Novel Distributed Load Management Algorithm (NDLMA) for Local Level Management in Smart Grid

Abstract

The world is adopting renewable energy sources to produce clean energy and save the environment. The conventional grid systems are facing a lot of problems due to this new adaption, for example, effective control of consumers, the recompense of supply instability, and fluctuation in power generation due to change in weather. The conventional electric grids have to ensure operability by adapting to energy demand. The smart grid can conquer these shortcomings. However, it requires data as precise as possible so that it can manage the demand of the grid and obtain good results. As a bigger quantity and accurate data reduce the privacy of consumers. Thus, it raises the conflict among privacy and Quality of Information (QoI). In this study, we are considering a model of a smart grid that has three levels: transmission, micro-grid, and local level. We propose a distributed algorithm for energy management at the local level which ensures the privacy of the user. For user data, it uses smart encryption. This algorithm categorizes smart home appliances into three categories: baseload, adaptable load, and shift-able load. Privacy is attained by taking different measures for privacy. However, privacy costs data volume overheads. This algorithm can normalize the peak demand and control the preference of home appliances, through distributing energy among appliances depending on their consumption and priority, without exceeding the predefined total energy consumption threshold.