Power consumption forecast model using ensemble learning for smart grid

Kumar, Jitendra; Gupta, Rishabh; Saxena, Deepika; Singh, Ashutosh Kumar

doi:10.1007/s11227-023-05096-4

Cited by 13 publications

(2 citation statements)

References 26 publications

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“…With the incorporation of digital technology in power supply system, traditional grids are transformed into smart grids that allow two systems for bi-directional communication, electricity consumption data analysis, enhanced management of power distribution and provides self-healing capabilities to the grid system. The smart grids employ the digital technology to record the consumers' power usage behaviours through smart sensors that help to manage power generation and supply efficiently [1][2][3][4][5]. A generic smart grid architecture includes a grid domain that generates, distributes and manages the electricity along with the service providers domain that include markets, operators and service providers to help consumers provide with tariff planning and other application based interfaces and the customer domain that includes house area networks with smart meters [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Review Of Fault-Tolerant Data Aggregation Schemes For Smart Grid Environment

Rani,

Swain

2024

Preprint

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The advent of smart grid in the power infrastructure of the nations has provisioned a proactive and highly efficient power management at the generation end and user end as well. The smart meters being a fundamental part of the grid system are responsible for the intermittent sharing of usage data that further assists the utility for decision making. However, the inclusion of digital technology accompanies some major challenges like data security, data loss and communication issues etc. Smart meters are lightweight devices hence susceptible to errors frequently and therefore can cause loss of data. If the unavailability of usage data is significantly high, this can be problematic for the utility in context with further power generation and distribution decisions. This article presents a comprehensive discussion of the fault-tolerant aggregation models for the smart grid environment. A thorough investigation of the most recent research on handling of unavailable data is provided. Finally, the paper identifies the major challenges and future research possibilities for an efficiently fault-tolerant aggregation in the smart grid environment.

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Section: Introductionmentioning

confidence: 99%

A Review Of Fault-Tolerant Data Aggregation Schemes For Smart Grid Environment

Rani,

Swain

2024

Preprint

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“…The vulnerabilities and susceptibilities of virtual machines management layer and hypervisor facilitates malicious user to get access to target physical machine and compromise all the virtual machines hosted on it. Hence, the prime challenge for cloud datacentre is to secure user data which is distributed on the shared multi-tenant physical servers while provisioning higher scalability of resources along with high performance and cost optimization [42,[113][114][115][116][117][118][119][120][121][122][123][124][125].…”

Section: Introductionmentioning

confidence: 99%

A Review on Secure Cloud Resource Management

Chhabra¹,

Saxena²,

Rekha³

2023

Preprint

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<p>Security is always a prime concern of every cloud user. Many pioneer surveys have been done concerning security during data communication among owners, users, and stakeholders. However, there is a lack of literature surveys that address the concern of security during data processing or the workload execution within cloud data centers. In this context, we present a concise review of the existing methods that have addressed the security of workload or user data during load scheduling and execution within cloud environments. These methods have applied load-balancing strategies that helped to minimize the security attacks via co-residency or covert channels. The pandect comparative summary of these methods follows the corresponding review. The paper is concluded with limitations and future direction concerning secure load management.</p>

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