Improving Wind Farm Dispatch in the Australian Electricity Market With Battery Energy Storage Using Model Predictive Control

Khatamianfar, Arash; Khalid, Muhammad; Savkin, Andrey V.; Agelidis, Vassilios G.

doi:10.1109/tste.2013.2245427

Cited by 113 publications

(59 citation statements)

References 19 publications

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“…Reference [4] presents a linearized MPC-based scheme for voltage regulation. Reference [23] applied MPC for wind farm dispatch with battery energy storage system. The model prediction errors and load-to voltage relationship is considered in reference [24] to deal with volt/var optimization problem.…”

Section: Introductionmentioning

confidence: 99%

Critical Bus Voltage Support in Distribution Systems With Electric Springs and Responsibility Sharing

Zheng

Hill

Meng

et al. 2017

IEEE Trans. Power Syst.

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Abstract-With the development of a new smart load device, the electric spring (ES), the operation of distribution systems with high renewable penetration becomes more flexible. The ESs can be installed at non-critical loads for grid support. This paper proposes a two-level voltage management scheme to optimize the voltage profiles of the network, especially at chosen critical buses. In the upper level, the tap positions of load tap changer and capacitor banks switching are optimized to prevent the voltages along the feeder from being out of limits. The model predictive control technique is applied to handle the uncertainties in renewable energy and demand. In the lower level, the responsibility of maintaining the voltages of the critical buses is shared among the electric springs ( II. INTRODUCTIONN the past, distribution systems have been designed for a one-way flow of energy from substations to customers. However, in recent years, increasing numbers of distributed generators have being connected at the customer side, such as wind or solar, due to environmental and economic concerns [1]. These renewables, besides offering sustainability solutions to energy crisis, can defer network reinforcement, reduce energy transaction, and save power losses. However, due to the high penetration level, energy now can flow in reverse directions during peak generation time, which is not allowed in the traditional systems, causing the voltage rise issue. Additionally, the voltage fluctuation along feeder caused by the intermittent nature of renewable energy is unacceptable for some critical energy consumers, who require more reliable energy supply with higher power quality.In a conventional distribution system without renewable energy penetration, voltage regulation is achieved through compensating voltage drop along feeder by typical means, such as load tap changer (LTC) and capacitor banks (CB). Such voltage regulation devices can respond to the voltage deviations according to different control strategies. Classic control algorithms and device models were proposed to keep the system voltages within constraints in [2]. However, in future distribution systems with the emerging voltage issues, LTC and CB are not flexible enough, especially for the voltage fluctuation mitigation [3]. The high intermittency of renewable energy causes increased number of tap operation actions and capacitor switching, which will decrease the lifetime of such devices [4], [5]. Meanwhile, the most common problem is shifted from voltage drop to voltage rise which cannot be handled by CBs. As a result, developing new control devices and control approaches for voltage regulation in a centralized or a distributed way are needed

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Section: Introductionmentioning

confidence: 99%

Critical Bus Voltage Support in Distribution Systems With Electric Springs and Responsibility Sharing

Zheng

Hill

Meng

et al. 2017

IEEE Trans. Power Syst.

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“…Unlike traditional power generation systems, BESS can act as a rapid-response active and reactive power injection or absorption device [1][2][3][4][5][6][7][8]. The BESS can be used to smooth the power fluctuations of PV or wind power stations [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Optimal control and management of a large-scale battery energy storage system to mitigate fluctuation and intermittence of renewable generations

Yao

Dong

2016

J. Mod. Power Syst. Clean Energy

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Battery energy storage system (BESS) is one of the effective technologies to deal with power fluctuation and intermittence resulting from grid integration of large renewable generations. In this paper, the system configuration of a China's national renewable generation demonstration project combining a large-scale BESS with wind farm and photovoltaic (PV) power station, all coupled to a power transmission system, is introduced, and the key technologies including optimal control and management as well as operational status of this BESS are presented. Additionally, the technical benefits of such a large-scale BESS in dealing with power fluctuation and intermittence issues resulting from grid connection of large-scale renewable generation, and for improvement of operation characteristics of transmission grid, are discussed with relevant case studies.

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“…The MPC algorithm has been widely used in industry cases since its first application in chemical process industry in 1990. Recently, MPC has been adopted in power and renewable energy systems as well [21][22][23][24][25][26][27][28]. MPC has two main advantages: the simplicity of handling complex constraints and real-time control based on rolling horizon optimization.…”

Section: Introductionmentioning

confidence: 99%

“…Lei et al presented a two-level dynamic programming to manage a wind farm and a storage system [33], in which the upper level is implemented over the whole period to obtain the reference trajectory and the lower level is implemented for real-time operation. In [28], a combination of the MPC method with fuzzy logic control was proposed, in which MPC is used for real-time control to achieve the optimization objective, and a fuzzy logic controller adjusts the power reference to increase the lifetime of the storage system.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the limit constrain of charge/discharge frequency should be added in this model. In [28], the merit of the method is that MPC method is combined with fuzzy logic control (FLC) method to control the wind farm and energy storage. The combination of the two methods is a novel way, and the results have demonstrated that the wind farm revenue has been improved by 3%.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

et al. 2015

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Abstract:Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC) method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long-and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.

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Improving Wind Farm Dispatch in the Australian Electricity Market With Battery Energy Storage Using Model Predictive Control

Cited by 113 publications

References 19 publications

Critical Bus Voltage Support in Distribution Systems With Electric Springs and Responsibility Sharing

Critical Bus Voltage Support in Distribution Systems With Electric Springs and Responsibility Sharing

Optimal control and management of a large-scale battery energy storage system to mitigate fluctuation and intermittence of renewable generations

Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

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