, or if the extent of the seismic zone has not been captured fully. For the deep learning neural network to depict such a correlation requires a steady seismic energy input flow. To address that the western area of the Hellenic seismic arc has been selected as a test case due to the nearly constant motion of the African plate that sinks beneath the Eurasian plate at a steady yearly rate. This causes a steady flow of strain energy stored in tectonic underground faults, i.e., the seismic energy storage elements; a partial release of which, when propagated all the way to the surface, casts as an earthquake. The results are complementary two-fold with the correlation between the energy release rates and the time interval amongst large earthquakes supporting the presence of a potential distinct seismic zone in the Ionian Sea and vice versa.

Unbalanced Operation Principle and Fast Balancing Charging Strategy of a Cascaded Modular Multilevel Converter–Bidirectional DC–DC Converter in the Shipboard Applications

In the vessel integrated power system (IPS), several common events, such as replacement of the aging batteries, isolation of fault modules, and launching of pulse loads, can make the state-of-charge (SOC) of energy storage elements (ESEs) inconsistent, which, consequently, requires different charging or discharging power commands for the ESEs to balance their SOC. Modular multilevel converter–bidirectional dc–dc converter (MMC-BDC) can be utilized in the vessel IPS to connect ESEs with the medium-voltage (MV) bus for its outstanding characteristics. However, the degree of imbalance in the module power of MMC-BDC is limited inherently, which can destabilize the system, but is usually neglected by the researchers. Therefore, this article investigates the unbalanced operating principle of a cascaded MMC-BDC. The imbalance boundary is studied. A control strategy is designed for the unbalanced operation to optimize the voltage stress of the components. A method of allocating unbalanced module power to the submodules (SMs) is raised on the basis of an imbalance boundary. A novel fast balancing charging strategy is proposed consequently. Finally, the proposed theory and strategies are verified through simulation and a 7.2-kW prototype.

Preparation and properties of porous electrode of supercapacitor based on particulate leaching method

Supercapacitor is a new type of energy storage element between traditional capacitor and battery. Particulate leaching method, which was used to increase specific surface area, was the main idea of this article. First of all, GR-PPy material was prepared by chemical in situ polymerization (FeCl3-MO self-degradation template was used to polymerize pyrrole monomer on GR layer). Subsequently, acetylene black and polytetrafluoroethylene emulsion were added and carbon paste electrode was obtained. At the same time, the porous electrode was prepared by particulate leaching method. Cyclic voltammetry, constant current charge and discharge test and AC impedance test were conducted in 1mol· L-1 Na2SO4 electrolyte. The results showed that the specific capacity of the porous electrode was increased by 12% compared with the normal electrode, and the ion diffusion rate was faster than the blank group. In addition, this porous treatment had little effect on the stability of circulation and the electrode resistance. Therefore, it could be concluded that the porous electrode is a promising electrode of supercapacitor.

Recent advances in optoelectronic oscillators

An optoelectronic oscillator (OEO) is a microwave photonic system that produces microwave signals with ultralow phase noise using a high-quality-factor optical energy storage element. This type of oscillator is desired in various practical applications, such as communication links, signal processing, radar, metrology, radio astronomy, and reference clock distribution. Recently, new mode control and selection methods based on Fourier domain mode-locking and parity-time symmetry have been proposed and experimentally demonstrated in OEOs, which overcomes the long-existing mode building time and mode selection problems in a traditional OEO. Due to these mode control and selection methods, continuously chirped microwave waveforms can be generated directly from the OEO cavity and single-mode operation can be achieved without the need of ultranarrowband filters, which are not possible in a traditional OEO. Integrated OEOs with a compact size and low power consumption have also been demonstrated, which are key steps toward a new generation of compact and versatile OEOs for demanding applications. We review recent progress in the field of OEOs, with particular attention to new mode control and selection methods, as well as chip-scale integration of OEOs.

Forecasting and optimisation for microgrid in home energy management systems

The wide proliferation of renewable energy and deregulation of power grid systems require small power utilization systems to deploy intelligent methods of adjustment to the user power demand. To accomplish this goal, the smart power demand forecasting and power consumption optimization methods and algorithms need to be developed. For this purpose, small power utilization systems can benefit from the techniques developed for the smart grid in general. The present paper is devoted to the development of a forecasting model based on the Long Short-Term Memory (LSTM) method and an optimization model based on Genetic Algorithm (GA) adopted for the use in home energy management systems (HEMS). The present work describes a smart microgrid architecture with a focus on LSTM and GA. The experiments demonstrate that the developed algorithms generate a stable pattern of daily power demand. The use of the developed algorithms allows automated shifting of power to achieve the lowest price without sacrificing their comfort. The main contributions of the present work are the inclusion of all parts of the smart microgrid architecture (non-invasive load identification, forecasting, optimization, renewable energy sources and storage elements) in the research proposing a fully automated control in HEMS rather than recommendation based only.