Swarm-intelligence-based coordinated control of electric heatings for voltage stabilization with zero communication burden

The movement towards electrification is entailing deep changes in power systems. On the demand side, the adoption of electric heating (EH) has grown rapidly in recent years. To eliminate the voltage fluctuations caused by the random switching-on/-off behaviors of EHs in some application scenes with special-power-line in low voltage distribution networks (LVDNs), a swarm-intelligence-based coordinated control approach of EHs for voltage stabilization with zero communication burden while guaranteeing the users’ thermal comforts is researched. A novel bird-perch-on-branch (BPB) -based swarm intelligence theory is proposed, which reveals the mapping relation between local observations and global states. On this theoretical basis, a multi-agent reinforcement learning (MARL) framework is developed for the coordinated dispatch of EHs, where the deep-Q-network (DQN) algorithm is adopted to learn and generate the optimal control policy for each EH. The implementation of the proposed MADQN-BPB approach is described based on the principle of centralized-training and decentralized-execution. Comparative control performances of MADQN-BPB with a commercially available approach, and the global optimal solution are evaluated. Simulation results verify the capability of MADQN-BPB in voltage stabilization with zero communication burden. Its control performance is close to that of the global optimal solution, and is scalable to the variations of environment.