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The Ingram School of Engineering at Texas State University-San Marcos is embarking on a research project focusing on distributed generation systems using Lanner’s Witness simulation software.

The research project proposes a simulation-based method for designing the optimal configuration that integrates alternative energy resources, such as wind turbines and solar photovoltaics (PV), into existing electric grid systems.

The simulation model comprises a power plant, a wind farm, and a PV-based system.

It incorporates the random power outputs associated with wind turbines and PVs.

Witness simulation language was selected for the modelling effort.

Saul Villarreal and Greg Guzman, industrial engineering majors, are leading the project; Dr Jesus A Jimenez and Dr Tongdan Jin are the faculty mentors.

Mandy Tague, director of business development – Americas at Lanner, explained that as renewable energy penetrates the utility market, the electricity industry is undergoing a paradigm shift that will lead to a fundamental change in the way of supplying electricity through distributed generation systems.

Tague said: ‘Process improvement software has to be adaptable to any scenario it is introduced to.

‘Witness works by enabling the user to represent real-world processes in a dynamic animated computer model, allowing experimentation with alternative “what-if” scenarios,’ Tague added.

Witness software’s interface is intuitive and quick to learn, Tague said.

The simulation modelling software is used in engineering courses taught at Texas State’s Ingram School of Engineering as well as at the school’s Center for High-Performance Systems, where students and faculty conduct research on production logistics, systems design, semiconductor manufacturing, material handling systems and intelligent transportation systems.

Lanner’s current Witness simulator suite is designed to help firms simulate and analyse how corporate decisions will affect the environment.

The simulation-modelling software’s functionality covers a range of environmental metrics, including carbon emissions and electricity, oil, water, gas and steam use.

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