Showing 12 results for Battery
P. Asgharian, R. Noroozian,
Volume 15, Issue 1 (3-2019)
Abstract
Microturbine generation system is one of the most promising and a fast growing distributed generation sources. It is used in various applications thanks to high efficiency, quick start and high reliability. Combination of the microturbine and storage system (e.g. battery bank) is desirable selection to satisfy the load requirements under all conditions and hence the battery bank can play an important role in restoring balance between source and demand. In this paper, modeling of the microturbine with battery energy storage system is presented to supply sensitive loads. Appropriate power exchange between battery and the microturbine is an essential issue so, a new control method is proposed for battery energy storage based on instantaneous value of DC-link voltage. In this new strategy, DC-link voltage as well as battery parameters (current and voltage) are used in order to produce desirable DC-DC switching. A control scheme based on voltage, current and frequency measurement is presented for the corresponding inverter. Simulations are carried out in MATLAB/Simulink software and the results show that storage along with proper control improves system reliability to supply sensitive load. The proposed configuration can be used as a remote power, emergency power and also in micro-grid.
M. El Alaoui, F. Farah, K. El Khadiri, H. Qjidaa, A. Aarab, A. Lakhssassi, A. Tahiri,
Volume 15, Issue 4 (12-2019)
Abstract
In this work, the design and analysis of new Level Shifter with Gate Driver for Li-Ion battery charger is proposed for high speed and low area in 180nm CMOS technology. The new proposed level shifter is used to raise the voltage level and significantly reduces transfer delay 1.3ns (transfer delay of conventional level shifter) to 0.15ns with the same input signal. Also, the level shifter with gate driver achieves a propagation delay of less than 0.25ns and the total area is only 0.05mm2. The proposed level shifter with gate driver was designed, simulated and layouted in Cadence using TSMC 180nm CMOS technology.
D. Kishan, P. S. R. Nayak, B. Naresh Kumar Reddy,
Volume 16, Issue 1 (3-2020)
Abstract
In recent years, the popularity of wireless inductive power transfer (WIPT) system for electric vehicle battery charging (EVBC) is always ever-increasing. In the WIPT inductively coupled coil structure is the heart of the system and the mutual inductance (MI) between the coupled coils is the key factor for effective power transfer. This paper presents the analysis of mutual inductance between the spiral square coils based on the cross-sectional area ratio of spiral circular and spiral square coupled coils. The analytical computed MI values are compared with FEM (Ansys Maxwell) simulation and Experimental computed values. Finally, the designed spiral square coils are implemented in a laboratory prototype model and at the receiver side for effective electric vehicle (EV) battery charging a closed-loop PID controller is implemented for DC-DC buck converter. The effectiveness of the proposed controller has been tested by providing sudden changes in mutual coupling and change in reference value. The proposed system is suitable for both stationary and dynamic wireless EVBC.
S. M. Hoseini, N. Vasegh, A. Zangeneh,
Volume 16, Issue 2 (6-2020)
Abstract
In this paper, a robust local controller has been designed to balance the power for distributed energy resources (DERs) in an islanded microgrid. Three different DER types are considered in this study; photovoltaic systems, battery energy storage systems, and synchronous generators. Since DER dynamics are nonlinear and uncertain, which may destabilize the power system or decrease the performance, distributed robust nonlinear controllers are designed for the DERs. They are based on the Lyapunov stabilization theory and super-twisting integral sliding mode control which guarantees system stability and optimality simultaneously. The reference signals for each DER are generated by a supervisory controller as a power management system. The controllers proposed in this work are robust, have fast response times, and most importantly, the control signals satisfy physical system constraints. The designed controller stability and effectiveness are also verified using numerical simulations.
