Adaptive Dynamic Programming and Blockchain Technique-Based Smart Home Energy Management

This paper focuses on developing an optimal energy storage strategy for smart home energy management using adaptive dynamic programming (ADP) and blockchain technique. The ADP-based self-learning algorithm is developed to generate an iterative control sequence for the battery as the electricity storage equipment. The algorithm takes real-time electricity prices, load demand, and battery power efficiency into account to establish an optimal performance index function. The goal is to minimize total electricity costs while maximizing the battery's lifespan. Additionally, the blockchain technique is employed to ensure transparent, tamper-proof and secure transaction data. A numerical simulation is provided to demonstrate the effectiveness of the proposed algorithm.