In the quest to optimize renewable energy consumption and reduce carbon footprints, researchers have turned to an unlikely ally: ice storage air conditioning systems. A recent study published in the journal *Power Technology*, led by WANG Kui from the State Grid Electric Power Research Institute in Nanjing, China, introduces a novel multi-time scale optimization strategy that could revolutionize the way we manage distribution networks and integrate photovoltaic (PV) power generation.
Traditional demand response models often overlook the unique capabilities of ice storage air conditioning systems, which can act as virtual energy storage units. These systems store energy in the form of ice during off-peak hours when electricity is cheaper and release it during peak hours, thereby reducing the overall demand for electricity and enhancing grid stability. WANG Kui’s research aims to harness this potential to improve the utilization of renewable energy and explore the low-carbon operation potential of new distribution systems.
The study proposes a multi-objective optimization model that considers the interests of all stakeholders: power supply companies, photovoltaic producers, and air conditioning users. “Our goal was to create a model that not only minimizes the incentive cost for power supply companies and the electricity consumption cost for users but also maximizes the profit for photovoltaic manufacturers,” explains WANG Kui. The model uses the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to efficiently solve the multi-objective optimization problem and select the optimal solution based on multi-dimensional preference analysis.
One of the key innovations of this research is the daily rolling correction optimization model, which addresses the impact of prediction errors on the model results. This ensures that the optimization strategy remains effective even when the actual conditions deviate from the initial predictions. The study’s findings demonstrate that the proposed model can reduce costs by approximately 20% for both power supply companies and air conditioning users, while increasing profit margins by about 3% for photovoltaic producers.
The implications of this research are significant for the energy sector. By integrating ice storage air conditioning systems into the demand response framework, distribution networks can become more flexible and resilient, better equipped to handle the intermittent nature of renewable energy sources. This could pave the way for a more sustainable and low-carbon energy future.
As WANG Kui notes, “The multi-objective optimization and control method based on multiple time scales not only ensures the interests of all parties but also eliminates the impact of prediction errors on model results, providing important technical support for low-carbon operation of new distribution systems.” This research offers a promising avenue for enhancing the efficiency and sustainability of our energy infrastructure, ultimately benefiting both the environment and the economy.
In the rapidly evolving landscape of renewable energy and smart grids, innovations like this one are crucial for driving progress and achieving our climate goals. As the energy sector continues to adapt and innovate, the insights from this study could shape the future of distribution networks and demand response strategies, making them more efficient, reliable, and environmentally friendly.