Privacy-preserving distributed economic dispatch protocol for Smart Grid

The economic dispatch (ED) problem is a large-scale optimization problem in electricity power grids. Its goal is to find a power output combination of all generator nodes that meet the demand of the customers at minimum operating cost. In recent years, distributed protocols have been proposed to replace the traditional centralized ED calculation for modern smart grid infrastructures with the most realistic being the one proposed by Binetti et al. (2014). However, we show that this protocol leaks private information of the generator nodes. We then propose a privacy-preserving distributed protocol that solves the ED problem. We analyze the security of our protocol and give experimental results from a prototype implementation to show the feasibility of the solution

On security and privacy of consensus-based protocols in blockchain and smart grid

In recent times, distributed consensus protocols have received widespread attention in the area of blockchain and smart grid. Consensus algorithms aim to solve an agreement problem among a set of nodes in a distributed environment. Participants in a blockchain use consensus algorithms to agree on data blocks containing an ordered set of transactions. Similarly, agents in the smart grid employ consensus to agree on specific values (e.g., energy output, market-clearing price, control parameters) in distributed energy management protocols. This thesis focuses on the security and privacy aspects of a few popular consensus-based protocols in blockchain and smart grid. In the blockchain area, we analyze the consensus protocol of one of the most popular payment systems: Ripple. We show how the parameters chosen by the Ripple designers do not prevent the occurrence of forks in the system. Furthermore, we provide the conditions to prevent any fork in the Ripple network. In the smart grid area, we discuss the privacy issues in the Economic Dispatch (ED) optimization problem and some of its recent solutions using distributed consensus-based approaches. We analyze two state of the art consensus-based ED protocols from Yang et al. (2013) and Binetti et al. (2014). We show how these protocols leak private information about the participants. We propose privacy-preserving versions of these consensus-based ED protocols. In some cases, we also improve upon the communication cost