Efficient Energy Management of IoT-Enabled Smart Homes Under Price-Based Demand Response Program in Smart Grid

Abstract

There will be a dearth of electrical energy in the prospective world due to exponential increase in electrical energy demand of rapidly growing world population. With the development of internet-of-things (IoT), more smart devices will be integrated into residential buildings in smart cities that actively participate in electricity market via demand response (DR) programs to efficiently manage energy in order to meet this increasing energy demand. Thus, with this incitement, an energy management strategy using price-based DR program is developed for IoT-enabled residential buildings. We propose a wind-driven bacterial foraging algorithm (WBFA), which is a hybrid of wind-driven optimization (WDO) and bacterial foraging optimization (BFO) algorithms. Subsequently, we devised a strategy based on our proposed WBFA to systematically manage the power usage of IoT-enabled residential building smart appliances by scheduling to alleviate peak-to-average ratio (PAR), minimize cost of electricity, and maximize user comfort (UC). This increases effective energy utilization, which in turn increases the sustainability of IoT-enabled residential buildings in smart cities. The WBFA-based strategy automatically responds to price-based DR programs to combat the major problem of the DR programs, which is the limitation of consumer’s knowledge to respond upon receiving DR signals. To endorse productiveness and effectiveness of the proposed WBFA-based strategy, substantial simulations are carried out. Furthermore, the proposed WBFA-based strategy is compared with benchmark strategies including binary particle swarm optimization (BPSO) algorithm, genetic algorithm (GA), genetic wind driven optimization (GWDO) algorithm, and genetic binary particle swarm optimization (GBPSO) algorithm in terms of energy consumption, cost of electricity, PAR, and UC. Simulation results show that the proposed WBFA-based strategy outperforms the benchmark strategies in terms of performance metrics.

Recent Advances in Internet of Things (IoT) Infrastructures for Building Energy Systems: A Review

“…Through the growth of IoT, further smart gadgets/appliances will be incorporated into residential buildings within smart buildings/cities, which proactively take part in electricity markets through demand response (DR) programmes to cost-effectively control energy so as to encounter this growing energy demand. For instance, Hafeez et al [ 42 ] developed an energy management strategy by means of price-based DR programme for IoT-allowed residential buildings. They proposed a wind-driven bacterial foraging algorithm (WBFA) that is a hybrid of wind-driven optimisation (WDO) and bacterial foraging optimisation (BFO) algorithms.…”

“…As previously mentioned, Hafeez et al [ 42 ] presented a demand response programme for residential buildings with IoT systems. Their programme managed the power usage of IoT enabled smart appliances to avoid peak demand times, minimising cost and maximising user comfort for the homeowner.…”

A Possible Smart Metering System Evolution for Rural and Remote Areas Employing Unmanned Aerial Vehicles and Internet of Things in Smart Grids

“…The system is connected to a database via Message Queuing Telemetry Transport (MQTT) to allow the users to remotely control it. a management system to control the increasing energy demand-response due to the growing spread of IoT-enabled smart homes is proposed in [ 63 ]. An improvement of the IoT-enabled smart home sustainability is guaranteed by following a strategy which controls and manages the power consumption during peak times, reduces the power cost, and increases users comfort.…”

Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges

“…A meta-heuristic integration of the enhanced DE and Harmony Search Algorithm has been proven to be effective regarding energy cost and PAR reduction in HEMS [103]. A Wind-Driven Bacterial Foraging algorithm, which combines a wind-driven algorithm and a bacterial foraging algorithm, has been implemented to systematically schedule IoT-based appliances in the smart home to eliminate PAR, decrease energy expenditure, and increase consumer comfort [104]. Some other studies have also applied hybrid bio-inspired approaches to solve different issues in EMS [105][106][107][108][109].…”

“…It takes both the characteristics of the smart grid and IoT. IoT is known as a novel communication paradigm that enables a large number of smart objects to communicate with each other and share services and information [7,49,104]. On the other hand, the smart grid can provide two-way connectivity among a power grid and EMS, monitor, and control power generator equipment [3,5].…”