In the bustling labs of Shanghai University of Electric Power, researchers led by Huiqun Yu are revolutionizing the way we think about microgrids and electric vehicles (EVs). Their groundbreaking work, recently published in ‘Zhongguo dianli’ (China Electric Power), introduces a hierarchical scheduling optimization strategy that could reshape the energy landscape, making it more efficient, reliable, and user-friendly.
Imagine a residential microgrid, a small-scale power grid that can operate independently or in conjunction with the main grid. Now, picture this microgrid teeming with electric vehicles, each with its own charging needs and user preferences. Traditionally, this scenario would present a significant challenge for grid stability and cost-effectiveness. However, Yu and her team have devised a strategy that not only smooths out the peaks in power demand but also minimizes the overall cost of the microgrid.
The strategy is divided into two layers: the load layer and the source storage layer. The load layer leverages the energy storage capabilities of EVs to balance the microgrid’s power demand. “We utilize the energy storage characteristics of electric vehicles to smooth the peak of the original load in the microgrid,” Yu explains. This means that during peak hours, when energy demand is high, the microgrid can draw power from the EVs, reducing the strain on the grid and lowering costs.
The source storage layer, on the other hand, focuses on integrating renewable energy sources. Any excess renewable energy is absorbed by the dispatchable EVs, ensuring that the microgrid operates at peak efficiency. To solve the complex optimization problem, the team employed an improved ant lion algorithm, a nature-inspired optimization technique that mimics the hunting behavior of antlions.
The results are impressive. The strategy not only improves the economics and reliability of the microgrid but also enhances the satisfaction of EV users. “The satisfaction degree of electric vehicle user is improved,” Yu notes, highlighting the strategy’s user-centric approach.
So, what does this mean for the energy sector? For starters, it paves the way for more efficient and reliable microgrids, which are crucial for integrating renewable energy sources and EVs into the power grid. It also sets a new standard for user satisfaction, ensuring that EV owners are happy with their charging experience while contributing to grid stability.
As we move towards a future where EVs and renewable energy sources play a central role in our power systems, strategies like Yu’s will be instrumental in shaping a more sustainable and efficient energy landscape. This research is a significant step forward, demonstrating the potential of hierarchical optimization scheduling in microgrids and setting the stage for future developments in the field.
