Dynamic microgrid-based operations: A new operational paradigm for distribution networks

Jose, Joel; Kowli, Anupama; Bhalekar, Vaibhav; Prasad, K.; Rajagopal, N.A.

doi:10.1109/isgt-asia.2016.7796446

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…A MG refers to a small/medium-scale power system comprising distributed generation (DG), distributed storage (DS), local/distributed loads, and multistage control systems for voltage and frequency regulation. 2 The characteristics of a MG include a critically defined electrical limit, a dedicated master controller that controls the distributed energy resource (DER) and load as a single controllable entity, and installed generation capacity must exceed the maximum load so that it can work even in island mode and supply the critical loads. 3 There is a growing demand for off-grid MGs by remotely located rural population, and there are efforts made by several urban organizations and communities to reduce their dependency on the main grid and increase participation in power exchange with main grid.…”

Section: Discussionmentioning

confidence: 99%

“…This newly deployed sources‐based power system is referred as microgrid (MG) which is a small‐scale version of the conventional grid. A MG refers to a small/medium‐scale power system comprising distributed generation (DG), distributed storage (DS), local/distributed loads, and multistage control systems for voltage and frequency regulation . The characteristics of a MG include a critically defined electrical limit, a dedicated master controller that controls the distributed energy resource (DER) and load as a single controllable entity, and installed generation capacity must exceed the maximum load so that it can work even in island mode and supply the critical loads .…”

Section: Introductionmentioning

confidence: 99%

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Frequency regulation in islanded microgrid considering stochastic model of wind and PV

Kumar

Mathur

Bhanot

et al. 2019

Int Trans Electr Energ Syst

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Summary This paper addresses the method of forecasting the wind and solar power and its application to an islanded microgrid (MG) model for load frequency control. Due to high penetration of renewable energy sources, the islanded MG suffers from lower equivalent inertia. The islanded MG faces several challenges in order to ensure the stable operation by maintaining the frequency and voltage at nominal value. The supply and demand power mismatch is mainly due to continuously changing solar irradiance, fluctuating wind speed, variable inertia, and load fluctuations. The intermittent nature of RESs can significantly affect the system stability; hence, the challenge lies in accurate forecasting of power from the renewable energy sources (RESs) so that a proactive arrangement is made available for compensation of active power or frequency variations. The forecasting will determine the correct estimate of power availability so that the power reserves can be activated prior to large variations in active power affecting the stability of the MGs. To address these challenges, a stochastic model of wind and solar has been developed using “Time series modeling” of the data obtained from Charanka Solar Park under Gujarat Energy Development Agency, India. Wind and solar power availability are forecasted using autoregressive integrated moving average (ARIMA) method including the seasonality factor. The proportional and integral (PI) controller is used for regulating the frequency fluctuations caused due to intermittency in the output of RESs and load power. Various load patterns are applied to the MG model to analyze its load frequency behavior along with variations in secondary sources.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Frequency regulation in islanded microgrid considering stochastic model of wind and PV

Kumar

Mathur

Bhanot

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

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“…In a centralised EMS, all MG resources in an NMG are scheduled by a central EMS for optimal energy sharing between MGs [70][71][72]. Figure 8(a) shows the centralised EMS structure of an NMG.…”

Section: Optimisation Of Energy In Nmgsmentioning

confidence: 99%

Control and optimisation of networked microgrids: A review

Islam

Yang

Ամին

2021

IET Renewable Power Gen

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Microgrids (MGs) have become an integral part of smart grid initiatives for future power system networks. Networked microgrids consist of several neighbouring microgrids connected in a low/medium distribution network. The primary objective of a network is to share surplus/shortage power with neighbouring microgrids to achieve mutual cost‐effective operation, utilising green energy from renewable energy resources in the network and increasing the reliability of customer service. This article classifies networked microgrids on the basis of network formation and provides an overview of recent research on control of networked microgrids. In addition, a state‐of‐the‐art review of optimisation methods is provided to solve the energy optimisation problem in networked microgrids. Furthermore, the advantages and challenges of the networked operation of microgrids are presented as for possible research directions in the future.

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“…The work done by [9] considers a dynamic MG as one with flexible boundaries that expand or shrink to maintain the balance between power generation and power consumption. The work in [10] considers the paradigm of a dynamic MG as a mechanism to continuously partition a DN based on the balance between electricity generation and demand.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model for the Scheduling of Virtual Microgrids Topology into an Active Distribution Network

2020

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This article presents a method based on a mathematical optimization model for the scheduling operation of a distribution network (DN). The contribution of the proposed method is that it permits the configuration and operation of a DN as a set of virtual microgrids with a high penetration level of distributed generation (DG) and battery energy storage systems (BESS). The topology of such virtual microgrids are modulated in time in response to grid failures, thus minimizing load curtailment, and maximizing local renewable resource and storage utilization as well. The formulation provides the load reduced by bus to balance the system at every hour and the global probability to present energy not supplied (ENS). Furthermore, for every bus, a flexibility load response range is considered to avoid its total load curtailment for small load reductions. The model has been constructed considering a linear version of the AC optimal power flow (OPF) constraints extended for multiple periods, and it has been tested in a modified version of the IEEE 33-bus radial distribution system considering four different scenarios of 72 h, where the global energy curtailment has been 27.9% without demand-side response (DSR) and 10.4% considering a 30% of flexibility load response. Every scenario execution takes less than a minute, making it appropriate for distribution system operational planning.

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Dynamic microgrid-based operations: A new operational paradigm for distribution networks

Cited by 9 publications

References 9 publications

Frequency regulation in islanded microgrid considering stochastic model of wind and PV

Frequency regulation in islanded microgrid considering stochastic model of wind and PV

Control and optimisation of networked microgrids: A review

A Mathematical Model for the Scheduling of Virtual Microgrids Topology into an Active Distribution Network

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