Impact of battery storage on residential energy consumption: An Australian case study based on smart meter data

Khafaf, Nameer Al; Rezaei, Ahmad Asgharian; Amani, Ali Moradi; Jalili, Mahdi; McGrath, Brendan; Meegahapola, Lasantha; Vahidnia, Arash

doi:10.1016/j.renene.2021.10.005

Cited by 43 publications

(12 citation statements)

References 51 publications

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“…It reveals demographic and locality information of customers that provide the grid operator with better knowledge of their occupancy behaviors [ 111 ]. Such information can benefit demand response operations and potentially support evidence-based policy decisions [ 112 ]. A case study to optimize energy management and the required energy capacity for a large group of households in the Netherlands is conducted over one year [ 113 ].…”

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

Self Cite

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“…The algorithm is realized by Python programming language and TensorFlow framework, and the hidden variable dimension is set to 10, the encoder adopts two-layer fully connected neural network, the decoder adopts one-layer fully connected neural network, the learning rate is set to 0.001, and the number of training rounds is set to 1000. Taking the data missing filling method of smart watt-hour meter based on the influence of battery storage on residential energy consumption in reference [5] as method 1, and the data missing filling method of smart watt-hour meter based on Internet of Things in reference [6] as method 2, this paper compares with the proposed method and conducts experimental analysis.…”

Section: Experimental Analysismentioning

confidence: 99%

“…Reference [5] studied how household battery devices lead to behavioral changes in energy consumption patterns. Provide data-based advice to distribution network operators and decision-makers.…”

Section: Introductionmentioning

confidence: 99%

Research on data missing filling of smart watt-hour meter based on variational self-encoder

Zhang

et al. 2023

Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023)

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The data of smart watt-hour meter has high-dimensional characteristics, and it is difficult to represent, so it is impossible to ensure high-precision filling of missing data. Therefore, the research on missing data filling of smart watt-hour meter based on variational self-encoder is proposed. Firstly, a filling model based on variational self-encoder is constructed to denoise the measurement data of smart watt-hour meter, then the denoised smart watt-hour meter data is input into the model, and the data missing filling result of smart watt-hour meter is output. Finally, the data missing filling of smart watt-hour meter is realized according to the result. The experimental results show that, after filling, the proposed method is coincident with the original data, and the final filling operation efficiency can reach more than 90%.

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“…Hemanth et al [29] proposed a method to recover missing data from SM measurements by using a particle swarm optimization (PSO) algorithm. Al Khafaf et al [30] studied the impact of using electrical energy storage in residential environments based on the use of SMs. Funde et al [31] studied data mining applied to the use of clustering to determine electricity usage patterns with SMs.…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of a Smart Energy Meter Using a LoRa Network in Real Time

2021

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Nowadays, the development, implementation and deployment of smart meters (SMs) is increasing in importance, and its expansion is exponential. The use of SMs in electrical engineering covers a multitude of applications ranging from real-time monitoring to the study of load profiles in homes. The use of wireless technologies has helped this development. Various problems arise in the implementation of SMs, such as coverage, locations without Internet access, etc. LoRa (long range) technology has great coverage and equipment with low power consumption that allows the installation of SMs in all types of locations, including those without Internet access. The objective of this research is to create an SM network under the LoRa specification that solves the problems presented by other wireless networks. For this purpose, a gateway for residential electricity metering networks using LoRa (GREMNL) and an electrical variable measuring device for households using LoRa (EVMDHL) have been created, which allow the development of SM networks with large coverage and low consumption.

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Impact of battery storage on residential energy consumption: An Australian case study based on smart meter data

Cited by 43 publications

References 51 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

Research on data missing filling of smart watt-hour meter based on variational self-encoder

Design and Implementation of a Smart Energy Meter Using a LoRa Network in Real Time

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