Privacy is of great importance for microgrids and has gained much attention recently. By eavesdropping on the communications among the devices, attackers may infer sensitive system operation information and user behavior due the intimate interplay between communication and control in mircogrids. In this paper, in order to facilitate simulational evaluations of privacy preservation techniques for microgrids, we develop a versatile cyber-physical co-simulator which integrates both networked communication and power system control subsystems as a whole. The co-simulator is built upon MATLAB/Simulink and OMNeT++ along with a module that coordinates the two tools in real-time simulations. Based on the co-simulator, we evaluates three privacy-preserving algorithms proposed in the literature, and find that SFPA performs better than PEMA and REP-CoDEMS in aspect of protecting the privacy of controllable inputs, but REP-CoDEMS and PEMA has a better performance considering both controllable inputs and uncontrollable inputs.

Recently, collaborative distributed energy management systems (CoDEMS) have emerged as an effective solution to manage distributed energy resources in microgrid. In CoDEMS, devices collaborate in a distributive manner over communication networks to meet electrical loads and supply balance at minimum cost. However, mutual information exchanges among the devices in CoDEMS may leak important information about the devices states. In this paper, we investigate the challenging problem of how to achieve optimality while preserving the privacy of CoDEMS at relatively low cost. Unlike many previous works that preserve the privacy by using additive noises, we propose a novel random-weight privacy-preserving algorithm with error compensation, termed as REP-CoDEMS, for CoDEMS. In the proposal, each distributed device generates two random weights each time and it communicates with its neighbor conveying values based on the weights, incremental cost estimation and power imbalance estimation information along with a novel error compensation term to eliminate the error induced by the random weights. We theoretically prove that the proposed REP-CoDEMS algorithm converges and preserves the privacy of all devices. We also derive analytical expressions of the maximum privacy disclosure probability for initial and final states of the CoDEMS. In addition, we conduct extensive simulations and the results demonstrate the effectiveness of the proposed algorithm.

The microgrid is envisioned to be the building block of the future smart grid, for its abilities to host distributed energy resources, to improve grid reliability, and to enhance system resiliency. One of the most studied research topics of the microgrid is the distributed microgrid energy management system. However, the algorithm prototyping and hardware validation still remain great challenges at the current stage. This paper proposes a highly scalable, customizable, and low-cost DC microgrid testbed framework that enables fast distributed MG-EMS prototyping and provides proof-of-concept validation. Moreover, an application example is presented to demonstrate the functionality and validity of the proposed microgrid testbed.