Design and Assessment of an Electric Vehicle Powertrain Model Based on Real-World Driving and Charging Cycles

In this paper, an advanced analytical model for an electric vehicle (EV) powertrain has been developed to illustrate the vehicular dynamics by combining electrical and mechanical models in the analysis. This study is based on a Nissan Leaf EV. In the electrical system, the powertrain has various components including a battery pack, a battery management system, a dc/dc converter, a dc/ac inverter, a permanent magnet synchronous motor, and a control system. In the mechanical system, it consists of power transmissions, axial shaft, and vehicle wheels. Furthermore, the driving performance of the Nissan Leaf is studied through the real-world driving tests and simulation tests in MATLAB/Simulink. In the analytical model, the vehicular dynamics is evaluated against changes in the vehicle velocity and acceleration, state of charge of the battery, and the motor power. Finally, a number of EVs involved in the power dispatch is studied. The greenhouse gas emissions of the EV are analyzed according to various energy power and driving features, and compared with the conventional internal combustion engine vehicle. In this case, Nissan Leaf is a pure EV. For a given drive cycle, Nissan Leaf can reduce CO2 emissions by 70%, depending on the way electricity is generated and duty cycles

Coordinated Control of a Wind-Methanol-Fuel Cell System with Hydrogen Storage

This paper presents a wind-methanol-fuel cell system with hydrogen storage. It can manage various energy flow to provide stable wind power supply, produce constant methanol, and reduce CO2 emissions. Firstly, this study establishes the theoretical basis and formulation algorithms. And then, computational experiments are developed with MATLAB/Simulink (R2016a, MathWorks, Natick, MA, USA). Real data are used to fit the developed models in the study. From the test results, the developed system can generate maximum electricity whilst maintaining a stable production of methanol with the aid of a hybrid energy storage system (HESS). A sophisticated control scheme is also developed to coordinate these actions to achieve satisfactory system performance

Energetic macroscopic representation control method for a hybrid-source energy system including wind, hydrogen, and fuel cell

This paper proposes a new control method for a hybrid energy system. A wind turbine, a hydrogen energy storage system, and a proton exchange membrane fuel cell are utilized in the system to balance the load and supply. The system is modeled in MATLAB/Simulink and is controlled by an improved energetic macroscopic representation (EMR) method in order to match the load profile with wind power. The simulation and test results have proved that (1) the proposed system is effective to meet the varying load demand with fluctuating wind power inputs, (2) the hybrid energy storage system can improve the stability and fault-ride-through performance of the system, and (3) the dynamic response of the proposed system is satisfactory to operate with wind turbines, energy storage, and fuel cells under EMR control

Improved Synchronous Machine Rotor Design for the Easy Assembly of Excitation Coils Based on Surrogate Optimization

This paper introduces a new rotor design for the easy insertion and removal of rotor windings. The shape of the rotor is optimized based on a surrogate method in order to achieve low power loss under the maximum power output. The synchronous machine with the new rotor is evaluated in 2-D finite element software and validated by experiments. This rotor shows great potential for reducing the maintenance and repair costs of synchronous machines, making it particularly suited for low-cost mass production markets including gen-sets, steam turbines, wind power generators, and hybrid electric vehicles

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

This paper presents a doubly fed induction generator (DFIG) wind power system with hydrogen energy storage, with a focus on its virtual inertia adaptive control. Conventionally, a synchronous generator has a large inertia from its rotating rotor, and thus its kinetic energy can be used to damp out fluctuations from the grid. However, DFIGs do not provide such a mechanism as their rotor is disconnected with the power grid, owing to the use of back-to-back power converters between the two. In this paper, a hydrogen energy storage system is utilized to provide a virtual inertia so as to dampen the disturbances and support the grid’s stability. An analytical model is developed based on experimental data and test results show that: (1) the proposed method is effective in supporting the grid frequency; (2) the maximum power point tracking is achieved by implementing this proposed system; and, (3) the DFIG efficiency is improved. The developed system is technically viable and can be applied to medium and large wind power systems. The hydrogen energy storage is a clean and environmental-friendly technology, and can increase the renewable energy penetration in the power network

Low-Carbon Transition Pathway Planning of Regional Power Systems with Electricity-Hydrogen Synergy

Hydrogen energy leads us in an important direction in the development of clean energy, and the comprehensive utilization of hydrogen energy is crucial for the low-carbon transformation of the power sector. In this paper, the demand for hydrogen energy in various fields is predicted based on the support vector regression algorithm, which can be converted into an equivalent electrical load when it is all produced from water electrolysis. Then, the investment costs of power generators and hydrogen energy equipment are forecast considering uncertainty. Furthermore, a planning model is established with the forecast data, initial installed capacity and targets for carbon emission reduction as inputs, and the installed capacity as well as share of various power supply and annual carbon emissions as outputs. Taking Gansu Province of China as an example, the changes of power supply structure and carbon emissions under different scenarios are analysed. It can be found that hydrogen production through water electrolysis powered by renewable energy can reduce carbon emissions but will increase the demand for renewable energy generators. Appropriate planning of hydrogen storage can reduce the overall investment cost and promote a low carbon transition of the power system

Game-Based Generation Scheduling Optimization for Power Plants Considering Long-Distance Consumption of Wind-Solar-Thermal Hybrid Systems

With the increasing penetration of renewable energy in power systems, fluctuation of renewable energy power plants has great influence on stability of the system, and renewable power curtailment is also becoming more and more serious due to the insufficient consumptive ability of local power grid. In order to maximize the utilization of renewable energy, this paper focuses on the generation scheduling optimization for a wind-solar-thermal hybrid system considering that the produced energy will be transmitted over a long distance to satisfy the demands of the receiving end system through ultra-high voltage (UHV) transmission lines. Accordingly, a bilevel optimization based on a non-cooperative game method is proposed to maximize the profit of power plants in the hybrid system. Users in the receiving end system are at the lower level of the bilevel programming, and power plants in the transmitting end system are at the upper level. Competitive behavior among power plants is formulated as a non-cooperative game and the profit of power plant is scheduled by adjusting generation and bidding strategies in both day-ahead markets and intraday markets. In addition, generation cost, wheeling cost, and carbon emissions are all considered in the non-cooperative game model. Moreover, a distributed algorithm is presented to obtain the generalized Nash equilibrium solution, which realizes the optimization in terms of maximizing profit. Finally, several simulations are implemented and analyzed to verify the effectiveness of the proposed optimization method

Battery energy storage selection based on a novel intermittent wind speed model for improving power system dynamic reliability

Owing to intermittency of wind power and slow ramp rates of conventional generators, a considerable amount of wind energy cannot be effectively utilized during frequency control processes. This paper proposes a technique for power system planners and operators to select or commit power capacity and energy capacity of battery energy storage system (BESS) for mitigating the effects of intermittent wind speeds on reliability and economics. A novel procedure is proposed to determine intermittent wind speeds based on the chaos theory and intermittency-related parameters. The frequency-related reliability and economic indices of a power system with BESS are formulated based on frequency control processes. The effects of BESS on dynamic reliability and economics of a practical power system are investigated using the proposed techniques and models