Resilient planning of PowerLine Communications networks over Medium Voltage distribution grids

Canale, Silvia; Priscoli, Francesco Delli; Giorgio, Alessandro Di; Lanna, Andrea; Mercurio, Andrea; Panfili, Martina; Pietrabissa, Antonio

doi:10.1109/med.2012.6265721

Cited by 23 publications

(9 citation statements)

References 18 publications

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“…The actual distribution network for low voltage customers appears inadequate to comply with these improvements. Smart grid is widely recognized as the new solution that must be developed to manage distributed network tackling the increment of renewable energies [25]- [28]. For these reasons it is necessary a new system to solve these problems increasing the system reliability and security, improving the efficiency making more possible more interaction between users and grid and finally achieve flexible, accessible and sustainable electricity networks [29]- [31].…”

Section: Discussionmentioning

confidence: 99%

Technologies for smart grids: A brief review

Falvo

Martirano

Sbordone

et al. 2013

2013 12th International Conference on Environment and Electrical Engineering

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In electrical power systems smart grid is widely recognized as the new solution that must be developed to manage distributed network tackling the increment of renewable energies. Through monitoring capability, data integration, effective communication, advanced analysis and system control the smart grid can meet the power demand as well as increase total efficiency and reduce consumption and costs. Many different technologies must converge to create a smart grid as a storage systems utilized as an energy buffer, telecommunication systems that can exchange data with sensors and actuators, advanced control systems that monitor the power grid and manage energy flows in real time. This paper reviews the state of the art of present application of these technologies in smart grids. The specific focus of the work is on telecommunication systems to have a monitoring through last smart metering application. The impacts and benefits of real time controls are investigated to improve the power efficiency, security and quality. © 2013 IEEE

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Section: Discussionmentioning

confidence: 99%

Technologies for smart grids: A brief review

Falvo

Martirano

Sbordone

et al. 2013

2013 12th International Conference on Environment and Electrical Engineering

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“…The presented algorithm lead to the overall energy efficiency improvement by making an optimal demand and supply control taking into account energy pricing. Concerning the communication between the system and the components of the grid, it will be ensured by a Power Line Communication (PLC) network connected to each node [34] as illustrated by the dashed redline in Fig.2. This line will communicate the different active and reactive energies besides the voltages at the PCC to the DNO.…”

Section: 2algorithm Descriptionmentioning

confidence: 99%

Untitled

2019

JESTR

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The energy flow management in distribution networks started to worry grid operators since the challenge of exploiting natural resources such as solar irradiance and wind speed to produce electricity became a reality. Due to their intermittent nature, mismanagement of these resources can result in a severe bidirectional energy flow; likewise, notable imbalances between demand and generation in the electrical lines. Consequently, this may engender excessive energy losses and could violate electrical component characteristics. However, a predictive management of these resources can allow for the forecast of the different existing electrical device regulations beside the energy needed to be produced by conventional generations in a vertically-integrated system. For that purpose, we present in this paper a Model Predictive Control approach applied on a distribution feeder connected to renewable distributed generators and supplied by a High Voltage/Medium Voltage substation through transmission lines. We associated to this model a regulating algorithm for energy optimization and cost minimization. The control strategy outputs are the active and reactive energy predicted to be injected by the substation into the feeder. Finally, we evaluated the accurateness of the proposed method and we identified the parameters that affect its precision error.

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“…Finally, the proposed MPC control algorithm can be hosted either at the level of the DSO SCADA control centre, or locally at the ESS level, with field data retrieved, respectively, through a telecommunication infrastructure or through the DSO electric infrastructure (e.g. through Power Line Communications (PLC) [17]).…”

Section: Reference Scenariomentioning

confidence: 99%

Model Predictive Control of Energy Storage Systems for Power Tracking and Shaving in Distribution Grids

Giorgio

Liberati

Lanna

et al. 2017

IEEE Trans. Sustain. Energy

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In this paper, a model predictive control (MPC)\ud strategy is proposed to control the energy flows in a distribution\ud network node (e.g. a distribution substation) equipped with an\ud electric storage system (ESS) and serving a portion of the grid\ud with high penetration of renewable energy sources (RES). The\ud aim is to make the power flow at node level more controllable in\ud spite of the presence of fluctuating distributed energy resources.\ud In particular, the proposed control strategy is such that the\ud controlled power flow at node level tracks the profile established\ud on a day-ahead basis for efficient operation of the grid. That is\ud achieved by letting the MPC controller decide the current storage\ud power setpoint based on the forecasts of the demand and of the\ud RES output. Theoretical results are reported on the stability of\ud the proposed control scheme in a simplified setting foreseeing\ud zero forecasting error. The performance of the system in the\ud general case is then evaluated on a simulation basis. Simulations\ud show the effectiveness in managing RES fluctuations in realistic\ud settings

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Resilient planning of PowerLine Communications networks over Medium Voltage distribution grids

Cited by 23 publications

References 18 publications

Technologies for smart grids: A brief review

Technologies for smart grids: A brief review

Untitled

Model Predictive Control of Energy Storage Systems for Power Tracking and Shaving in Distribution Grids

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