Market-oriented Optimal Control Strategy for an Integrated Energy Storage System and Wind Farm

Esmaeili, Sajjad; Amini, Mohammad; Khorsandi, Siavash; Fathi, S. H.; Hosseinian, Seyed Hossein; Millimonfared, Jafar

doi:10.1109/icee52715.2021.9544337

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…The intermittent nature of wind has a significant effect on the profits of wind farms and weakens their competitiveness in the electricity market [1]. In this regard, various solutions have been proposed to solve this challenge and improve the profitability of wind farms [2]. Among them, integrating batteries with wind farms has drawn more attention [3].…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling and Cost-Benefit Analysis of Lithium-Ion Batteries Based on Battery State of Health

2023

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This paper presents a novel battery degradation cost (BDC) model for lithium-ion batteries (LIBs) based on accurately estimating the battery lifetime. For this purpose, a linear cycle counting algorithm is devised to estimate the battery cycle aging. In this algorithm, the local maximum and minimum values of the profile of the battery state of charge are identified by the proposed linear formulations. Then, the battery cycle aging due to the complete and incomplete cycles is determined. In this step, the battery cycle aging during an incomplete cycle is calculated by converting it to two complete cycles. After that, the calendar aging process of the LIB is linearly formulated based on the semi-empirical model to estimate the BDC accurately. After linearizing the LIB degradation process, a mechanism for computing the BDC during the scheduling horizon is designed by modeling the BDC as a series of equal payments over the LIB lifetime. In order to incorporate the BDC in the battery energy management problem, an iterative algorithm is presented for efficiently calculating the BDC associated with the adopted charging/discharging strategy. The numerical simulation results indicate that integrating the battery degradation process into the battery scheduling problem can reduce the amount of the battery capacity fading by 32.81%, as well as increase the profit of battery owners by 1.21%. Moreover, the conducted analyses highlight the importance of considering the LIB calendar aging process in determining the optimal LIB capacity.INDEX TERMS Battery degradation cost (BDC), cycle aging process, calendar aging process, battery scheduling problem, wind energy.

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Section: Introductionmentioning

confidence: 99%

Optimal Scheduling and Cost-Benefit Analysis of Lithium-Ion Batteries Based on Battery State of Health

2023

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“…The variability in wind speed introduces fluctuations in the active power output of wind farms, which can disrupt the stable operation of the grid [35]. Integrating a BESS at the grid connection point of wind farms allows for the effective smoothing of these power fluctuations.…”

Section: Wind Storage Cogeneration System and Power Relationmentioning

confidence: 99%

A Wind Power Fluctuation Smoothing Control Strategy for Energy Storage Systems Considering the State of Charge

Peng,

Luo,

Yang

et al. 2024

Energies

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With the significant increase in the scale of energy storage configuration in wind farms, improving the smoothing capability and utilization of energy storage has become a key focus. Therefore, a wind power fluctuation smoothing control strategy is proposed for battery energy storage systems (BESSs), considering the state of charge (SOC). First, a BESS smoothing wind power fluctuation system model based on model predictive control (MPC) is constructed. The objective function aims to minimize the deviation of grid-connected power from the target power and the deviation of the BESS’s remaining capacity from the ideal value by comprehensively considering the smoothing effect and the SOC. Second, when the wind power’s grid-connected power exceeds the allowable fluctuation value, the weight coefficients in the objective function are adjusted in real time using the first layer of fuzzy control rules combined with SOC partitioning. This approach smooths wind power fluctuations while preventing overcharging and overdischarging of the BESS. When the grid-connected power is within the allowable fluctuation range, the charging and discharging power of the BESS is further refined using a second layer of fuzzy control rules. This enhances the BESS’s capability and utilization for smoothing future wind power fluctuations by preemptively charging and discharging. Finally, the proposed control strategy is simulated using MATLAB R2021b with actual operational data from a wind farm as a case study. Compared to the traditional MPC control method, the simulation results demonstrate that the proposed method effectively controls the SOC within a reasonable range, prevents the SOC from entering the dead zone, and enhances the BESS’s ability to smooth wind power fluctuations.

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“…The simulation parameters and BES characteristics are shown in Table 2. PV farm output power and RT electricity market price are forecasted using an artificial neural network (ANN) network with a multi-layer perceptron (MLP) structure [54,55]. Two nets are trained for the PV farm output power forecast, one for hourly prediction and another for day-ahead forecasting.…”

Section: Case Studies and Main Assumptionsmentioning

confidence: 99%

Predictive energy management strategy for battery energy storage considering battery degradation cost

Amini

Nazari

Hosseinian

2022

IET Renewable Power Gen

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This study proposes a novel predictive energy management strategy to integrate the battery energy storage (BES) degradation cost into the BES scheduling problem and address the uncertainty in the energy management problem. As the first step, the factors affecting the BES calendar aging and cycle aging are linearly modelled. Furthermore, a linear algorithm is provided to calculate the BES cycle aging due to the BES complete and incomplete cycles. Subsequently, a novel approach to estimating the BES degradation cost function according to the BES specifications and degradation process is presented. Finally, taking into account the BES degradation cost model, the proposed predictive energy management strategy framework is implemented on an integrated photovoltaic and BES system to evaluate the applicability and efficiency of the proposed scheme in integrating the BES degradation cost in the energy management problem. The numerical simulation results indicate that integrating the BES degradation cost into the energy management problem significantly affects the BES charge/discharge strategy. Moreover, comparing the proposed predictive energy management strategy with a simple one, it is verified that the provided approach could decrease the BES capacity fade and degradation cost by 5.06% and 4.67%, respectively, and increase the photovoltaic farm profit by 1.10%.

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Market-oriented Optimal Control Strategy for an Integrated Energy Storage System and Wind Farm

Cited by 10 publications

References 17 publications

Optimal Scheduling and Cost-Benefit Analysis of Lithium-Ion Batteries Based on Battery State of Health

Optimal Scheduling and Cost-Benefit Analysis of Lithium-Ion Batteries Based on Battery State of Health

A Wind Power Fluctuation Smoothing Control Strategy for Energy Storage Systems Considering the State of Charge

Predictive energy management strategy for battery energy storage considering battery degradation cost

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