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Due to the presence of onboard pulsed loads and other electric loads, medium-voltage direct current system (MVdc), which contains hybrid energy storage, is attracting a lot of interest in ship power system studies. To ensure proper operation of such a system, suitable management is required to maintain the voltage of the MVdc bus and confirm the load-generation balance. Consequently, this article first shows the effect of uncontrolled insertion of pulsed loads on the ship performance. Then, a proposed intelligent coordination algorithm is used to mitigate the effects of pulsed loads and ensure proper power sharing among the storage units, having different available energy. The coordination algorithm differentiates between the transient and steady state needs and takes the proper decision of insertion/removal of the appropriate storage unit and reference values. The algorithm is simulated through MATLAB/Simulink, and then the processor in the loop testing is used to validate the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a family of three-port three-level converters (TPTLC) composed of asymmetrical bidirectional half-bridge modules is proposed, which offers the benefits in terms of a simple control scheme, extended soft switching over a wide range of operating conditions, and reduced voltage stress across switches. The proposed converters take advantage of a pulsewidth modulation plus phase shift control technique to regulate the output voltage as well as to control the power flow between different ports independently. A stacked TPTLC is taken as an example to be introduced in detail to gain a thorough insight into the proposed family of converters. The stacked TPTLC can provide a high voltage gain along with a wide voltage gain range without using any transformer, resulting in the improvement in the power density. In order to minimize the conduction loss and reduce the current stress of switches, the root-mean-square current of the inductor and the boundary condition of the phase-shift controller in different operation scenarios are studied. Finally, the feasibility of the proposed concept and effectiveness of the design approach are validated based on the experimental results of a 1-kW, 100-kHz prototype of the stacked TPTLC using gallium nitride switches. [ABSTRACT FROM AUTHOR]

In the drivetrain of a fuel cell (FC)-powered electric vehicle, double-input converter plays a critical role by transferring the power from battery and FC to an ultracapacitor (UC) during acceleration and from UC to the battery during braking. As the battery and FC have unregulated low voltage, the converter should provide a high-voltage gain as well as an efficient power conversion. In this article, a double-input three-level converter composed of buck-boost-half-bridge modules is proposed for automotive applications. The proposed converter can supply the load in the absence of FC or battery. The converter takes advantage of active clamp configuration in terms of reducing the voltage stress across switches and providing soft-switching performance. Consequently, the converter's overall performance in terms of switching losses and cost can be considerably improved. The switching scheme doubles the effective switching frequency, which, in turn, reduces the size of the boost inductors to enhance power density. The operational characteristics of the converter and comparison with state-of-the-art converters are given in this article. Finally, a 4-kW, 100-kHz prototype using gallium nitride switches is implemented to validate the proposed concept. [ABSTRACT FROM AUTHOR]

A modular quasi-resonant bidirectional dc–dc converter composed of half-bridge gallium nitride modules (HBGM) with reduced switch voltage stress is proposed in this paper. By using an auxiliary capacitor, a resonant circuit is formed to shape the current and voltage so that zero-voltage switching at turn-on instant is achieved. Since the switching loss dominates the power losses in a high-frequency dc–dc converter, the soft-switching performance leads to a noticeable reduction in the total loss; so, the operating temperature will decrease, and consequently, size of the heatsink will be reduced. The proposed circuit takes advantage of enhancement-mode gallium nitride (eGaN) switches regarding their small on-resistance RDS(on), low gate charge, and fast switching speed to improve both efficiency and power density. The main performance issue of adopting GaN switches in a bidirectional dc–dc converter is the high voltage stress of GaN devices, which is handled by connecting the HBGM in the active-clamped stacked configuration, as well as optimizing printed circuit board layout design. Finally, a 1 kW, 600 V laboratory prototype operating at 100 kHz is implemented to validate the proposed concept. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive solution that allows a wirelessly connected electric vehicle (EV) to be autonomously charged and discharged, during long-term parking and/or transient stops. A bilayer power flow controller for bidirectional wireless power transfer system (BWPTS) in EVs applications is proposed. The proposed controller can manage the power flow between the EV and surrounding infrastructures, such as utility grid, home micro-grid, building micro-grid, road, or another vehicle. It consists of two control layers; the first is responsible for communicating with the surrounding infrastructures and gathering information from the vehicle operator, charging station, utility grid, and battery management system. These data are analyzed to generate the reference power signal with information about the mode of operation (charge, discharge, or abstain) and rate. The second layer receives the reference signal and predicts the control parameters for the resonant converters (on both the vehicle and grid sides) to track the desired power. The proposed algorithm is adaptively estimating the mutual inductance to consider the misalignments in the system, based on a new simple real-time mutual estimation algorithm using a single voltage measurement from the vehicle side. The second control layer is designed based on an accurate analytical model for the BWPTS's power flow. For verification purposes, a prototype for BWPTS was built and driven by the proposed controller, which was implemented using a field-programmable gate array integrated circuit. Also, a vehicle-level simulation was performed to validate the operation of the proposed controller in quasi-dynamic wireless charging at traffic signals. The proposed controller shows fast and stable response during both the transient and steady-state operation in comparison with the conventional proportional-integral controller. [ABSTRACT FROM AUTHOR]

