Real-Time Co-Simulation Platform for Smart Grid Volt-VAR Optimization Using IEC 61850

Manbachi, Moein; Shrivastava, Abhinav; Farhangi, Hassan; Monti, Antonello; Palizban, Ali; Ponci, Ferdinanda; Arzanpour, Siamak

doi:10.1109/tii.2016.2569586

Cited by 81 publications

(36 citation statements)

References 17 publications

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“…As can be concluded from Figure 7, most research are done considering the combination of noncoordinated energy management and cost optimization or power quality. The combination of customer-driven objectives with coordinated energy 84 Representing a simulation platform based on IEC61850 for microgrids 85 Validating proposed strategy for power management of multi DER microgrids with NI-cRIO 55 Validating proposed decentralized robust control of islanded microgrids 56 Testing control algorithms and management strategies for microgrid 88 Validating proposed protection method for microgrid with RTDS and dSPACE processor board 89 Validating control scheme of a hybrid energy storage system in the microgrid 90 Development of an RT hardware test bed in order to analyze the transient stability of a simulated power system by using PMU 91 Laboratory prototype…”

Section: Discussionmentioning

confidence: 99%

A review on real‐time simulation and analysis methods of microgrids

Ahmadiahangar

Rosin

Niaki

et al. 2019

Int Trans Electr Energ Syst

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Summary Microgrid is a recently developed concept for future power systems. The main characteristics of the microgrid are the capability of integration of renewable energy sources and the ability to operate in two grid‐connected and islanded modes. A significant challenge of microgrid implementation is developing comprehensive control methods to ensure efficient, stable, and reliable operation. Real‐time studies are a promising approach in this case. In this paper, various real‐time energy management approaches have been thoroughly explained following a new categorization of them. A significant literature review of real‐time simulation and modeling methods has also been presented. A review of different applications of hardware‐in‐the‐loop testing of the microgrid is included in the present study. Finally, a discussion on demand for further research has been made. The presented work is organized to allow a reader to understand the importance of real‐time studies of microgrids and highlight trends in literary works without delving deeply into each one.

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Section: Discussionmentioning

confidence: 99%

A review on real‐time simulation and analysis methods of microgrids

Ahmadiahangar

Rosin

Niaki

et al. 2019

Int Trans Electr Energ Syst

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“…The concern of the response time of a simulation could be seen in [10] by using PSCAD\NS2 (Network Simulator 2), in [11] by using PSFL\NS2 [12][13][14][15] it is possible to see an effort and concern for this integration or co-simulation and thus validate the results in the new context of the intelligent network. You can still find other researchers of multiagent system applied to microgrid [16][17][18][19][20][21][22] where the telecommunications system was not included.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

et al. 2018

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This paper presents a framework to analyze the problem of real-time management of Smart Grids. For this purpose, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems (MAS) leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. With this framework it was possible to evaluate the design of the energy management and the impact of the algorithm developed in the MAS. In the same way, the data sent from the power system to be used for energy management have a direct impact on his behavior. The proposed framework is tested with the help of a microgrid, so the results may be replicated.

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“…[120], [121]) or introduce complex substation protocols (e.g. [59], [123]) or are dedicated to phasor-based investigations with limited flexibility to other types of data and studies (e.g. [121], [122]).…”

Section: Resultsmentioning

confidence: 99%

“…Although not very popular, there have been proposed controllers which provide control optimisation by means of Genetic Algorithms (GA), Fuzzy Logic or Particle Swarm approach. In particular, study [59] elaborates on an improved GA used in a centralised control method. However, considering long reaction time (i.e.…”

Section: Swarm Algorithmsmentioning

confidence: 99%

“…Yet another popular trend is to implement the RTDS-MATLAB platform but with use of substation protocols. Namely, the study [59] utilises IEC61850 standard and Goose Messages to send data to an OPC server and pass it forward to a MATLAB-based algorithm. Similarly, in [123], the Volt-Var optimiser retrieves data via DNP.3 protocol combined with an OPC server.…”

Section: Online Co-simulation Platformsmentioning

confidence: 99%

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Voltage control in power distribution grids equipped with large-scale renewable energy sources

Krata¹

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High integration of renewable energy sources (RESs) and battery energy storage systems (BESS) into power distribution networks brings new challenges to grid control schemes. The old assumption of unidirectional power flow (from transmission system to loads) is no longer valid when almost every load bus can become temporarily or permanently a generation bus due to increasing power from renewable sources such as photovoltaic (PV) generation. In fact, a power flow direction can alter at any grid location many times a day, impacting existing voltage regulation schemes. In particular, due to the lack of coordination between different voltage control apparatus, a dynamic change in PV generation can cause the grid voltage magnitude to go beyond acceptable limits. Hence, daily power fluctuations, e.g. caused by moving clouds, can lead to over-or under-voltage situations with a regulation time that takes minutes before the voltage is recovered and the grid is ready for a next, unexpected disturbance. This prolonged and inaccurate traditional regulation process affects electrical devices connected to grids with medium-and large-PV generation. Even more importantly, insufficient voltage regulation can prevent new developments of RESs plants because power utility companies might not allow for more RESs generation if a grid voltage is prone to fluctuate.This research is focused on the behaviour of power distribution systems exposed to large-scale PV generation and BESS facilities. Specifically, the study aims to address questions of how those modern power technologies influence voltages and their control in a distribution network as well as how to improve cooperation between traditional and modern grid regulation devices by means of advanced control strategies. To answer the research questions, the study investigates the real-time performance of a distribution grid voltage control in the presence of dynamically changing large-scale RESs and BESS generation and provides a novel real-time coordinated control to address voltage fluctuations caused by uncertain PV generation. Furthermore, the developed voltage control method is based on a model-driven approach with the real-time controller predicting hundreds of possible regulation trajectories and choosing the one that fulfils optimisation criteria the most. In addition, the multidimensional, nonlinear, mixed-integer optimisation is executed based on parallel-computed time-series grid simulations, which reproduce grid behaviour, incorporate mutual interactions of voltage controllers and ii account for PV variability. Uniquely, the algorithm also considers autonomous responses from upstream voltage regulation devices and includes them into the solution.Next, the investigation was conducted on real-time models of a semi-rural grid located in South-East Queensland, Australia, with a large-scale PV plant (3.15MWp of power) and BESS facility as large as 0.6MW/0.76MWh. As a result of implementing the proposed control coordination to the studied grid, voltage fluctuations caused by dyn...

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Real-Time Co-Simulation Platform for Smart Grid Volt-VAR Optimization Using IEC 61850

Cited by 81 publications

References 17 publications

A review on real‐time simulation and analysis methods of microgrids

A review on real‐time simulation and analysis methods of microgrids

Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

Voltage control in power distribution grids equipped with large-scale renewable energy sources

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