M. Sedighizadeh, S. M. M. Alavi, A. Mohammadpour,
Volume 16, Issue 3 (9-2020)
Abstract
Regarding the advances in technology and anxieties around high and growing prices of fossil fuels, government incentives increase to produce cleaner and sustainable energy through distributed generations. This makes trends in the using microgrids which consist of electric demands and different distributed generations and energy storage systems. The optimum operation of microgrids with considering demand-side management increases efficiency and reliability and maximize the advantages of using distributed generations. In this paper, the optimal operation scheduling and unit commitment of generation units installed in a microgrid are investigated. The microgrid consists of technologies based on natural gas that are microturbine and phosphoric acid fuel cell and technologies based on renewable energy, including wind turbine and photovoltaic unit along with battery energy storage system and plug-in electric vehicle commercial parking lot. The goal of the paper is to solve a multi-objective problem of maximizing revenues of microgrid operator and minimizing emissions. This paper uses an augmented epsilon constraint method for solving the multi-objective problem in a stochastic framework and also implements a fuzzy-based decision-maker for choosing the suitable optimal solution amid Pareto front solutions. This new model implements the three type of the price-based and incentive-based demand response program. It also considers the generation reserve in order to enhance the flexibility of operations. The presented model is tested on a microgrid and the results demonstrate the efficacy of the proposed model economically and environmentally compared to other methods.
P. Bhat Nempu, J. N. Sabhahit,
Volume 16, Issue 4 (12-2020)
Abstract
The hybrid AC-DC microgrid (HMG) architecture has the merits of both DC and AC coupled structures. Microgrids are subject to intermittence when the renewable sources are used. In the HMG, since power fluctuations occur on both subgrids due to varying load and unpredictable power generation from renewable sources, proper voltage and frequency regulation is the critical issue. This article proposes a unique method for operating a microgrid (MG) comprising of PV array, wind energy system (WES), fuel cell (FC), and battery in HMG configuration. The control scheme of the interlinking converter (ILC) regulates frequency, voltage, and power flow amongst the subgrids. Power management in the HMG is investigated under different scenarios. Proper power management is accomplished within the individual subgrids and among the subgrids by the control techniques adopted in the HMG. The system voltage and frequency deviations are found to be minimized when the FC system acts as the backup source for DC subgrid, reducing the power flow through the ILC.
S. K. Gudey, S. Andavarapu,
Volume 17, Issue 3 (9-2021)
Abstract
A three-phase dual-port T-type asymmetrical multilevel inverter (ASMLI) using two sources, solar forming the high voltage level and the battery forming the low voltage level, is considered for grid interconnection. A vertical shifted SPWM is used for the ASMLI circuit. A transformerless system for grid interconnection is achieved for a 100-kW power range. A well-designed boost converter and a Buck/Boost converter is used on the front side of the inverter. Design of battery charge controller and its controlling logic are done and its SOC is found to be efficient during charging and discharging conditions. A closed-loop control using PQ theory is implemented for obtaining power balance at 0.7 modulation index. The THD of the current harmonics in the system is observed to be 0.01% and voltage harmonics is 0.029% which are well within the permissible limits of IEEE-519 standard. The power balance is found to be good between the inverter, load, and the grid during load disconnection for a period of 0.15s. A comparison of THD’s, voltage, current stresses on the switches, and conduction losses is also presented for a single-phase system with respect to a two-level inverter which shows improved efficiency and low THD. Hence this system can be proposed for use in grid interconnection with renewable energy sources.
M. Habibzadeh, S. M. Mirimani,
Volume 17, Issue 4 (12-2021)
Abstract
The role of energy management in hybrid and electric vehicles (EVs) is an important concern to enhance operational performance and provide the defined efficiency targets in transportation. The power conversion stage as an interface between storage units and the DC-link of the three-phase inverter forms a major challenge in EVs. In this study, a control approach for DC-bus voltage, which utilizes a hybrid energy storage system (HESS) for EV applications, has been proposed. A high-energy-density battery pack and an ultra-capacitor, which owns a high-power density, form the hybrid energy storage system. The proposed approach allows full utilization of the stored energy in the storage devices, and also adds a voltage boost feature to the DC-bus. In the proposed control structure, a motor drive based on SVM-DTC is used to track the flux and torque components using regulators with the space vector modulation. The optimal DC-bus voltage can be tracked by incorporating the motor drive stage with a HESS. This integration results in less processed power. This article presents the simulation results toward confirming and verifying the effectiveness of the proposed approach.
