Capacity optimization for power system decarbonization – a comprehensive multi-objective analysis

As global efforts to reduce carbon emissions intensify, decarbonizing power systems has become a critical objective. Power systems that rely heavily on renewable energy sources, such as wind and solar power, face challenges due to the inherent intermittency of these resources. To address this, the integration of energy storage systems (ESS) has become increasingly important for stabilizing the grid. In this context, a novel power system dispatch model is developed, which incorporates thermal power, wind power, PV generation, and ESS, with a focus on optimizing capacity configurations for cost reduction, carbon emission control, and stability enhancement.

The team, developed the model using Monte Carlo simulations to account for the uncertainties in renewable energy generation and user demand. By applying the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the team analyzed different capacity configurations for the power system. The findings highlight how increasing ESS capacity can improve renewable energy utilization while mitigating fluctuations in power generation. However, they also suggest that there are limits to the share of renewable energy that can be integrated without impacting system stability.

“We found that optimizing ESS capacity can lead to a significant reduction in system costs and carbon emissions, while increasing renewable energy utilization,” said Yan Tang, the corresponding author of the paper and a professor at the School of Management at Tianjin University of Technology. “Our results also show that the optimal configurations for ESS capacity vary depending on the renewable energy share, indicating the importance of balancing these elements for a stable and low-carbon energy system.”

The study’s results emphasize the trade-offs between cost, carbon emissions, and power fluctuations, providing key insights into the challenges of balancing renewable energy integration with grid stability. The authors recommend that policymakers focus on deploying ESS capacities tailored to the renewable energy integration needs of each region.

The research team expects the findings to support future developments in power system decarbonization and encourage the integration of ESS in achieving carbon neutrality targets. “The model we developed is a robust tool for guiding energy policy decisions, and we plan to extend it to more detailed policy analyses, considering interactions with other environmental models,” Tang said.

Contributors to the study include Zhenqing Sun, Xinzhi Wang, and other Master's degree candidate from Carbon Neutral Research Institute of Tianjin University of Science and Technology. The project was supported by the National Social Science Foundation of China (Grant No. 22BGL270).

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