In the rapidly evolving landscape of energy distribution, the integration of distributed photovoltaic (PV) systems has presented both opportunities and challenges. As the penetration of these systems increases, so does the complexity of managing active distribution networks (ADNs). Enter Jiachuan Shi, a researcher from the Shandong Key Laboratory of Smart Buildings and Energy Efficiency at Shandong Jianzhu University, who has developed a novel approach to optimize the operation of ADNs, addressing the uncertainties introduced by high levels of distributed PV.
Shi’s research, published in Energies, focuses on creating a two-layer optimization model that simplifies the solution of ADN optimal operation problems. The model is designed to identify “key” nodes within the network using an improved K-means clustering algorithm and two critical indexes: integrated voltage sensitivity and reactive power-balance degree. This approach allows for a more nuanced understanding of the network’s dynamics, enabling better control and management.
One of the standout features of Shi’s model is its consideration of PV users’ interests. By maximizing PV active power output, the model ensures that the benefits of distributed PV systems are fully realized. “Our goal is to create a control strategy that not only optimizes the network’s operation but also takes into account the needs and benefits of the users,” Shi explains. This user-centric approach is a significant step forward in the integration of distributed energy resources.
The model operates on two time scales. The upper layer, which operates on a longer time scale, includes on-load tap-changer transformers (OLTC) and capacitor banks (CB). The lower layer, operating on a shorter time scale, focuses on PV inverters and distributed energy storages (ESs). This dual-layer approach allows for more precise and efficient control of the network.
One of the key innovations in Shi’s research is the linearization of the OLTC model. By using integer binary expansion and the big M method, Shi has developed a linear model for OLTC tap change frequency constraints. This linearization is crucial for transforming the complex, non-linear models into a mixed-integer second-order cone convex optimization (MISOCP) model, which can be solved using solvers like CPLEX.
The effectiveness of Shi’s model was verified using the IEEE33 node system. The results were impressive, with a 70% reduction in network losses and all node voltages maintained within qualified limits. This demonstrates the model’s potential for both economic and stable operation of distribution networks.
The implications of Shi’s research are far-reaching. As ADNs continue to evolve, the integration of more complex non-linear devices will become inevitable. Shi’s model provides a framework for addressing these challenges, ensuring that the benefits of distributed energy resources are fully realized while maintaining the stability and efficiency of the network.
“This research is a significant step forward in the optimization of active distribution networks,” Shi concludes. “By addressing the complexities introduced by high levels of distributed PV, we can create more efficient, stable, and user-friendly energy systems.”
As the energy sector continues to evolve, the need for innovative solutions like Shi’s will only grow. The integration of distributed energy resources, the increasing complexity of ADNs, and the need for user-centric solutions all point to a future where research like Shi’s will play a crucial role. The work published in Energies, which translates to “Energies” in English, is a testament to the ongoing efforts to shape a more sustainable and efficient energy future.
