RES Digital Twin for Smart Energy Management Flexibility Research

In recent years, guidelines in developing energy systems have proposed massive participation of renewable energy sources. This inevitably leads to an increase in the flexibility of networks in terms of the ability to react to load changes quickly, but it also has disadvantages due to the random nature of energy production from RES. One of the main guidelines in the construction of future energy installations is to ensure flexibility in case of a lack or surplus of energy in the network. This flexibility could be ensured by synchronizing the load operation, storage capacity utilization, and generation facilities flexible control. It could be granted by developing new algorithms for adequate reaction based on energy availability and demand response techniques and IoT technologies for metering and control. Testing of such algorithms involves the construction of pilot installations or laboratory models. This approach is expensive, time-consuming, and allows us to test a limited range of algorithms. Another approach is to use mathematical models or digital twins. Well-designed digital twin helps consolidate real-object data and make it available for use by machine learning and artificial intelligence algorithms to support decision-making in complex real-world situations, including energy systems. This article considers the application of power system control based on a programmable logic controller and virtual environment for simulating the behavior of loads, batteries, and photovoltaic installations. It proposes an approach to create a digital twin of energy system designed to easily and safely implement flexible algorithms for managing energy production and demand response.