Abstract
The integration of the smart grid with the cloud computing environment promises to develop an improved energy-management system for utility and consumers. New applications and services are being developed which generate huge requests to be processed in the cloud. As smart grids can dynamically be operated according to consumer requests (data), so, they can be called Data-Driven Smart Grids. Fog computing as an extension of cloud computing helps to mitigate the load on cloud data centers. This paper presents a cloud–fog-based system model to reduce Response Time (RT) and Processing Time (PT). The load of requests from end devices is processed in fog data centers. The selection of potential data centers and efficient allocation of requests on Virtual Machines (VMs) optimize the RT and PT. A New Service Broker Policy (NSBP) is proposed for the selection of a potential data center. The load-balancing algorithm, a hybrid of Particle Swarm Optimization and Simulated Annealing (PSO-SA), is proposed for the efficient allocation of requests on VMs in the potential data center. In the proposed system model, Micro-Grids (MGs) are placed near the fogs for uninterrupted and cheap power supply to clusters of residential buildings. The simulation results show the supremacy of NSBP and PSO-SA over their counterparts.
Highlights
With the increasing population, the introduction of new electrical and electronic gadgets in daily lives has increased the demand for electricity
MGs are placed with each fog for uninterrupted and cheap power supply to the clusters
A MG has maintenance or recurring cost which depends on the size, types of sources and number of demand requests from the clusters
Summary
The introduction of new electrical and electronic gadgets in daily lives has increased the demand for electricity. The consumers are educated to optimize their energy demands according to electricity tariff. Demand response is a program in which the consumer changes the behavior of power consumption according to the utility tariff [4]. These programs play an important role in maintaining the sustainability of the SG. The energy supply and consumption is optimized with IoT-based devices and cloud-based energy management. Autonomous and intelligent energy management, with distributed energy sources for the demand side to mitigate the load on the supply side, is the requirement of modern SG. Cloud computing suffers from delay, load request congestion, huge data computation and communication cost. Machines (VMs) cost, Data Transfer (DT) cost and recurring cost of MG comprise the system cost, which is added in the consumer bill
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