A robust <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si33.gif" overflow="scroll"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> controller based frequency control approach using the wind-battery coordination strategy in a small power system

Howlader, Abdul Motin; Izumi, Yuya; Uehara, Akie; Urasaki, Naomitsu; Senjyu, Tomonobu; Saber, Ahmed Yousuf

doi:10.1016/j.ijepes.2014.01.024

Cited by 50 publications

(5 citation statements)

References 32 publications

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“…Another strategy was used to charge or discharge the battery using an H-infinity controller for high-frequency power fluctuation smoothing [48]. In [49], the approach to improve frequency regulation in a renewable energy microgrid is to incorporate a rule-based plan using the state of charge of the BESS and the frequency response of the energy system.…”

Section: Optimization Schemes Based On Demand Response With Frequency...mentioning

confidence: 99%

Survey of Strategies to Optimize Battery Operation to Minimize the Electricity Cost in a Microgrid With Renewable Energy Sources and Electric Vehicles

Colucci,

Mahgoub,

Yousefizadeh

et al. 2024

IEEE Access

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There is a rapid increase in the utilization of renewable sources such as solar and wind to provide power and electricity. The reason for this trend is to reduce costs and preserve the environment. However, the challenge is to efficiently use and store the energy from these sources. One approach is to optimize the decision when to charge or discharge a battery. The objective is to generate the greatest monetary gain. More charge/discharge cycles will reduce the life of a battery, thereby increasing the cost. A strategy to reduce the number of charge cycles while maintaining the effectiveness of electricity distribution from battery storage will improve battery life. With the inevitable proliferation of electric vehicles (EVs) in the market, strategies specific to electric vehicle battery profitability will be explored. An additional concern which threatens the financial feasibility of battery energy storage systems (BESSs) is the requirement of secure operation. There is currently little research study on strategies to detect cyberattacks on such systems. In this paper, we have presented a novel taxonomy for battery optimization, survey representative BESS utilization strategies, and classify these schemes within the taxonomy. Within our classification, we outline the battery optimization methods that have been discussed, analyze their ability to address issues that arise when implementing a BESS, and describe alternative research that could be explored. Future research could refer to this information to create unique battery optimization schemes to provide more efficiency and optimal revenue for a BESS when compared to current strategies.

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Section: Optimization Schemes Based On Demand Response With Frequency...mentioning

confidence: 99%

Survey of Strategies to Optimize Battery Operation to Minimize the Electricity Cost in a Microgrid With Renewable Energy Sources and Electric Vehicles

Colucci,

Mahgoub,

Yousefizadeh

et al. 2024

IEEE Access

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“…Frequency and voltage control, as well as power sharing, are presently challenging topics in autonomous (islanded or stand-alone) MGs, thus requiring advanced control techniques, with robust control design being an illustrative example. Among powerful robust control design frameworks, the H ∞ approach is perfectly suited for offering the required flexibility in order to generally guarantee robustness to parameter uncertainties [3], [4], [5], [6], [7], [8], [9], [10], [11], topology changes [7], interaction dynamics [7], [12], system inertia and damping property uncertainties [9], [10], wide range of MG operating conditions [10], measurement noise [3], [10], dynamics of phase-locked loop with measurement delay [10], as well as robust rejection of disturbances originating from all types of source and/or load variation, including RES generation [9], [10], [13], [14], possibly nonlinear and/or unbalanced loads [6], [11], [12], [13], load harmonics [11]. H ∞ techniques may be successfully combined with some other well-known controller designs -e.g., droop characteristics improved by integrating power derivative and integral terms [3], multiple droop control [7], decentralized static output feedback technique [13], mixed-sensitivity optimization [3], [4], [5], [8], [12], [14], virtual-inertia-injection technique [9], [10], loop-shaping metho...…”

Section: B Literature Reviewmentioning

confidence: 99%

“…H ∞ techniques may be successfully combined with some other well-known controller designs -e.g., droop characteristics improved by integrating power derivative and integral terms [3], multiple droop control [7], decentralized static output feedback technique [13], mixed-sensitivity optimization [3], [4], [5], [8], [12], [14], virtual-inertia-injection technique [9], [10], loop-shaping method [6], output feedback scheme [11], low-/fixed-order dynamic output feedback control [8] -to lead to well-performing results spanning from numerical simulation to hardware-in-the-loop validation test benches, potentially including suitable order reduction of the resulted controller such as to meet real-time implementation constraints. As regards storage and generation coordination in MGs frequency control [3], [4], [13], despite optimization of various trade-offs, analysis lacks controllers' robustness to model uncertainties. In [9], the output multiplicative perturbation technique is used to represent uncertainty, whereas in [10], the uncertainties are retrieved from the system in the form of structured uncertainties.…”

