Intelligent and Self-Sufficient Control for Time Controllable Consumers in Low-Voltage Grids
Abstract
The increasing number of decentralized power generation plants, such as wind turbines or photovoltaics (PV), causes more and more fluctuating feed-in, especially in the distribution grid. To balance power generation with electrical loads, a promising approach is the temporal shift of controllable consumers depending on the grid state, meaning energy deficit, or surplus. The so-called demand-side management is one possible alternative to grid reinforcements, allowing minimization of peak loads and thus increasing grid efficiency. The German Energy Industry Act (§14a EnWG) enables distribution system operators (DSOs) to control controllable consumers at reduced grid charges. However, the needed communication is subjected to high standards for data security, that is, the data volume should be kept small to reduce effort and costs. In addition, especially in rural areas with high PV feed-in, the grid state changes within a few kilometers. A general schedule for a larger grid section would not meet the individual situation. To overcome these issues, a highly automated and self-sufficient control for controllable consumers was developed and investigated. The innovative algorithm processes the locally measured voltages and loads and estimates the grid state. A schedule for blocking times for different clusters of controllable consumers is calculated. No communication is necessary for this basic principle, but DSOs still have the possibility to send prioritized switching commands. This local control system works in compliance with already existing regulations and within contractual frameworks. It is tested in a real laboratory of about 100 private households in rural and urban areas. The results show a high potential for this decentralized load management to serve the grid.