Microgrid protection schemes require a fast, reliable, and a robust communication system, to adjust relay settings for the appropriate current levels according to the microgrid's operation mode. However, risks of communication link failures and cyber security threats are major challenges for the implementation of protection scheme. This paper presents a co-simulation platform for microgrid based on multiagent system (MAS) when the communication is available in the system. IEC 61850 is used to emulate the proposed protection scheme. The data distribution service (DDS) middleware is used to link between the hardware and software environments. During islanded mode, the system is capable of riding-through communication failures by the aid of a lithium-ion battery. When the communication is attacked, the battery plays an important role and contribute to the fault current for helping the circuit breaker to trip during islanded mode. The design of the control algorithm for the battery's ac/dc converter is developed with single mode operation to eliminate the reliance on communicated control command signals to shift the controller between different modes. [ABSTRACT FROM AUTHOR]

In this paper, we develop formulation of a multi-objective optimization problem (MOOP) to optimally size a battery unit (BU) ultracapacitor (UC) hybrid energy storage system (HESS) for plug-in electric vehicle (EV). In this application, the objectives were to minimize cost, weight, volume of the HESS simultaneously maximizing the remaining cycle life of the BU at the end of the driving cycle. The MOOP is solved by the non-dominated sorting genetic algorithm type 2 algorithm. Detailed mathematical models for the BU and UC are given. The thermal effect on performance and sizing are also included in the formulation. The power demand by the EV powertrain is shared amongst the BU and HESS by two methods: First is by using wavelet transformation, while the second is by using power split ratio. The ratio of the power (i.e., power split) handled by each storage unit was determined by the optimizer. A sensitivity analysis was conducted for the power splitting ratio verification. The problem was solved for using the urban dynamometer driving schedule and the highway fuel economy test driving profiles. This has resulted in sizing of an HESS with lower cost, volume, and weight than those existing in literature. Finally, the effect of changing the motor type on the MOOP result was investigated. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are recently gaining traction in the power sector due to various challenges and opportunities they provide to utility operators. For electric utilities that incorporate demand side management (DSM) programs, EVs could become either a burden or an advantage depending on their charging control strategy and the signaling of the DSM program. This paper proposes a decentralized fuzzy-based controller to successfully integrate and coordinate the charging of EVs that ensures fair charging of EVs at different point of connections (POCs) in the distribution grid where voltage conditions might not be the same. The controller operates in an autonomous mode that reduces the monetary cost of the communication overhead and preserves bandwidth. The proposed controller takes into consideration the owner requirements in terms of energy needed and time to charge, the voltage at the POC with the grid, and the pricing signal coming from the utility. The controller is tested under different DSM programs that exist in the literature. This paper also proposes a new DSM program that is capable of benefiting from EVs as prosumers that can provide grid services. The controller's performance was validated through MATLAB simulations that showed the controller's ability to successfully coordinate the charging of EVs in a fair manner and achieve flat system peaks without any rebound effect. The controller was also successfully tested in the presence of voltage control units, such as capacitor banks, and in the presence of distributed generations. [ABSTRACT FROM AUTHOR]

