Power smoothing and power ramp control for wind energy using energy storage

Esmaili, Ali; Nasiri, Adel

doi:10.1109/ecce.2011.6063870

Cited by 16 publications

(12 citation statements)

References 11 publications

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“…System. Due to the randomness of the natural condition, the output power of renewable energy generations varies drastically and these fluctuations make undesirable effects on the voltage, frequency, and transient stability of the utility grid [19]. In this paper, a 500 KW energy storage system is employed to support the short-term shortcomings of renewable energy and the construction of the ESS model is depicted in Figure 5.…”

Section: Energy Storagementioning

confidence: 99%

Modeling Analysis and Improvement of Power Loss in Microgrid

Lan

Wen

et al. 2015

Mathematical Problems in Engineering

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The consumption of conventional energy sources and environmental concerns have resulted in rapid growth in the amount of renewable energy introduced to power systems. With the help of distributed generations (DG), the improvement of power loss and voltage profile can be the salient benefits. However, studies show that improper placement and size of energy storage system (ESS) lead to undesired power loss and the risk of voltage stability, especially in the case of high renewable energy penetration. To solve the problem, this paper sets up a microgrid based on IEEE 34-bus distribution system which consists of wind power generation system, photovoltaic generation system, diesel generation system, and energy storage system associated with various types of load. Furthermore, the particle swarm optimization (PSO) algorithm is proposed in the paper to minimize the power loss and improve the system voltage profiles by optimally managing the different sorts of distributed generations under consideration of the worst condition of renewable energy production. The established IEEE 34-bus system is adopted to perform case studies. The detailed simulation results for each case clearly demonstrate the necessity of optimal management of the system operation and the effectiveness of the proposed method.

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Section: Energy Storagementioning

confidence: 99%

Modeling Analysis and Improvement of Power Loss in Microgrid

Lan

Wen

et al. 2015

Mathematical Problems in Engineering

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“…These constraints vary from country to country in different manuscripts. For instance, in a research conducted in the United States of America [26], the power ramp constraint has been considered so that the instantaneous ramp up and ramp down should be limited at 5% per minute for the last minute average. The maximum power ramp rate is 10% per minute of the rated power for the wind power systems in Germany and in Ireland, there are two specified ramp rate settings of 1 min and 10 min [27].…”

Section: Fluctuation Mitigation Constraints (Fmc)mentioning

confidence: 99%

Mitigation of windfarm power fluctuation by adaptive linear neuron‐based power tracking method with flexible learning rate

Jannati¹,

Hosseinian²,

Vahidi³

et al. 2014

IET Renewable Power Generation

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Most wind turbine generators installed in large windfarms are of variable speed types operating at the maximum power point tracking mode to generate the maximum amount of power. Owing to this fact and regarding the random nature of the windspeed, the output power of the windfarm fluctuates. Fluctuating power is a serious problem for high capacity power plants and should be smoothed. As an effective factor on the required battery energy storage system (BESS) capacity value, tracking is the most important part performed by a coordinated control system in the power smoothing process. An ADAptive LInear NEuron (ADALINE)-based power tracking method with a flexible learning rate is proposed in this study. Furthermore, a particle swarm optimisation-based calculation of the learning rate is presented for optimising the proposed tracking method which reduces the required BESS capacity and the investment cost. Moreover, a charging/discharging algorithm for the BESS units is proposed which decreases the number of required BESS units and increases their useful life by reducing the switching activity as well. To evaluate the performance of the proposed coordinated control approach, the real output data of a 99 MW windfarm are tested. The simulation results verify the effectiveness of the proposed approach.

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“…The high average value requires a long time of ESS operation and a high power of ESS. The small average value can causes a high WPF [11]- [12]. …”

Section: Proposed Wind Smoothing Controlmentioning

confidence: 99%

A Study on Wind Smoothing Control by Using Short-term Average Value through Detecting Wind Power Fluctuation Rate

Chae¹,

Kim²

2024

RE&PQJ

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Abstract. In order to increase grid stability, there are some methods to reduce wind power fluctuation by using energy storage system (ESS). Operating time of ESS will determine its losses and the lifetime of batteries. From this point, this paper proposes a wind power smoothing control by calculating shortterm average value of wind power. In this case, the operation of ESS will be decided through detecting wind fluctuation rate during 60 seconds. It means that the ESS will not operate at small fluctuation of wind power which does not affect the grid stability. The effectiveness of proposed method will be verified by comparing the conventional method with the proposed method. The wind power data were measured by power quality analysis device from 15 MW wind farm in Jeju Island located in South of Korea peninsula. The simulation results are carried out by using Matlab program.

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Power smoothing and power ramp control for wind energy using energy storage

Cited by 16 publications

References 11 publications

Modeling Analysis and Improvement of Power Loss in Microgrid

Modeling Analysis and Improvement of Power Loss in Microgrid

Mitigation of windfarm power fluctuation by adaptive linear neuron‐based power tracking method with flexible learning rate

A Study on Wind Smoothing Control by Using Short-term Average Value through Detecting Wind Power Fluctuation Rate

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