Non-technical loss analysis and prevention using smart meters

Ahmad, Tanveer

doi:10.1016/j.rser.2017.01.100

Cited by 78 publications

(31 citation statements)

References 64 publications

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“…A few review articles focused on non-intrusive load monitoring (NILM), such as different disaggregation algorithms [17] and the evaluation criteria [18]. The methods for how to detect non-technical loss (NTL) in power grids based on smart meter data were reviewed in [19], while the NTL challenges were discussed in [20]. The applications of smart meter data analytics on customer behavior were summarized in [21].…”

Section: B Relevant Review Articlesmentioning

confidence: 99%

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Wang

Chen

Hong

et al. 2019

IEEE Trans. Smart Grid

918

370

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The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected. Meanwhile, the deregulation of the power industry, particularly on the delivery side, has continuously been moving forward worldwide. How to employ massive smart meter data to promote and enhance the efficiency and sustainability of the power grid is a pressing issue. To date, substantial works have been conducted on smart meter data analytics. To provide a comprehensive overview of the current research and to identify challenges for future research, this paper conducts an application-oriented review of smart meter data analytics. Following the three stages of analytics, namely, descriptive, predictive and prescriptive analytics, we identify the key application areas as load analysis, load forecasting, and load management. We also review the techniques and methodologies adopted or developed to address each application. In addition, we also discuss some research trends, such as big data issues, novel machine learning technologies, new business models, the transition of energy systems, and data privacy and security.

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Section: B Relevant Review Articlesmentioning

confidence: 99%

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Wang

Chen

Hong

et al. 2019

IEEE Trans. Smart Grid

918

370

View full text Add to dashboard Cite

show abstract

“…As a result, by using a robust system of two-way communications, AMI can provide intelligence to the conventional electrical network. Additionally, AMI can satisfy the future demand growth and can help to achieve the following: integration of DRES, dynamic operation of the network and progress of the communication standards [2].…”

Section: Ami In Microgridsmentioning

confidence: 99%

“…With the increase in demand, at peak hours, there is a need for more generation plants to avoid voltage drops and the decrease in the quality of the electrical energy. As a result, institutions should encourage the Demand Side Management (DSM), which becomes viable, implementing robust bi-directional communication systems [2]. These systems need appropriate hybrid topologies to allow the communication network to provide the user with reliability and safety on the use of information [3], This approach opens a path to the existence of an intelligent electric network (IEN).…”

Section: Introductionmentioning

confidence: 99%

Optimal Deployment of FiWi Networks using Heuristic Method for Integration Microgrids with Smart Metering

Inga¹,

Campaña²,

Hincapié³

et al. 2018

Preprint

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The unpredictable increase in electrical demand affects the quality of theenergy throughout the network. A solution to the problem is the increase of distributedgeneration units which burn fossil fuels.While this is an immediate solution to theproblem the ecosystem gets affected by the emission of CO2.A promising solutionis the integration of Distributed Renewable Energy Sources (DRES) to the conventionalelectrical system, thus, introducing the concept of smart microgrids (SMG) that requirea safe, reliable and technically planned two-way communication system. This documentpresents a heuristic based on planning capable of providing a bidirectional communicationnear optimal route map, following the structure of an hybrid Fiber-Wireless (FiWi) with thepurpose of obtaining information of electrical parameters that help us to manage the useof energy by integrating conventional electrical system to SMG. A FiWi network is basedon the integration of wireless access and optical networks. This integration increases thecoverage and reliability at a lower cost. The optimization model is based on clusteringtechniques, through the construction of balanced conglomerates. The method is used forthe development of the clusters along with the Nearest-Neighbor Spanning Tree Algorithm(N-NST). Additionally, Optimal Delay Balancing (ODB) model will be used to minimizethe end to end delay of each grouping. In addition, the heuristic observes real designparameters such as: capacity and coverage. Using the Dijkstra algorithm, the routes arebuilt following the minimum shorter path. Therefore, this paper presents a heuristic able to plan the deployment of smart meters (SMs) through a tree-like hierarchical topology for theintegration of SMG at the lowest cost.

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“…With the increase in demand at peak hours, there is a need for more generation plants to avoid voltage drops and the decrease in the quality of the electrical energy. As a result, institutions should encourage Demand Side Management (DSM), which becomes viable by implementing robust bidirectional communication systems [ 2 ]. These systems need appropriate hybrid topologies to allow the communication network to provide the user with reliability and safety on the use of information [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering

Inga

Campaña

Hincapié

et al. 2018

Sensors

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The unpredictable increase in electrical demand affects the quality of the energy throughout the network. A solution to the problem is the increase of distributed generation units, which burn fossil fuels. While this is an immediate solution to the problem, the ecosystem is affected by the emission of CO2. A promising solution is the integration of Distributed Renewable Energy Sources (DRES) with the conventional electrical system, thus introducing the concept of Smart Microgrids (SMG). These SMGs require a safe, reliable and technically planned two-way communication system. This paper presents a heuristic based on planning capable of providing a bidirectional communication that is near optimal. The model follows the structure of a hybrid Fiber-Wireless (FiWi) network with the purpose of obtaining information of electrical parameters that help us to manage the use of energy by integrating conventional electrical system with SMG. The optimization model is based on clustering techniques, through the construction of balanced conglomerates. The method is used for the development of the clusters along with the Nearest-Neighbor Spanning Tree algorithm (N-NST). Additionally, the Optimal Delay Balancing (ODB) model will be used to minimize the end to end delay of each grouping. In addition, the heuristic observes real design parameters such as: capacity and coverage. Using the Dijkstra algorithm, the routes are built following the shortest path. Therefore, this paper presents a heuristic able to plan the deployment of Smart Meters (SMs) through a tree-like hierarchical topology for the integration of SMG at the lowest cost.

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Non-technical loss analysis and prevention using smart meters

Cited by 78 publications

References 64 publications

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Optimal Deployment of FiWi Networks using Heuristic Method for Integration Microgrids with Smart Metering

Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering

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