| 1. |
- Li, Yang, 1984, et al.
(författare)
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Design of Minimum Cost Degradation-Conscious Lithium-Ion Battery Energy Storage System to Achieve Renewable Power Dispatchability
- 2020
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Ingår i: Applied Energy. - : Elsevier BV. - 1872-9118 .- 0306-2619. ; 260
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Tidskriftsartikel (refereegranskat)abstract
- The application of lithium-ion (Li-ion) battery energy storage system (BESS) to achieve the dispatchability of a renewable power plant is examined. By taking into consideration the effects of battery cell degradation evaluated using electrochemical principles, a power flow model (PFM) of the BESS is developed specifically for use in system-level study. The PFM allows the long-term performance and lifetime of the battery be predicted as when the BESS is undertaking the power dispatch control task. Furthermore, a binary mode BESS control scheme is proposed to prevent the possible over-charge/over-discharge of the BESS due to the uncertain renewable input power. Analysis of the resulting new dispatch control scheme shows that a proposed adaptive BESS state of energy controller can guarantee the stability of the dispatch process. A particle swarm optimization algorithm is developed and is incorporated into a computational procedure for which the optimum battery capacity and power rating are determined, through minimizing the capital cost of the BESS plus the penalty cost of violating the dispatch power commitment. Results of numerical examples used to illustrate the proposed design approach show that in order to achieve hourly-constant power dispatchability of a 100-MW wind farm, the minimum-cost Li-ion BESS is rated 31-MW/22.6-MWh.
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| 2. |
- Xiong, Binyu, et al.
(författare)
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An Enhanced Equivalent Circuit Model of Vanadium Redox Flow Battery Energy Storage Systems Considering Thermal Effects
- 2019
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Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 7, s. 162297-162308
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Tidskriftsartikel (refereegranskat)abstract
- Thermal issue is one of the major concerns for safe, reliable, and efficient operation of the vanadium redox flow battery (VRB) energy storage systems. During the design of the operational strategy for a grid-connected VRB system, a suitable mathematical model is needed to predict the dynamic behaviors under various operating conditions. However, conventional VRB models usually neglect the impact of temperature variations on system performance. This work develops an enhanced VRB model with the consideration of the coupling effects between the electrochemical and the thermal behaviors. The proposed model consists of two equivalent circuits. First, the electrochemical behaviors of the VRB are modeled by a second-order RC network taking account of the effects of concentration variation of the vanadium ions and the electrochemical activation. Second, a third-order Cauer network is used to model the heat transfer process in the VRB system, and the dynamic thermal behaviors of stacks, pipes and heat exchangers are characterized. Well-designed experiments and particle swarm optimization algorithm are use to identify the parametric values of the developed model. The proposed modeling method was validated experimentally using a 5kW/3kWh VRB platform, and the results show that the model is capable of accurately predicting the VRB performance under variable temperature conditions. The developed coupled electro-thermal model is then used for simulating and analyzing the performance of a VRB system operated in conjunction with a wind power plant under real-world conditions.
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| 3. |
- Xiong, Binyu, et al.
(författare)
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Peak Power Estimation of Vanadium Redox Flow Batteries Based on Receding Horizon Control
- 2023
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Ingår i: IEEE Journal of Emerging and Selected Topics in Power Electronics. - 2168-6777 .- 2168-6785. ; 11:1, s. 154-165
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Tidskriftsartikel (refereegranskat)abstract
- The peak power of a vanadium redox flow battery (VRB) reflects its capability to continuously absorb or release energy. Accurate estimation of peak power is essential for the safe, reliable, and efficient operation of VRB systems, but also challenging as it is limited by various factors, such as currents, flow rates, temperature, and state of charge. This article proposes a new online model-based peak power estimation scheme for VRBs. First, the model parameters and system states are accurately estimated using the recursive least squares with forgetting and the unscented Kalman filter, respectively. Next, based on a linear time-varying VRB model and the estimated states, the peak power estimation is formulated into an optimal control problem, and the problem is solved using the receding horizon control (RHC). The influence of the predictive horizon on the estimated peak power is discussed. Finally, the effectiveness of the proposed RHC-based peak power estimation scheme is experimentally verified on a 5-kW/3-kWh VRB platform.
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