Energy Efficient Smart Buildings Using Coordination Among Appliances Generating Large Data

Muhammad Hassan Rahim,Nadeem Javaid,Musaed Alhussein,Khursheed Aurangzeb,Zahoor Ali Khan,Adia Khalid

doi:10.1109/access.2018.2805849

Abstract

Internet of Things based smart grids (SGs) represent a vision of future power systems which helps to provide electricity in a smart and user friendly way. Demand side management is one of the most important component of a SG which allows energy consumers to change their electricity consumption patterns to reduce the electricity consumption cost. In this paper, we propose a home energy management system which helps to achieve our desired objectives: reduced electricity consumption cost, peak to average ratio and maximize user comfort. For this purpose, we have proposed a scheduling technique which is a hybrid of already existing optimization techniques: bacteria foraging algorithm and harmony search algorithm and is named as hybrid bacterial harmony (HBH) algorithm. Being producer of electricity units to the consumers, a utility establishes an incentive based pricing tariff; we, on top of it have employed seasonal time of use tariff which allows consumers to take decisions regarding their consumption patterns. Moreover, we introduce the concept of coordination among smart appliances using dynamic programming (DP) approach. The coordination among appliances is achieved by the help of the large data generated from the appliances of multiple homes with the joint work of heuristic techniques and DP. The resultant coordination not only reduces the electricity cost but also increases the user comfort. At last, we evaluate the performance of our proposed energy management system using our proposed optimization technique HBH. To comparatively evaluate the performance of our proposed technique, we compare it with already existing techniques. Simulation results validate that the proposed technique effectively accomplish the desired objectives while considering the consumer comfort.

Highlights

Numerous challenges are being faced by the electric power industry
To satisfy peak load demands, utilities turns on generators running on fossil fuels and natural gases which cause environmental issues as these generators are a great source of emitting harmful gasses
SIMULATIONS AND RESULTS simulation results are evaluated to analyze the performance of the proposed Home energy management (HEM) model

Summary

INTRODUCTION

Numerous challenges are being faced by the electric power industry. The reliability of existing power grid is one of the challenges of power system which is affected by the increase in power demand, a limited amount of natural resources, and aging infrastructure. It persuades consumers to modify their electricity usage pattern by shifting their heavy load from on-peak to off-peak hours in response to varying energy price This facilitates in reducing the aggregated electricity consumption cost and PAR by efficiently managing power consumption pattern from which both consumers and utility get benefits. Minimization of green house gas emissions, efficient load management to reduce PAR and consumer comfort are some of the major problems in the residential sector of SGs. Electricity consumption cost reduction, optimal management of gross load, making the grid more sustainable, and PAR reduction are some of the common objectives of SG. The major focus of our proposed algorithm is to manage the load in order to minimize the electricity cost and PAR. Vector in random direction. xiL Lower bound of decision variable. xiU Upper bound of decision variable. xinew Decision variable

STATE OF THE ART LITERATURE REVIEW

PROPOSED SYSTEM MODEL

FEASIBLE REGION

SIMULATIONS AND RESULTS