Software models for Smart Grid

Singhal,; Saxena,

doi:10.1109/se4sg.2012.6225717

Cited by 32 publications

(8 citation statements)

References 5 publications

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“…However, the term Smart Grid (SG) is a nebulous term spanning various functionalities geared towards modernizing the power grid. At its core, a smart grid utilizes digital communications and control systems to monitor and control power flows, with the goal of making the power grid more resilient, efficient and cost effective [6]. Coordinated charging can help to reduce the pressure on EG in compari-son with uncoordinated charging.…”

Section: Pevs' Effect On Electrical Gridmentioning

confidence: 99%

Futuristic model of electric vehicle charging queues

Akbari¹

2021

Preprint

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The use of PEVs (Plug-in Electric Vehicles) is fast expanding due to their low energy cost and low environmental pollution. However, a big hurdle is that PEVs have a short driving range and long battery charging time even when using supercharging stations. There- fore, better queuing models are necessary to improve the quality of services using public charging stations. This thesis develops an approach for estimating various discharging profiles of PEV batteries considering different regional driving cycles. Each driving cycle generates a unique discharging profile. These discharging profiles were employed in a computer model to study recharging process of PEVs in public charging stations. More- over, a unique utility function is construed which is optimized to minimize the overall waiting time for consumers and harmonize the queue size in each charging station. This model uses Toronto downtown area as a case study.

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Section: Pevs' Effect On Electrical Gridmentioning

confidence: 99%

Futuristic model of electric vehicle charging queues

Akbari¹

2021

Preprint

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“…While in [13][14] PI and PID controller have been utilized to manage the supply side price, Kaygusuz [15] has proposed a PI controller which regulates the demand side price to ensure an equilibrium between demand and generation in an electricity grid. side resources [16]. Pricing strategies contemplate the unit price and weather conditions on supply side, comfort requirements and electricity availability from decentralized generation on demand side whether to use or store or sell electricity.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic Reasoning Based Real Time Energy Price Regulation Approach for Smart Grids

Çakmak

ÇAKANEL>

2019

Mugla Journal of Science and Technology

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Intelligent technologies have become pioneer force to provide flexible, dynamic and efficient energy generation and management. Thus, smart algorithms such as fuzzy logic, artificial neural network, machine learning, soft computing techniques are sole remedy against growing diverse and numerous distributed generations that make more complicated power systems. Real time closed loop controlling requires energy price as a featured variable to procure supply demand equilibrium point for a stable and reliable power system operation, where several dynamic models and estimation software are introduced in the literature. In this study, a fuzzy logic reasoning-based price regulator (FLR-PR) is designed and simulated on MATLAB/Simulink environment using 2018 hourly data of a summer day taken from annual energy report of Turkey. The proposed model has been compared to Proportional Integral Derivative (PID) price controller based on performance indexes in the constituted simulation cases. FLR-PR tracks instant reference demand signal changes with minimum steady state error and fast transient response with respect to PID controller.

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“…Electrical smart or micro grids extensively utilize modern control, communication and signal processing techniques to optimize the efficiencies of its constituents [3,4], while also utilizing advanced sensing and measurement instruments to supply green and clean power to consumers [5][6][7]. Steady increase in fossil fuels and other natural resources for superior power systems further led to green technologies, i.e., power generation systems utilizing renewable energy sources such as water, photovoltaic or wind.…”

Section: Introductionmentioning

confidence: 99%

“…Smart grids implement the green technologies along with conventional power generation plants to produce power in a more economical and ecological manner [3,8], especially under steadily increasing power demand, increasing scarcity in fossil fuels, and broader and justifiable concerns on environmental factors. However, the optimal integration of smart grid components and green technologies has proved to be sufficiently complex to warrant advanced modeling, control and optimization algorithms for stable, economical, ecological and reliable power system performance objectives under different types of uncertainties, varying communication channel characteristics and time-varying or nonlinear power source dynamics [3][4][5][6][8][9][10][11]. Also, various dynamical modeling and model-based as well as intelligent control implementations of microgrid safe and economical operations have been utilized to address the underlying complexities.…”

Section: Introductionmentioning

confidence: 99%

Linear Parameter Varying Modeling and Control of a Nonlinear Power Plant

Kamalapur

Yilmaz

Adediran

2015

2015 Seventh Annual IEEE Green Technologies Conference

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This study explores different Linear Parameter Varying (LPV) modeling approaches and optimization methodology for a nonlinear hydro power plant. The overall hydro plant dynamics is assumed to be decomposable to its subsystems whose overall characteristics involve different dynamical behaviors related to two real-time time-varying parameters that can be measurable in future periods. The hydro plant dynamics are expressed in terms of an LPV model with two time-varying parameters to efficiently characterize the plant dynamical variations to compare as well as achieve superior modeling, analysis and control frameworks, especially in contemporary smart grid networks. The two-parameter LPV hydro plant model control system configurations and corresponding simulations illustrate a valuable computational tool for nonlinear power plant optimization.

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Software models for Smart Grid

Cited by 32 publications

References 5 publications

Futuristic model of electric vehicle charging queues

Futuristic model of electric vehicle charging queues

A Fuzzy Logic Reasoning Based Real Time Energy Price Regulation Approach for Smart Grids

Linear Parameter Varying Modeling and Control of a Nonlinear Power Plant

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