In the dynamic world of energy, where the lines between different energy sources are increasingly blurring, a groundbreaking study led by Biao Wu from the School of Mechatronic Engineering and Automation at Shanghai University is set to revolutionize how we think about integrated energy systems (IES). Wu’s research, published in the International Journal of Electrical Power & Energy Systems, delves into the intricate dance between IES and multi-energy markets, offering a fresh perspective on demand response strategies.
Imagine an energy system that can seamlessly integrate electricity, natural gas, and heat, optimizing their use in real-time. This is the promise of IES, and Wu’s work takes it a step further by exploring how these systems can act as price makers in multi-energy markets. “The key is to understand the interactions between IES and the markets for electricity and natural gas,” Wu explains. “By doing so, we can develop strategies that not only optimize energy use but also mitigate the market power of traditional energy providers.”
Wu’s approach involves a sophisticated bi-level model. At the upper level, the IES makes decisions based on electricity and natural gas prices, considering factors like electricity purchases from the electricity market (EM), natural gas purchases from the natural gas market (NGM), and the consumption of electricity and heat. The lower level, however, is where the real game begins. Here, Wu employs ordinal potential game (OPG) theory to model the competitive dynamics among power generators (PGs) in the EM and natural gas companies (NGCs) in the NGM. “By constructing an ordinal potential function, we can find the Nash equilibrium of these games,” Wu elaborates. “This allows us to predict how different players will behave in response to changes in the market.”
But the energy sector is notoriously unpredictable, especially when it comes to renewable sources like wind power. To tackle this uncertainty, Wu incorporates information gap decision theory (IGDT). This innovative approach helps in addressing the severe uncertainty of wind power, ensuring that the IES can still operate efficiently even when faced with unpredictable energy inputs.
The implications of Wu’s research are vast. For one, it could significantly reduce the market power of traditional energy providers, leveling the playing field for newer, more sustainable energy sources. This could lead to more competitive pricing and greater innovation in the energy sector. Moreover, by optimizing the use of multiple energy sources, IES could help reduce overall energy costs and improve the reliability of energy supply.
Wu’s work also paves the way for future developments in the field. The distributed algorithm he developed to handle information asymmetry could be a game-changer, enabling more efficient and effective management of integrated energy systems. As Wu puts it, “Our model and algorithm provide a robust framework for IES to navigate the complexities of multi-energy markets. This could be a significant step towards a more integrated and sustainable energy future.”
The study, published in the International Journal of Electrical Power & Energy Systems, marks a significant milestone in the field of energy systems integration. As the energy sector continues to evolve, Wu’s research offers a glimpse into a future where energy systems are not just more efficient but also more equitable and sustainable.
