The real-time control strategy of double layer and double time scale for combined frequency regulation of thermal power energy storage

This paper proposes a two-stage smart charging algorithm for future buildings equipped with an electric vehicle, battery energy storage, solar panels, and a heat pump. The first stage is a non-linear programming model that optimizes the charging of electric vehicles and battery energy storage based on a prediction of photovoltaïc (PV) power, building demand, electricity, and frequency regulation prices. Additionally, a Li-ion degradation model is used to assess the operational costs of the electric vehicle (EV) and battery. The second stage is a real-time control scheme that controls charging within the optimization time steps. Finally, both stages are incorporated in a moving horizon control framework, which is used to minimize and compensate for forecasting errors. It will be shown that the real-time control scheme has a significant influence on the obtained cost reduction. Furthermore, it will be shown that the degradation of an electric vehicle and battery energy storage system are non-negligible parts of the total cost of energy. However, despite relatively high operational costs, V2G can still be cost-effective when controlled optimally. The proposed solution decreases the total cost of energy with 98.6% compared to an uncontrolled case. Additionally, the financial benefits of vehicle-to-grid and operating as primary frequency regulation reserve are assessed.

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Real-Time Control Strategy of Energy Storage Systems for Renewable Energy Sources Exploitation

IEEE Transactions on Sustainable Energy ◽

10.1109/tste.2013.2273400 ◽

2014 ◽

Vol 5 (2) ◽

pp. 567-576 ◽

Cited By ~ 44

Author(s):

Alfonso Damiano ◽

Gianluca Gatto ◽

Ignazio Marongiu ◽

Mario Porru ◽

Alessandro Serpi

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Real Time ◽

Control Strategy ◽

Storage Systems ◽

Renewable Energy Sources ◽

Energy Sources ◽

Energy Storage Systems ◽

Real Time Control ◽

Time Control

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Review for "A real time control strategy for improvement of autonomous operation in AC / DC micro grids using electric springs"

10.1002/2050-7038.12626/v2/review1 ◽

2020 ◽

Keyword(s):

Real Time ◽

Control Strategy ◽

Real Time Control ◽

Time Control ◽

Autonomous Operation ◽

Micro Grids

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Optimal control of a novel uninterrupted multi-speed transmission for hybrid electric mining trucks

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407018821524 ◽

2019 ◽

Vol 233 (12) ◽

pp. 3235-3245 ◽

Cited By ~ 2

Author(s):

Weiwei Yang ◽

Jiejunyi Liang ◽

Jue Yang ◽

Nong Zhang

Keyword(s):

Dynamic Programming ◽

Real Time ◽

Control Strategy ◽

Dynamic Models ◽

Fuel Efficiency ◽

Real Time Control ◽

Traction Motor ◽

Time Control ◽

Power Split ◽

Shift Strategy

Considering the energy consumption and specific performance requirements of mining trucks, a novel uninterrupted multi-speed transmission is proposed in this paper, which is composed of a power-split device, and a three-speed lay-shaft transmission with a traction motor. The power-split device is adapted to enhance the efficiency of the engine by adjusting the gear ratio continuously. The three-speed lay-shaft transmission is designed based on the efficiency map of traction motor to guarantee the drivability. The combination of the power-split device and three-speed lay-shaft transmission can realize uninterrupted gear shifting with the proposed shift strategy, which benefits from the proposed adjunct function by adequately compensating the torque hole. The detailed dynamic models of the system are built to verify the effectiveness of the proposed shift strategy. To evaluate the maximum fuel efficiency that the proposed uninterrupted multi-speed transmission could achieve, dynamic programming is implemented as the baseline. Due to the “dimension curse” of dynamic programming, a real-time control strategy is designed, which can significantly improve the computing efficiency. The simulation results demonstrate that the proposed uninterrupted multi-speed transmission with dynamic programming and real-time control strategy can improve fuel efficiency by 11.63% and 8.51% compared with conventional automated manual transmission system, respectively.

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