AN OPTIMIZATION FRAMEWORK FOR CLOUD-BASED DATA MANAGEMENT MODEL IN SMART GRID

Abstract

Smart Grid (SG) is an intelligent electricity network that incorporates advanced information, control and communication technologies to increase the reliability of existing power grid. With advanced communication and information technologies, smart grid deploys complex information management model. This paper presents a cloud service based information management model which opens the issues and benefits from the perspective of both smart grid domain and cloud domain of system model. The overall cost of data management includes storage, computation, upload, download and communication costs which need to be optimized. This paper provides an optimization framework for reducing the overall cost for data management and integration in smart grid model. In this paper, the optimization model focuses on optimizing the size of data items to be stored in the clouds under concern. The types of data items to be stored in the clouds are considered as customer behavior data and Phasor Measurement Units (PMU) data in the smart grid environment. The management model usually comprises of four domains viz., smart grid domain, cloud domain, broker domain and network domain. The present work focuses mainly on smart grid and cloud domain and optimization of cost related to these domains for simplicity of model considered. The proposed model is optimized using various evolutionary optimization techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). The results of various techniques when implemented for proposed model are compared in terms of performance measures and a most suitable technique is identified for cloud based data management.