GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

Chassin, David P.; Fuller, Jason C.; Djilali, Ned

doi:10.1155/2014/492320

Cited by 157 publications

(81 citation statements)

References 26 publications

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“…A notable exception for distribution system analysis is the open-source package GridLAB-D [43]. Since this is an open-source software, the reliability analysis component could be incorporated.…”

Section: B Simulation Toolmentioning

confidence: 99%

Reliability Modeling Considerations for Emerging Cyber-Physical Power Systems

Aravinthan

Balachandran

Benidris

et al. 2018

2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

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Section: B Simulation Toolmentioning

confidence: 99%

Reliability Modeling Considerations for Emerging Cyber-Physical Power Systems

Aravinthan

Balachandran

Benidris

et al. 2018

2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

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“…GridLAB-D is a new type of power system simulation tool, which uses an agent-based approach to simulating smart grids [42]. It contains different modules with specific functions, such as power flow module, residential module and so on.…”

Section: Simulation and Case Studiesmentioning

confidence: 99%

A Kriging Model Based Optimization of Active Distribution Networks Considering Loss Reduction and Voltage Profile Improvement

Wang

Tang

et al. 2017

Energies

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Optimal operation of the active distribution networks (ADN) is essential to keep its safety, reliability and economy. With the integration of multiple controllable resources, the distribution networks are facing more challenges in which the optimization strategy is the key. This paper establishes the optimal operation model of the ADN considering a diversity of controllable resources including energy storage devices, distributed generators, voltage regulators and switchable capacitor banks. The objective functions contain reducing the power losses and improving the voltage profiles. To solve the optimization problem, the Kriging model based Improved Surrogate Optimization-Mixed-Integer (ISO-MI) algorithm is proposed in this paper. The Kriging model is applied to approximate the complicated distribution networks, which speeds up the solving process. Finally, the accuracy of the Kriging model is validated and the efficiency among the proposed method, genetic algorithm (GA) and particle swarm optimization (PSO) is compared in an unbalanced IEEE-123 nodes test feeder. The results demonstrate that the proposed method has better performance than GA and PSO.

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“…GridLAB-D [8] is a comprehensive power distribution simulation and analysis tool, which also includes building models and control algorithms. However, its co-simulation capability is limited, e.g., it does not provide an EnergyPlus interface and its Matlab interface is primitive.…”

Section: B Related Workmentioning

confidence: 99%

OpenBuildNet framework for distributed co-simulation of smart energy systems

Nghiem

Bitlislioğlu

Gorecki

et al. 2016

2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV)

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Abstract-The complexity and diversity of future energy systems will require co-simulation solutions that enable the integration of tools from multiple domains for research and development.We introduce an open-source framework, OpenBuildNet, for distributed co-simulation of large-scale smart energy systems. Using a loose-coupling approach to co-simulate parallel processes, it can leverage and seamlessly integrate specialized simulation and computation tools in a common platform. Users can therefore benefit from the capabilities of state-of-the-art and widely used tools in each domain. OpenBuildNet is scalable and highly flexible as it uses a decentralized architecture, message-based communication, and peer-to-peer data exchange between subsystem nodes. It also provides a set of easy-to-use software tools tailored for researchers and engineers. This paper presents the architecture and tool suite of OpenBuildNet, and demonstrates its usefulness in a case study of controlling multiple buildings for demand response.

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GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

Cited by 157 publications

References 26 publications

Reliability Modeling Considerations for Emerging Cyber-Physical Power Systems

Reliability Modeling Considerations for Emerging Cyber-Physical Power Systems

A Kriging Model Based Optimization of Active Distribution Networks Considering Loss Reduction and Voltage Profile Improvement

OpenBuildNet framework for distributed co-simulation of smart energy systems

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