Optimal reserve provision regulation for wind farms equipped with energy storage systems

Yu, Mingcan; Huang, Wentao; Tai, Nengling; Zheng, Xiaodong; Shi, Jinxiao

doi:10.1002/etep.2718

Cited by 3 publications

(3 citation statements)

References 33 publications

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“…They also proposed management strategies based on the variable characteristics between the state of charge (SOC) and the terminal voltage of the battery, so that the fluctuation of the wind farm output could be smoothed rapidly and effectively. Yu et al [40] considered the influence of the continuous hours of wind power generation and determined the energy storage capacity of a wind farm based on the distribution law of the wind power generation, regarding average power as the expected value. Khaki et al [41] proposed some indices for measuring the fluctuation of the total active power, considering the influence of different energy storage capacities.…”

Section: Of 20mentioning

confidence: 99%

Research on Energy Storage Optimization for Large-Scale PV Power Stations under Given Long-Distance Delivery Mode

Yang

Lian

et al. 2019

Energies

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Western China has good conditions for constructing large-scale photovoltaic (PV) power stations; however, such power plants with large fluctuations and strong randomness suffer from the long-distance power transmission problem, which needs to be solved. For large-scale PV power stations that do not have the conditions for simultaneous hydropower and PV power, this study examined long-distance delivery mode and energy storage optimization. The objective was to realize the long-distance transmission of electrical energy and maximize the economic value of the energy storage and PV power storage. For a large-scale PV power station, the energy storage optimization was modelled under a given long-distance delivery mode, and the economic evaluation system quantified using the net present value (NPV) of the battery was based on the energy dispatch optimization model. By contrast, a lithium battery performance model was developed. Therefore, further analysis of the economics of the energy storage and obtaining the best capacity of the energy storage battery and corresponding replacement cycle considered battery degradation. The case study of Qinghai Gonghe 100 MWp demonstration base PV power station showed that the optimal energy storage capacity was 5 MWh, and the optimal replacement period was 2 years. Therefore, the annual abandoned electricity was reduced by 3.051 × 10 4 MWh compared with no energy storage. The utilization rate of both the PV power station and quality of the delivered electricity were modelled to realize a long-distance transmission to the grid net. This will have an important guiding significance to develop and construct large-scale single PV power stations.

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Section: Of 20mentioning

confidence: 99%

Research on Energy Storage Optimization for Large-Scale PV Power Stations under Given Long-Distance Delivery Mode

Yang

Lian

et al. 2019

Energies

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“…A two‐phase flexible dispatch and reserve scheduling model is proposed to find the appropriate proportion of wind power deration . The deviation of the wind power output caused by the WPFE is adjusted by the energy storage system and the capability of the reserve provided by the wind farms is analyzed . Based on the kernel density estimation, a multi‐state model is developed to exploit the potentiality of wind power to provide the operating reserve .…”

Section: Introductionmentioning

confidence: 99%

Sensitivity‐based reliability coordination for power systems considering wind power reserve based on hybrid correlation control method for wind power forecast error

Dong

Zhang

et al. 2020

Int Trans Electr Energ Syst

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Summary With the derated output, the wind farms provide the active power reserve and contribute to power system reliability. The impacts of the wind power forecast error (WPFE) on the capability of reserve provision and power system reliability may be quantified by the sensitivity model. For reliability and sensitivity analysis, the samples of the WPFE are usually manually generated instead of the historical data, thus the correlation control methods should be used to ensure that the samples have the same correlation with the historical data. The existing methods are either inaccurate or computationally expensive. In this article, a hybrid method for correlation control is proposed to reduce the calculation effort while ensuring the accuracy. The univariate nonstandard third‐order polynomial normal transformation (NSTPNT) method is extended to multivariate one to produce the non‐normal sample which is applied as the initial population of the genetic algorithm with local search to improve the initial fitness. The analytical sensitivity model of power system reliability with respect to the derated proportion of the wind farms and the reserve capacity provided by the conventional generators is proposed. The coordination model describing the relationship among the expected demand not served and the reserves of the wind power and the conventional generators is proposed. In numerical results, the computational effort of the proposed hybrid method is analyzed. The accuracies of the sensitivity model and the coordination model are validated. The contributions of the wind power deration and the conventional generator's reserve on the reliability are compared.

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“…In Ref., 25 the potential and capability of wind farms as reserve resource are investigated. Also, the energy storage systems are utilized in combination with wind turbine to mitigate the related uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Stochastic very short‐term economic dispatch for wind power operation using flexible ramp reserve

Nadermahmoudi

Amraee

Oskouee

2020

Int Trans Electr Energ Syst

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Summary Uncertainty of renewable generation is a major challenge in power system operation. Without scheduling enough fast reserves, the load shedding or wind curtailments are expected under rapid deviations of renewable generation. Therefore, the flexible ramp (FR) reserves are scheduled in short‐term horizons to compensate the uncertainties of renewable resources and load demand. In this paper, a very short‐term economic dispatch (ED) model is developed to handle the wind and load uncertainties using FR reserve. FR products refer to rapid 10‐minute spinning reserves that are provided by the fast‐response generating units and energy storage (ES) devices to handle the load and wind uncertainties in both upward and downward directions. The proposed model minimizes the costs of generation, contingency reserve, FR reserves, and charging of battery ES. Technical constraints of generating units and the transmission network limits are considered. The future scheduling hour is divided into six 10‐minute intervals and the generation levels and required reserves are optimized for the subsequent receding 10‐minute intervals. Point estimate (PE) method is utilized to reduce the wind generation and load uncertainty scenarios. The efficacy of PE method is compared with Monte Carlo technique. In addition to credible scenarios of wind and load uncertainties, some regional worst‐case scenarios are considered in each electric area to minimize the amount of FR underestimation. The proposed ED model is formulated as a stochastic mixed integer linear programming (MILP) model that is solved using CPLEX algorithm in GAMS for the IEEE 118‐bus and 300‐bus test systems.

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Optimal reserve provision regulation for wind farms equipped with energy storage systems

Cited by 3 publications

References 33 publications

Research on Energy Storage Optimization for Large-Scale PV Power Stations under Given Long-Distance Delivery Mode

Research on Energy Storage Optimization for Large-Scale PV Power Stations under Given Long-Distance Delivery Mode

Sensitivity‐based reliability coordination for power systems considering wind power reserve based on hybrid correlation control method for wind power forecast error

Stochastic very short‐term economic dispatch for wind power operation using flexible ramp reserve

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