Finding the optimal asynchronous decentralized power flow and its impact on cybersecurity in electrical and telecommunication networks

The power flow calculation is historically carried out by the network operator after the resolution of the electricity market to check that all physical constraints are respected. If this is not the case, the latter encourages market agents to move their operating points until the solution respects the network constraints. This method therefore requires several round trips between the market operator and the network operator to find a feasible operating point for a given future moment. The calculation of the Optimal Power Flow (OPF) makes it possible in a single step to find the optimal solution both from the economic point of view of the market agents, but also from the point of view of the electricity network by ensuring the feasibility of the solution. It introduces the complex voltage variables as well as complex powers in the lines, and ensures that these variables remain within imposed intervals. The OPF has so far been carried out in a centralized manner, i.e. by a single agent. Since the separation of the electricity market and network managers, it is no longer possible to consider that a single entity has all the information necessary to solve the OPF problem. Indeed, the data of the cost functions as well as the power limits of producers and consumers must be communicated if we want to solve the OPF in a centralized manner, which undermines the confidentiality of each agent's data. In addition, with the advent of distributed renewable energies and diverse energy communities, the number of actors that can interact through the electricity network is likely to increase significantly, which makes the centralized OPF calculation more complicated. The decentralization of the OPF makes it possible to overcome these problems by making it possible to scale up, to take into account a large-scale electricity network, as well as the confidentiality of each agent's data. On the other hand, it requires many iterations and communication between agents at each iteration. This makes the decentralized resolution very sensitive to communication hazards. An asynchronous version is then proposed for each decentralized OPF algorithm, which makes the resolution more robust to communication hazards. Thus, the asynchronous versions of the presented algorithms allow a real implementation less sensitive to the different communication hazards. After presenting the Optimal Power Flow problem in section 1, the centralized resolution will be explained in section 2 by highlighting its shortcomings for a large-scale implementation. The principle of decomposition of the problem for its decentralized resolution will be presented in section 3. We will then present two decentralized algorithms, one decomposed by nodes in section 4 and the other decomposed by boundaries in section 5. For each of these decentralized algorithms, the asynchronous versions will be introduced and compared to the synchronous versions to show the interest of asynchronous implementations in various conditions of the communication network and various cases with regard to network partitioning. Novelty : It addresses the communication vulnerability of decentralized OPF by proposing and analyzing asynchronous versions of these algorithms.This means that agents don't have to wait for each other to complete their calculations and communicate. They can operate more independently, making the system more resilient. The article compares the performance of synchronous and asynchronous versions, showing the advantages of the asynchronous approach in realistic communication scenarios. It also describes two different decentralized OPF algorithms, one decomposed by nodes and the other decomposed by boundaries, then applies the asynchronus methods to each. In essence, the article moves beyond the limitations of synchronous decentralized OPF by providing a more practical and reliable solution for real-world implementation, where communication issues are inevitable.