In the quest for a greener, more efficient energy future, researchers are constantly seeking innovative ways to integrate and optimize energy systems. A recent study published in IEEE Access, led by Kaiyan Wang from the School of Electrical Engineering at Xi’an University of Technology in China, offers a compelling solution. Wang and his team have developed a novel method for optimizing integrated energy systems (IES) that could significantly reduce carbon emissions and operational costs.
The study introduces a dynamic approach to scheduling IES, incorporating a reward and punishment mechanism based on electricity and thermal carbon emission factors. This method not only promotes the efficient use of thermal energy but also encourages low-carbon behaviors among users. “By considering energy coupling and thermal energy cascade utilization, we can achieve a high-grade use of thermal energy in combination with thermal load demand,” Wang explains. This means that waste heat, often a byproduct of industrial processes, can be repurposed to meet thermal energy needs, reducing the overall carbon footprint.
The researchers have also developed an improved model for dynamic electricity and thermal carbon emission factors. This model characterizes the carbon emission intensity and renewable energy consumption capacity, providing a more accurate picture of the environmental impact of energy use. “Our integrated demand response (IDR) mechanism, driven by electricity, thermal reward, and carbon price, guides users toward low-carbon behaviors and renewable energy consumption,” Wang adds. This mechanism is a key component of the two-stage optimal scheduling model proposed in the study.
The first stage involves pre-scheduling, where an initial plan is developed and load distribution is adjusted through the IDR mechanism. The second stage, re-scheduling, updates the load curve to obtain the final scheduling plan. Through simulation, the researchers found that their method reduces carbon emissions by 7.7%, improves the renewable energy consumption rate by 4%, and reduces the comprehensive operating cost of the system by 4.3%.
The implications of this research are far-reaching. For the energy sector, this could mean more efficient use of resources, lower operational costs, and a significant reduction in carbon emissions. As the world continues to grapple with climate change, such innovations are crucial. This research could shape future developments in the field by providing a framework for optimizing energy systems that balances environmental and economic considerations. As the energy sector continues to evolve, the need for such integrated and dynamic solutions will only grow.