A flexible, automatic, reliable, and safe charging and discharging system for electric vehicles (EVs) and hybrid EVs is crucial in vehicle-to-grid (V2G) operation. The bidirectional inductive wireless power transfer system (BIWPTS) is an ideal solution in this situation. With authentic power-flow models for the BIWPTS in hand, designers and operators can predict, optimize, and analyze the interaction performance between the EV and the grid. Thus, this paper presents a harmonics-based theoretical power-flow model for BIWPTS for charging and discharging EVs in V2G applications. The proposed model provides accurate estimation for the active and reactive power flow during V2G and grid-to-vehicle modes. Moreover, the impact of the circuit losses and harmonics, due to the high-frequency power inverters, on the power-flow performance is investigated. This effect is stated mathematically by four novel power-flow criteria formulas. New conditions for achieving maximum active and reactive power, and unity and zero power-factor system operation, are also developed. The sensitivity of the circuit performance to the variation of its parameters has been studied. For validation purposes, a computer-based model and experimental platform of BIWPTS for EV applications are developed and tested. The comparison between the theoretical, simulation, and experimental results verified the proposed models and analysis. [ABSTRACT FROM PUBLISHER]

In this paper, a lithium ion cobalt polymer battery cell is modeled using 3-D finite elements (3DFE) for the study of its performance under a wide range of operating scenarios. The electrochemistry is modeled and coupled to an electromagnetic model to forecast the cell voltage overpotential as a result of charging and discharging under six current densities. To study this phenomenon, light ( $C$ /10), medium ( $C$ /2), and high ( $1C$ ) charging and discharging currents are imposed at the battery terminals and compared with experimental results. The electric field inside the electrodes and electrolyte is analyzed at each case highlighting regions where loss occurs. A magnetic field analysis depicts the total electrochemical generation of current densities inside the cell while identifying how the development of gradient currents occur, a mechanism which can shorten the life span of the battery. This paper distinguishes where 3DFE analysis battery models can be useful in studying how lithium ion batteries will behave given a particular loading or a charging profile before placing them in service. [ABSTRACT FROM AUTHOR]

This paper presents a real-time coordinated control of the hybrid ac/dc microgrids involving energy storage and pulsed loads. Grid-isolated hybrid microgrid applications require special considerations due to the intermittent generation, online energy storage control, and pulsed loads. In this study, we introduce a comprehensive frequency and voltage control scheme for a hybrid ac/dc microgrid consisting of a synchronous generator, solar generation emulator, and bidirectional (ac/dc and dc/dc) converters. A bidirectional controlled ac/dc converter with an active and reactive power decoupling technique is used to link the ac bus with the dc bus, while regulating the system voltage and frequency. A dc/dc boost converter with a maximum power point tracking function is implemented to maximize the intermittent energy generation from solar generators. Current-controlled bidirectional dc/dc converters are applied to connect each lithium-ion battery bank to the dc bus. Lithium-ion battery banks act as energy storage devices that serve to increase the system resiliency by absorbing or injecting power. Experimental results are presented for verification of the introduced hybrid ac/dc power flow control scheme. [ABSTRACT FROM AUTHOR]

Energy storage systems provide viable solutions for improving efficiency and power quality as well as reliability issues in dc/ac power systems including power grid with considerable penetrations of renewable energy. The storage systems are also essential for aircraft powertrains, shipboard power systems, electric vehicles, and hybrid electric vehicles to meet the peak load economically and improve the system’s reliability and efficiency. Significant development and research efforts have recently been made in high-power storage technologies such as supercapacitors, superconducting magnetic energy storage (SMES), and flywheels. These devices have a very high-power density and fast response time and are suitable for applications with rapid charge and discharge requirements. In this paper, the latest technological developments of these devices as well as advancements in the lithium-ion battery, the most power dense commercially available battery, are presented. Also, a comparative analysis of these high-power storage technologies in terms of power, energy, cost, life, and performance is carried out. This paper also presents the applications, advantages, and limitations of these technologies in a power grid and transportation system as well as critical and pulse loads. [ABSTRACT FROM PUBLISHER]

