Anomaly detection of transactive energy systems with competitive markets

An anomaly detection method is proposed for transactive energy systems with competitive markets. The detection method is also applicable to general distributed convex optimization problems. Transactive energy systems seek an optimal power allocation through hybrid economic control methods to facilitate the integration of various types of distributed energy resources to power distribution systems. In transactive energy systems, every participant is assumed to be a rational entity, in which the consumers have diminishing marginal utility and the suppliers have increasing marginal cost. With the proposed method, the convexity of the objective function is examined through the monotonicity of the gradient in distributed optimization problems, which corresponds with the assumption of diminishing marginal utility and increasing marginal cost in transactive energy systems. The proposed detection method does not require any data beyond those necessary to find the optimal solution. Simulation is carried out to show the efficacy of the proposed method to detect anomaly caused by cyberattacks.