Industrial parks play a crucial role in China's pursuit of carbon peak and carbon neutrality goals. However, their current energy systems face issues such as high energy consumption and large carbon emissions. A recent study published in Engineering focuses on optimizing the energy systems of industrial parks with hybrid energy storage to enhance economic performance, reliability, and carbon reduction.
The study points out that while renewable energy is a key to low-carbon operations in industrial parks, its intermittency and the unpredictable load demands pose challenges. Existing energy storage technologies have limitations, and most optimization research on hybrid energy storage has relied on rule-based passive-control principles.
To address these gaps, the research team developed a detailed model for the industrial park energy system with hybrid energy storage (IPES-HES), considering the operational characteristics of various energy devices. They proposed an active operation strategy that uses the hourly power output of energy storage for the next day as decision variables. An optimization configuration model was formulated with the goals of cost reduction and carbon emission lowering, solved using the non-dominated sorting genetic algorithm II (NSGA-II). A day-ahead nonlinear optimization scheduling method was also developed based on configuration optimization.
The findings are significant. On a typical summer day, the system energy bill and peak power of the IPES-HES under the optimization-based operational strategy were reduced by 181.4 USD (5.5%) and 1600.3 kW (43.7%) respectively, compared to an operation strategy based on proportional electricity storage.
The researchers plan to further investigate integrating load flexibility into the IPES-HES to improve renewable energy utilization. This study provides important theoretical support and practical guidance for optimizing the energy systems of industrial parks and is expected to have broad applications in the field.
The paper "Day-Ahead Nonlinear Optimization Scheduling for Industrial Park Energy Systems with Hybrid Energy Storage," authored by Jiacheng Guo, Yimo Luo, Bin Zou, Jinqing Peng. Full text of the open access paper: https://doi.org/10.1016/j.eng.2024.10.006
