Optimal Energy Scheduling Based on Jaya Algorithm for Integration of Vehicle-to-Home and Energy Storage System with Photovoltaic Generation in Smart Home

Wang, Min; Abdalla, Modawy Adam Ali

doi:10.3390/s22041306

Cited by 26 publications

(10 citation statements)

References 35 publications

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“…They can make choices to reduce their electricity cost according to the optimal scheduling algorithms. Smart meters provide incentives, like current electricity prices, to help prosumers decide the change or discharge of their electric vehicles from time to time [ 77 ]. Electric vehicles are hence switching between home-to-vehicle mode (charging) and vehicle-to-home mode (discharging), to interact with the smart grid.…”

Section: How Smart Meters Support Smart Gridsmentioning

confidence: 99%

Control and Optimisation of Power Grids Using Smart Meter Data: A Review

Chen

Amani

et al. 2023

Sensors

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This paper provides a comprehensive review of the applications of smart meters in the control and optimisation of power grids to support a smooth energy transition towards the renewable energy future. The smart grids become more complicated due to the presence of small-scale low inertia generators and the implementation of electric vehicles (EVs), which are mainly based on intermittent and variable renewable energy resources. Optimal and reliable operation of this environment using conventional model-based approaches is very difficult. Advancements in measurement and communication technologies have brought the opportunity of collecting temporal or real-time data from prosumers through Advanced Metering Infrastructure (AMI). Smart metering brings the potential of applying data-driven algorithms for different power system operations and planning services, such as infrastructure sizing and upgrade and generation forecasting. It can also be used for demand-side management, especially in the presence of new technologies such as EVs, 5G/6G networks and cloud computing. These algorithms face privacy-preserving and cybersecurity challenges that need to be well addressed. This article surveys the state-of-the-art of each of these topics, reviewing applications, challenges and opportunities of using smart meters to address them. It also stipulates the challenges that smart grids present to smart meters and the benefits that smart meters can bring to smart grids. Furthermore, the paper is concluded with some expected future directions and potential research questions for smart meters, smart grids and their interplay.

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Section: How Smart Meters Support Smart Gridsmentioning

confidence: 99%

Control and Optimisation of Power Grids Using Smart Meter Data: A Review

Chen

Amani

et al. 2023

Sensors

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“…Therefore, the distributed energy resources, such as rooftop photovoltaic and wind power, are used to reduce energy consumption. However, the variable renewables energy intermittent nature can cause many problems, such as over-generation and voltage fluctuations, which affect the system reliability [8]. ESS is an important technology that provides a high level of flexibility and energy management capability [9,10].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Energy Usage and Smoothing Load Profile via a Home Energy Management Strategy with Vehicle-to-Home and Energy Storage System

Abdalla,

Min,

Amran

et al. 2023

Sustainability

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This study investigates an energy utilization optimization strategy in a smart home for charging electric vehicles (EVs) with/without a vehicle-to-home (V2H) and/or household energy storage system (HESS) to improve household energy utilization, smooth the load profile, and reduce electricity bills. The proposed strategy detects EV arrival and departure time, establishes the priority order between EV and HESS during charge and discharge, and ensures that the EV battery state of energy at the departure time is sufficient for its travel distance. It also ensures that the EV and HESS are charged when electricity prices are low and discharged in peak hours to reduce net electricity expenditure. The proposed strategy operates in different modes to control the energy amount flowing from the grid to EV and/or HESS and the energy amount drawn from the HESS and/or EV to feed the demand to maintain the load curve level within the average limits of the daily load curve. Four different scenarios are presented to investigate the role of HESS and EV technology in reducing electricity bills and smoothing the load curve in the smart house. The results demonstrate that the proposed strategy effectively reduces electricity costs by 12%, 15%, 14%, and 17% in scenarios A, B, C, and D, respectively, and smooths the load profile. Transferring valley electricity by V2H can reduce the electricity costs better than HESS, whereas HESS is better than EV at flattening the load curve. Transferring valley electricity through both V2H and HESS gives better results in reducing electricity costs and smoothing the load curve than transferring valley electricity by HESS or V2H alone.

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“…On the other hand, 40% of the residential energy consumption in Australia comes from space conditioning [ 3 ]. As renewable generation, smart-grid technologies and smart meters are being added into the network, there is a renewed interest in integrating demand-side management strategies into the network with decreasing technological barriers [ 4 , 5 ]. The advancement of Internet of Things (IoT) technologies has allowed the integration of intelligent algorithms for demand management applications in smart homes.…”

Section: Introductionmentioning

confidence: 99%

Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home

Philip

Islam

Phillips³

et al. 2022

Sensors

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This paper addresses the optimal pre-cooling problem for air conditioners (AC) used in Internet of Things (IoT)-enabled smart homes while ensuring that user-defined thermal comfort can be achieved. The proposed strategy utilises renewable energy generation periods and moves some of the air conditioning loads to these periods to reduce the electricity demand. In particular, we propose a multi-stage approach which maximises the utilisation of renewable energy at the first stage to satisfy air conditioning loads, and then schedules residual energy consumption of these loads to low price periods at the second stage. The proposed approach is investigated for the temperature and renewable generation data of NSW, Australia, over the period 2012−2013. It is shown that the approach developed can significantly reduce the energy consumption and cost associated with AC operation for nearly all days in summer when cooling is required. Specifically, the proposed approach was found to achieve a 24% cost saving in comparison to the no pre-cooling case for the highest average temperature day in January, 2013. The analysis also demonstrated that the proposed scheme performed better when the thermal insulation levels in the smart home are higher. However, the optimal pre-cooling scheme can still achieve reduced energy costs under lower thermal insulation conditions compared to the no pre-cooling case.

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Optimal Energy Scheduling Based on Jaya Algorithm for Integration of Vehicle-to-Home and Energy Storage System with Photovoltaic Generation in Smart Home

Cited by 26 publications

References 35 publications

Control and Optimisation of Power Grids Using Smart Meter Data: A Review

Control and Optimisation of Power Grids Using Smart Meter Data: A Review

Optimizing Energy Usage and Smoothing Load Profile via a Home Energy Management Strategy with Vehicle-to-Home and Energy Storage System

Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home

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