A Home Energy Management System with Peak Demand Reduction Using Ant Colony Optimization and Time of Use Pricing Scheme

Ramalingam, S.; Shanmugam, Prabhakar Karthikeyan

doi:10.1007/978-981-16-2712-5_43

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…DAP hourly price for five climatic conditions was taken from the Indian Energy Exchange, and the same is represented in Table 4 [37]. Recent research [50][51][52][53][54] has proved that both TOU and DAP pricing schemes reduce the energy consumption cost and the peak-average ratio. Hence, this paper considered the DAP scheme as the preferred option to use.…”

Section: Simulation Resultsmentioning

confidence: 99%

Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm

Ramalingam

Shanmugam

2022

Energies

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A remodeled sperm swarm optimization (RMSSO) algorithm for a home energy management (HEM) system is proposed, and its real-time efficacy was evaluated using a hardware experimental model. This home environment comprised sixteen residential loads, a smart meter and a Raspberry Pi controller to optimize the energy consumption cost (ECC) in response to the Indian day-ahead pricing (DAP) scheme. A wired/wireless communication network was considered to communicate with the smart meter and controller. To address this optimization problem, the sperm swarm optimization (SSO) algorithm’s constriction coefficient was remodeled to improve its global searching capability and proposed as RMSSO. For the first time, salp swarm optimization (SSA), SSO, and RMSSO algorithms were employed to schedule home appliances in the Indian scenario. To validate the proposed technique’s outcome, the results were compared to those of the conventional SSO and SSA algorithms. This problem was solved using the Python/GUROBI optimizer tool. As a consequence, consumers can use this control strategy in real-time to reduce energy consumption costs.

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Section: Simulation Resultsmentioning

confidence: 99%

Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm

Ramalingam

Shanmugam

2022

Energies

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“…The authors discuss the challenges and opportunities associated with V2H technology and propose a control strategy based on the P&O algorithm to optimize energy management in residential homes. The study shows that the proposed strategy can effectively manage energy consumption and reduce energy costs [2]. The authors consider the impact of renewable energy sources and propose a twostage control strategy that includes battery charging and discharging management.…”

Section: Introductionmentioning

confidence: 99%

Integrating Vehicle-to-Home Unit with Smart Home Energy Management Systems: A Unified Energy Management Framework

2023

IJSREM

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The increasing acceptance of electric vehicles (EVs) and renewable energy sources (RES) has led to the need for a unified energy management framework that can integrate multiple energy systems, including Vehicle-to-Home (V2H) units, Smart Home Energy Management Systems (SHEMS), Solar PV systems, and the grid. The framework uses a centralized control strategy that makes decisions based on real-time integration of a Vehicle-to-Home (V2H) unit with a Smart Home Energy Management System (SHEMS), which can provide a solution to these challenges by enabling bidirectional power flow between the EV battery and the home. We proposed a unified energy management framework that integrates a Ve- hicle-to-Home (V2H) unit with a SHEMS using a Perturb and Observe (P-&-O) algorithm. The proposed framework allows for the optimization of energy usage in the home by utilizing the battery of an EV, which can be charged during off-peak hours and discharged during peak hours. The P&O algorithm is a well-known algorithm used in photovoltaic systems to track the Maximum Power Point (MPP) of a solar panel. The algorithm is also applicable to EV charging and discharging systems. The algorithm uses a per- turbation signal to change the charging rate of the EV battery and observes the resulting change in the bat- tery voltage. The simulation results can also provide benefits to EV owners, such as reduced electricity costs and increased flexibility in managing their EV charging, helping to achieve efficient and sustainable energy management in residential areas. Keywords: Solar panel, Electric Vehicle Battery, Vehicle-to-Home (V2H), Smart Home Energy Manage- ment Systems (SHEMS), Demand side management.

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“…In this configuration, grid electricity was the primary source, with battery storage serving as a backup during moments of peak demand. Using ant colony optimization, the authors of [ 12 ] developed and presented an improved HEMS that reduced peak demand and improved user comfort. A comparison of the achieved results to non-scheduled alternatives demonstrated the expanded potential of HEMS to reduce PAR by scheduling household appliances depending on the terms of use pricing.…”

Section: Introductionmentioning

confidence: 99%

Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System

Almughram

Sami

Zafar

2022

Sensors

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Integration of vehicle-to-home (V2H) centralized photovoltaic (HCPV) systems is a requested and potentially fruitful research topic for both industry and academia. Renewable energy sources, such as wind turbines and solar photovoltaic panels, alleviate energy deficits. Furthermore, energy storage technologies, such as batteries, thermal, and electric vehicles, are indispensable. Consequently, in this article, we examine the impact of solar photovoltaic (SPV), microgrid (MG) storage, and an electric vehicle (EV) on maximum sun radiation hours. As a result, an HCPV scheduling algorithm is developed and applied to maximize energy sustainability in a smart home (SH). The suggested algorithm can manage energy demand between the MG and SPV systems, as well as the EV as a mobile storage system. The model is based on several limitations to meet households’ electrical needs during sunny and cloudy weather. A multi-agent system (MAS) is undertaken to ensure proper system operation and meet the power requirements of various devices. An experimental database for weather and appliances is deployed to evaluate and control energy consumption and production cost parameters. The obtained results illustrate the benefits of V2H technology as a prospective unit storage solution.

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A Home Energy Management System with Peak Demand Reduction Using Ant Colony Optimization and Time of Use Pricing Scheme

Cited by 7 publications

References 12 publications

Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm

Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm

Integrating Vehicle-to-Home Unit with Smart Home Energy Management Systems: A Unified Energy Management Framework

Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System

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