Optimal configuration of double carbon energy system considering climate change

How to achieve the double carbongoal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the double carbongoal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's double carbongoal, CPES and CNES need to increase their costs by 1.97% and 2% respectively.

Automated summary

This study proposes an approach that integrates machine learning and the honey badger algorithm to examine the impact of climate change on integrated energy systems (IES) and explores strategies to achieve the double carbon goal in energy systems.