Using renewable energy as power source is of great importance in our modern society. In this work, design and implementation of hybrid energy storage system to provide electricity from solar energy in a consistent manner is demonstrated. Different computational intelligence algorithms and methods, namely support vector machines, neural networks together with evolutionary optimisation algorithms, have been used to minimise the production costs and eliminate power cut during peak hours of electricity consumption. Support vector machines and neural networks have been applied for prediction of the electricity consumption during the peak hours, and evolutionary optimisation algorithms have been used for minimising the production costs and finding the optimal numbers of components in the hybrid energy storage system.
|Publication status||Published - 2021|
|Event||The 12th Asia-Pacific Power and Energy Engineering Conference - Xi'an, China|
Duration: 17 Apr 2021 → 19 Apr 2021
Conference number: 12
|Conference||The 12th Asia-Pacific Power and Energy Engineering Conference|
|Abbreviated title||APPEEC 2021|
|Period||17/04/21 → 19/04/21|