This paper presents the design and implementation of an advanced battery management system (BMS). The basic concept is to divide each series battery array into sub-arrays where each battery is individually monitored and managed. The proposed BMS continuously monitors the voltage, current, and energy of each battery. Based on these measurements, the BMS can calculate individual state of charge (SoC) levels and C-rates. Furthermore, the system has the capability to isolate each individual battery to apply different charging profiles and advanced diagnostics to detect the correct problems. Pulsed charging is deployed using different duty cycles for SoC balancing. The isolated battery is bypassed to maintain uninterrupted supply to the load despite reduced series array voltage. An unidirectional dc–dc boost converter maintains a constant output voltage level to the load, regardless of the number of batteries connected, until the problem is corrected. A hardware implementation of the proposed BMS is explained in detail. The performance of the system is tested experimentally under different loading conditions, including heavy pulsed loads. [ABSTRACT FROM PUBLISHER]

In this paper, a new energy control scheme is proposed for actively controlled hybrid dc microgrid to reduce the adverse impact of pulsed power loads. The proposed energy control is an adaptive current–voltage control (ACVC) scheme based on the moving average measurement technique and an adaptive proportional compensator. Unlike conventional energy control methods, the proposed ACVC approach has the advantage of controlling both the voltage and current of the system while keeping the output current of the power converter at a relatively constant value. For this study, a laboratory-scale hybrid dc microgrid is developed to evaluate the performance of the ACVC strategy and to compare its performance with other conventional energy control methods. Using experimental test results, it is shown that the proposed strategy highly improves the dynamic performance of the hybrid dc microgrid. Although the ACVC technique causes slightly more bus voltage variation, it effectively eliminates the high current and power pulsation of the power converters. The experimental test results for different pulse duty ratios demonstrated a significant improvement achieved by the developed ACVC scheme in enhancing the system efficiency, reducing the ac grid voltage drop and the frequency fluctuations. [ABSTRACT FROM PUBLISHER]

This paper investigates the real-time control and energy management of a dc microgrid incorporating hybrid energy sources with various loading schemes. In the proposed dc microgrid, a supercapacitor bank, a power buffer, and a pulse load are directly connected to a dc bus. The proposed system configuration highly improves the grid redundancy and reduces the total power losses. Moreover, the supercapacitor bank not only supplies the pulse load, but also supports the grid during transient periods when it is highly loaded. However, the energy management and control of such a system is more complex, since the heavy pulse load can cause high power pulsation and voltage drop. To reduce the adverse effects of the pulse load, a new real-time energy management system (EMS) with an adaptive energy calculator (AEC) based on the moving average measurement technique is developed. The proposed microgrid was implemented in hardware and experimentally tested. The results were compared with other methods, such as direct voltage control and continuous current averaging approaches. The results show that the developed EMS with AEC technique properly share the power and control the bus voltage under different loading conditions, while the adverse effects of the pulse load are highly reduced. [ABSTRACT FROM PUBLISHER]

