KEYWORDS: Device simulation, Network security, Defense and security, Data communications, Simulink, Computer simulations, MATLAB, Telecommunications, Communication and information technologies, Renewable energy
Demand response is one of key smart grid applications that aims to reduce power generation at peak hours and maintain
a balance between supply and demand. With the support of communication networks, energy consumers can become
active actors in the energy management process by adjusting or rescheduling their electricity usage during peak hours
based on utilities pricing incentives. Nonetheless, the integration of communication networks expose the smart grid to
cyber-attacks. In this paper, we developed a smart grid simulation test-bed and designed evaluation scenarios. By
leveraging the capabilities of Matlab and ns-3 simulation tools, we conducted a simulation study to evaluate the impact
of cyber-attacks on demand response application. Our data shows that cyber-attacks could seriously disrupt smart grid
operations, thus confirming the need of secure and resilient communication networks for supporting smart grid
operations.
The smart grid is the integration of computing and communication technologies into a power grid with a goal of enabling real time control, and a reliable, secure, and efficient energy system [1]. With the increased interest of the research community and stakeholders towards the smart grid, a number of solutions and algorithms have been developed and proposed to address issues related to smart grid operations and functions. Those technologies and solutions need to be tested and validated before implementation using software simulators. In this paper, we developed a general smart grid simulation model in the MATLAB/Simulink environment, which integrates renewable energy resources, energy storage technology, load monitoring and control capability. To demonstrate and validate the effectiveness of our simulation model, we created simulation scenarios and performed simulations using a real-world data set provided by the Pecan Street Research Institute.
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