Section: B Literature Reviewmentioning

confidence: 99%

Frequency Robust Control Application in Islanded Microgrids Considering Parametric Uncertainties and Distinct Photovoltaic Penetration Rate Scenarios

Lam,

Riu,

Bratcu

2023

IEEE Access

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In this paper, a cascaded two-level hybrid control scheme based on multi-variable robust H ∞ and proportional integral control is proposed for primary frequency control of an island mode microgrid consisting of a diesel engine generator, a photovoltaic energy source, an energy storage system, and an aggregated static load. Topological and nonlinear averaged models of each subsystem are introduced, followed by linearized frequency-control-oriented modelling of the entire system. Then, for currents control, conventional proportional-integral-based tracking controllers placed on a lower control level are designed, with their reference values generated from the output of an H ∞ -control-based upper level. A comprehensive methodology that casts the specific engineering demands of microgrid operation into the H ∞ control formalism is outlined. Additionally, it is demonstrated how closed-loop dynamic performance requirements must at their turn be taken into account in the initial microgrid setup and sizing, namely in appropriately choosing and rating the energy storage system. Numerical simulations performed with MATLAB ® /Simulink ® show the validity and effectiveness of the proposed frequency robust control technique in the presence of multiple photovoltaic power step changes on a kVA-rated microgrid. A robust performance analysis of the previously designed H ∞ controller is performed under numerous uncertainty levels in the steady-state value of the supercapacitor state of charge and multiple photovoltaic power step changes to determine if the closed-loop system remains robust from a performance standpoint around its nominal design. The H ∞ control design procedure allows a further investigation on how to link time-domain dynamic performance specifications (e.g., desired control objectives) and frequency-domain specifications (e.g., via so-called weighting functions) in a systematic and optimal manner (i.e., automation for their design or expert modelling), from which an useful guide can be created for practical control engineers in the future. Distinct photovoltaic penetration rate scenarios together with respective computed H ∞ controllers, on the other hand, are examined to determine whether or not an H ∞ optimal control solution that is robust in performance to a variety of photovoltaic power step variations relative to the rated operating point can always be generated.

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“…Pitch angle can be controlled according to power speed curve shown in Figure 2. The pitch control system can be illustrated by subdividing the power speed curve into four regions [29]:…”

Section: Blade Pitch Systemmentioning

confidence: 99%

“…Bacterial forging optimization (BFO) is designed in [28]. H ∞ control has been applied to control the pitch angle, as in [29,30]. The differential evaluation algorithm technique is used for tuning the PI pitch controller in [31,32].…”

Section: Introductionmentioning

confidence: 99%

Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm

et al. 2019

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Frequency control represents a critically significant issue for the enhancement of the dynamic performance of isolated micro grids. The micro grid system studied here was a wind-diesel system. A new and robust optimization technique called the mine blast algorithm (MBA) was designed for tuning the PID (proportional-integral-differential) gains of the blade pitch controller of the wind turbine side and the gains of the superconducting magnetic energy storage (SMES) controller. SMES was implemented to release and absorb active power quickly in order to achieve a balance between generation and load power, and thereby control system frequency. The minimization of frequency and output wind power deviations were considered as objective functions for the PID controller of the wind turbine, and the diesel frequency and power deviations were used as objective functions for optimizing the SMES controller gains. Different case studies were considered by applying disturbances in input wind, load power, and wind gust, and sensitivity analysis was conducted by applying harsh conditions with varying fluid coupling parameter of the wind-diesel hybrid system. The proposed MBA-SMES was compared with MBA (tuned PID pitch controller) and classical PI control systems in the Matlab environment. Simulation results showed that the MBA-SMES scheme damped the oscillations in the system output responses and improved the system performance by reducing the overshoot by 75% and 36% from classical and MBA-based systems, respectively, reduced the settling time by 45% compared to other systems, and set the final steady-state error of the frequency deviation to zero compared to other systems. The proposed scheme was extremely robust to disturbances and parameter variations.

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A robust H∞ controller based frequency control approach using the wind-battery coordination strategy in a small power system

Cited by 50 publications

References 32 publications

Survey of Strategies to Optimize Battery Operation to Minimize the Electricity Cost in a Microgrid With Renewable Energy Sources and Electric Vehicles

Survey of Strategies to Optimize Battery Operation to Minimize the Electricity Cost in a Microgrid With Renewable Energy Sources and Electric Vehicles

Frequency Robust Control Application in Islanded Microgrids Considering Parametric Uncertainties and Distinct Photovoltaic Penetration Rate Scenarios

Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm

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