In this paper, the economic analysis of a real-time power flow control algorithm for charging a large-scale plug-in electric vehicles (PEVs) network is proposed. Such a system is in an urban area power system with optimized renewable energy resources in South Florida. In this model, the PEVs charging rates are controlled by a central aggregator through wireless communication. To limit the impact of the PEVs' charging to the utility grid, while optimizing the scheduling of vehicle-to-grid (V2G) frequency regulation services, a V2G intelligent power flow management algorithm based on fuzzy logic control was developed. The smart charging system will improve the power system stability and robustness while bringing benefits to the utility ac grid, the PEVs network, and its customers. An economic analysis model was built with the consideration of the battery degradation and capital cost. The proposed smart charging algorithm was tested with a 50 000 PEVs network model. The simulation results show the effectiveness and economic value of the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes an intelligent workplace parking garage for plug-in hybrid electric vehicles (PHEVs). The system involves a developed smart power charging controller, a 75-kW photovoltaic (PV) panel, a dc distribution bus, and an ac utility grid. Stochastic models of the power that is demanded by PHEVs in the parking garage and the output power of the PV panel are presented. In order to limit the impact of the PHEVs' charging on the utility ac grid, a fuzzy logic power-flow controller was designed. Based on their power requirements, the PHEVs were classified into five charging priorities with different rates according to the developed controller. The charging rates depend on the predicted PV output power, the power demand by the PHEVs, and the price of the energy from the utility grid. The developed system can dramatically limit the impact of PHEVs on the utility grid and reduce the charging cost. The system structure and the developed PHEV smart charging algorithm are described. Moreover, a comparison between the impact of the charging process of the PHEVs on the grid with and without the developed smart charging technique is presented and analyzed. [ABSTRACT FROM AUTHOR]

–In this paper, a real-time energy management algorithm (RTEMA) for a grid-connected charging park in an industrial/commercial workplace is developed. The charging park under study involves plug-in hybrid electric vehicles (PHEVs) with different sizes and battery ratings as well as a photovoltaic (PV) system. Statistical and forecasting models were developed as components in the developed RTEMA to model the various uncertainties involved such as the PV power, the PHEVs, arrival time, and the energy available in their batteries upon their arrival. The developed energy management algorithm aims at reducing the overall daily cost of charging the PHEVs, mitigating the impact of the charging park on the main grid, and contributing to shaving the peak of the load curve. Hence, the benefits of implementing this RTEMA is shared among the customers, the charging park considering all customers as a bulk of power connected to the grid, and the ac grid. This makes it applicable for various business models. The developed RTEMA utilizes a fuzzy controller to manage the random energy available in the PHEVs’ batteries arriving at the charging park and their charging/discharging times, power sharing among individual PHEVs that is commonly known as vehicle-to-vehicle functionality, and vehicle-to-grid service between the charging park and the main ac grid. The developed RTEMA was simulated using the standard IEEE 69-bus system at different penetration and distribution levels. The obtained results verify the effectiveness and validity of the developed RTEMA. [ABSTRACT FROM PUBLISHER]

This paper presents a real-time energy management algorithm for hybrid ac/dc microgrids involving sustainable energy and hybrid energy storage. This hybrid storage system consists of super capacitors (SC) for ultra-fast load matching beside lithium-ion batteries for relatively long term load buffering. The energy management algorithm aims mainly at managing the energy within the system such that the effect of pulsed (short duration) loads on the power system stability is minimized. Moreover, an average annual saving of around 7% is achieved by shifting loads to off-peak hours. The expected energy needed during a future peak, the time of its occurrence and the current state of charge of both elements of the hybrid storage system are all examples of the inputs to the algorithm. A nonlinear regression technique is used to obtain mathematical models for the uncertain quantities including load and sustainable energy curves. The results show a significant improvement for the system in terms of voltage and power stability by applying the proposed algorithm. [ABSTRACT FROM PUBLISHER]

As various types of energy storage (ES) types continue to penetrate grid, electric vehicle, and Naval applications, a need arises in extending traditional analysis to cover the revised performance metrics associated with a hybrid energy storage system (HESS). Each ES device has its own respective power density, energy density, response time, and voltage stability under load. In some critical applications, such as ship power systems (SPS), it is recommended to combine two or more ES types to overcome the impediments of the other. In this paper, three different series-configured HESS are mathematically modeled, evaluated, and tested experimentally. Lead acid and lithium ion batteries as well as supercapacitor equivalent circuit models are defined as components for each mixed HESS configuration. The impulse response to a constant and pulsed load was used to evaluate each ES model. The charging of mixed ES technologies was then accomplished using a special controller to handle the unique charging constraints of each ES module. Moreover, this same controller was used to apply a “rolling charging” algorithm to extend the operating time of the HESS. The validity of the derived model and controller were validated experimentally through a hardware setup simulating a multi-pulsed load SPS profile. [ABSTRACT FROM AUTHOR]