V. M. Zavylov, I. Y. Semykina, S. A. Abeidulin, E. A. Dubkov, A. S. Veliliaev,
Volume 18, Issue 1 (3-2022)
Abstract
The promising element of the infrastructure of unmanned electric vehicles is wireless chargers. The central part of such systems is a resonant circuit that provides wireless power transfer. The article discusses a set of criteria used for making the rational choice of the resonant circuit parameters. Such criteria include the efficiency, the current transfer coefficient, the excess voltage on the resonant circuit capacitors over the input voltage, the ratio between the transmitting circuit current and the receiving one. For the resonant circuit with fixed coils size and fixed resonant frequency, the families of curves were obtained via parametric analysis to show how these criteria change depending on the inductance and capacitance of the resonant circuit. The obtained dependencies allow choosing the rational inductances and capacitances of the resonant circuit, providing for a given size and a given value of the input voltage the highest conveyed power with the highest efficiency at the minimum voltage class of capacitors and the minimum current of semiconductor switches. The results of the parametric analysis were confirmed experimentally.
A. Rahali, K. El Khadiri, A. Tahiri,
Volume 19, Issue 1 (3-2023)
Abstract
In this paper, a Li-Ion Battery Charger Interface (BCI) circuit with fast and safe charging for portable electronic devices is proposed. During the charging of Li-Ion battery, current spikes due to asynchronous control signals, and temperature are factors that greatly affect battery performances and life. This circuit has the following features: prevents current spikes and also incorporates a permanent battery temperature monitoring block. The BCI uses a dual current source and generates a constant current in a large current mode of 1.5 A, further reducing charging time. The proposed BCI was designed and simulated in Cadence Virtuoso using TSMC 180 nm technology. The simulation results of the control signals show that the proposed architecture was able to eliminate the current drifts and keep the battery temperature within the normal operating range.
Nasreddine Attou, Sid-Ahmed Zidi, Samir Hadjeri, Mohamed Khatir,
Volume 19, Issue 3 (9-2023)
Abstract
Demand-side management has become a viable solution to meet the needs of the power system and consumers in the past decades due to the problems of power imbalance and peak demand on the grid. This study focused on an improved decision tree-based algorithm to cover off-peak hours and reduce or shift peak load in a grid-connected microgrid using a battery energy storage system (BESS), and a demand response scheme. The main objective is to provide an efficient and optimal management strategy to mitigate peak demand, reduce the electricity price, and replace expensive reserve generation units. The developed algorithm is evaluated with two scenarios to see the behavior of the management system throughout the day, taking into account the different types of days (weekends and working days), the random profile of the users' demand, and the variation of the energy price (EP) on the grid. The simulation results allowed us to reduce the daily consumption by about 30% to 40% and to fill up to 12% to 15% of the off-peak hours with maximum use of renewable energies, demonstrating the control system's performance in smoothing the load curve.
Jayati Vaish, Anil Kumar Tiwari, Seethalekshmi K.,
Volume 19, Issue 4 (12-2023)
Abstract
In recent years, Microgrids in integration with Distributed Energy Resources (DERs) are playing as one of the key models for resolving the current energy problem by offering sustainable and clean electricity. Selecting the best DER cost and corresponding energy storage size is essential for the reliable, cost-effective, and efficient operation of the electric power system. In this paper, the real-time load data of Bengaluru city (Karnataka, India) for different seasons is taken for optimization of a grid-connected DERs-based Microgrid system. This paper presents an optimal sizing of the battery, minimum operating cost and, reduction in battery charging cost to meet the overall load demand. The optimization and analysis are done using meta-heuristic, Artificial Intelligence (AI), and Ensemble Learning-based techniques such as Particle Swarm Optimization (PSO), Artificial Neural Network (ANN), and Random Forest (RF) model for different seasons i.e., winter, spring & autumn, summer and monsoon considering three different cases. The outcome shows that the ensemble learning-based Random Forest (RF) model gives maximum savings as compared to other optimization techniques.
