Networked Microgrids: State-of-the-Art and Future Perspectives

Alam, Mahamad Nabab; Chakrabarti, Saikat; Ghosh, Arindam

doi:10.1109/tii.2018.2881540

Cited by 200 publications

(151 citation statements)

References 74 publications

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“…The continuous-time state space model for the frequency control of an islanded microgrid is defined by Equations (1) and (2).…”

Section: Subsystem Transfer Function Parametersmentioning

confidence: 99%

“…In the past decade, microgrids have been widely studied because of their potential environmental and economic benefits in regard to the integration distributed energy resources, especially renewable energy systems [1][2][3]. Due to the different types of distributed energy resources, dynamical load characteristics, power quality constraints, and perturbed system parameters, how to optimize control of a microgrid, for it to operate well under grid-connected and islanded modes, has been a challenging issue [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

et al. 2018

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Optimal frequency control of an islanded microgrid has been a challenging issue in the research field of microgrids. Recently, fractional-order calculus theory and some related control methods have attempted to handle this issue. In this paper, a novel fractional-order model predictive control (FOMPC) method is proposed to achieve the optimal frequency control of an islanded microgrid by introducing a fractional-order integral cost function into model predictive control (MPC) algorithm. Firstly, a discrete state-space model is derived for the optimal frequency control problem of an islanded microgrid. Afterward, a fractional-order integral cost function is designed to guide the FOMPC algorithm to obtain optimal control law by borrowing the Grünwald-Letnikov (GL) definition of fractional order calculus. Six simulation studies have been carried out to illustrate the superiority of FOMPC to conventional MPC under dynamical load disturbances, perturbed system parameters and random dynamical power fluctuation of wind turbines.

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“…The continuous-time state space model for the frequency control of an islanded microgrid is defined by Equations (1) and (2).…”

Section: Subsystem Transfer Function Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

et al. 2018

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show abstract

“…In the last few years, there has been a growing interest in the development of microgrids (MGs) for enhancing power system reliability, better power quality and reducing the environmental impacts [1,2]. An MG is a small-scale power system with distinct electrical boundaries with the capability of supplying its loads autonomously when it is islanded from the main grid [3]. One of the main characteristics of MG is that it consists of different types of power sources such as distributed generations (DGs) and energy storage systems [4,5].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Use of Reinforcement Learning for Integrated Voltage/Frequency Control in AC Microgrids

2020

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The main purpose of this paper is to present a novel algorithmic reinforcement learning (RL) method for damping the voltage and frequency oscillations in a micro-grid (MG) with penetration of wind turbine generators (WTG). First, the continuous-time environment of the system is discretized to a definite number of states to form the Markov decision process (MDP). To solve the modeled discrete RL-based problem, Q-learning method, which is a model-free and simple iterative solution mechanism is used. Therefore, the presented control strategy is adaptive and it is suitable for the realistic power systems with high nonlinearities. The proposed adaptive RL controller has a supervisory nature that can improve the performance of any kind of controllers by adding an offset signal to the output control signal of them. Here, a part of Denmark distribution system is considered and the dynamic performance of the suggested control mechanism is evaluated and compared with fuzzy-proportional integral derivative (PID) and classical PID controllers. Simulations are carried out in two realistic and challenging scenarios considering system parameters changing. Results indicate that the proposed control strategy has an excellent dynamic response compared to fuzzy-PID and traditional PID controllers for damping the voltage and frequency oscillations.

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“…The intermittent nature of renewable sources demands the inclusion of storage for improved reliability [13]. The charging station may be a stand-alone charging unit or may be a part of a microgrid [14,15] which requires an energy management controller [16]. A vast majority of the charger topologies are still grid dependent which undermine the clean energy image of the electric vehicle.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Simulation of Efficient Energy Management Algorithms for Electric Vehicle Chargers

Krishnamoorthy¹,

Narayanan²,

Kannan³

2020

Intelligent and Efficient Transport Systems - Design, Modelling, Control and Simulation

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Transportation electrification is happening at a rapid pace around the globe in response to the climate change mitigation measures taken by the regulatory agencies to curb tailpipe emissions. As the electric vehicle technology evolved, the size of on-board storage units has increased, which require charging from an external energy source. Renewable charging of electric vehicles is an attractive option to reduce the carbon footprint of an electric vehicle. The intermittent nature of the renewables necessitates a storage unit to provide continuous power. With a battery complementing solar generation, a power converter is deployed to interface these sources and storage units with the electric vehicle for charging. The converter shall now have to operate to quench the charging requirements by sourcing power from solar generation and storage elements. The converter also has to capture the generated solar power during the non-charging period and store it in the battery. All these functional requirements demand a robust energy management strategy to utilize all available sources and storage units efficiently without compromising load requirements. A Stateflow-based energy management algorithm for a three-port converter is proposed in this work. The proposed algorithm is implemented using OPAL-RT, and the real-time simulation results are presented.

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Networked Microgrids: State-of-the-Art and Future Perspectives

Cited by 200 publications

References 74 publications

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Assessing the Use of Reinforcement Learning for Integrated Voltage/Frequency Control in AC Microgrids

Real-Time Simulation of Efficient Energy Management Algorithms for Electric Vehicle Chargers

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