• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.557-560
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• 2021

In the face of the COVID-19 pandemic, the Korean Government announced the Korean New Deal as a national development strategy to overcome the economic recession from the pandemic crisis and lead the global action aginst sturctural changes. The Green New Deal related with the energy aims to achieve net-zero emissions and accelerates the transition towards a low-carbon and green economy. To this end, the government plans to promete an increased use of renewable energy in the the society at large. This paper introduces a compact-binary power plant using unused thermal energy and a control system based on Neural Network in order to accelerate the transition towards a low-carbon and green economy. It is expected that he compact-binary power plant accelerate introduction of renewable energy along with solar and wind power.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1495-1504
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• 2021

An ultra-compact binary power generation plant converts thermal energy into electric power using temperature difference between heat source and cooling source. In the actual power generation environment, the characteristic value of the plant changes due to any negative effects such as environmental condition or corrosion of related equipment. If the characteristic value of the plant changes, it may lead to unstable output of the turbine in a conventional PID control system with fixed PID parameters. A Neuro PID control system based on Neural Network adaptively to adjust the PID parameters according to the change in the characteristic value of the plant is proposed in this paper. Discrete-time transfer function models to represent the dynamic characteristics near the operating point of the investigated plant are deduced, and a design strategy of the proposed control system is described. The proposed Neuro PID control system is compared with the conventional PID control system, and its effectiveness is demonstrated through the simulation results.