Internet of energy-based demand response management scheme for smart homes and PHEVs using SVM

Jindal, Anish; Kumar, Neeraj; Singh, Mukesh

doi:10.1016/j.future.2018.04.003

Cited by 37 publications

(17 citation statements)

References 24 publications

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“…Similarly, EVSEs use Open Charge Point Protocol (OCPP) for communication between the EVSE and the energy management systems. While EI-based V2G has many benefits (as mentioned above), cyber-security of the components and data are big concerns [28][29]. The vehicles themselves face increasingly complex attacks that target not only the vehicle's operation but also its privacy.…”

Section: Methodsmentioning

confidence: 99%

“…On the other hand, during the execution of the proposed authenticated key agreement scheme, all parties communicate through an insecure public channel. In this context, we consider the Dolev-Yao threat model (DY model) [29], where an adversary may eavesdrop, modify, or delete the messages exchanged during transmission. Now, due to the usage of public networks and wireless communication in this EI-based V2G environment, there is a possibility of several attacks, such as impersonation, man-in-the middle, replay attacks, etc.…”

Section: B Adversary Modelmentioning

confidence: 99%

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An Efficient Privacy-Preserving Authentication Scheme for Energy Internet-Based Vehicle-to-Grid Communication

Gope

Sikdar

2019

IEEE Trans. Smart Grid

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Section: Methodsmentioning

confidence: 99%

Section: B Adversary Modelmentioning

confidence: 99%

An Efficient Privacy-Preserving Authentication Scheme for Energy Internet-Based Vehicle-to-Grid Communication

Gope

Sikdar

2019

IEEE Trans. Smart Grid

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“…The residential sector includes homes and buildings, whereas the commercial sector includes banking, hospitals, stores, etc., and the industrial sector comprises of many industries such as food processing, manufacturing, and automobile. Moreover, the rapid increase in the electric vehicles (EVs) penetration in the transportation sector has escalated the burden on the electricity grids manifolds as they also require electric energy to charge their batteries [6]. All these sectors need electric energy to perform their dayto-day operations.…”

Section: Introductionmentioning

confidence: 99%

GUARDIAN: Blockchain-Based Secure Demand Response Management in Smart Grid System

Jindal

Aujla

Kumar

et al. 2020

IEEE Trans. Serv. Comput.

Self Cite

102

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Smart grid (SG) is an emerging technology which provides many services to the end users and utilities such as-load management, frequency regulation, and grid stability. Although many solutions exist to provide these services in a secure manner, but these solutions are not adequate keeping in view of the heavy cryptographic primitives execution on these devices. Hence, in this paper, GUARDIAN, a blockchain-based secure demand response management scheme is presented so as to take energy trading decisions securely for managing the overall load of residential, commercial, and industrial sectors. In GUARDIAN, the miner nodes, which are block verifiers, are selected using their power consumption and processing power. These nodes are responsible for authenticating the energy transactions in SG. The energy transaction is initialized by an end user which creates the block of transaction to trade the energy. The miner nodes then validate these blocks and adds these in the blockchain. The successful energy trade occurs only for the blocks which are in the blockchain. The proposed scheme is lightweight in terms of communication and computation costs. Moreover, the results obtained demonstrate the effectiveness of proposed scheme for secure demand response management in the SG.

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“…Intensive research has been carried out to manage demand response effectively. Some of these techniques are discussed here [6][7][8][9]. In [6], a demand response model is developed for flattens the load curve, clips the peak load and decreases the customer's payment cost.…”

Section: Introductionmentioning

confidence: 99%

Gated recurrent unit based demand response for preventing voltage collapse in a distribution system

Gundu¹,

Simon²,

Sundareswaran³

et al. 2020

Turk J Elec Eng & Comp Sci

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This paper presents the application of deep learning algorithms towards demand response management. Demand limit violation and voltage stability are the major problems associated with a secondary distribution system. These problems are solved using demand response models by day ahead scheduling loads at every 15 minutes interval through linear integer programming and based on short term forecasting of load(kW). A new architecture for short term load forecasting is presented namely Gated Recurrent Unit in which statistical analysis is carried out to get the optimal architecture of the neural network model. Reliability indices such as Loss of Load Probability (LOLP) is evaluated to handle uncertainties that may occur in forecasting due to overestimation and underestimation. Here a novel dynamic power flow is carried out to check limit violation of the voltage. Also, scheduling is performed for two types of loads namely deferrable with interruptible and deferrable with uninterruptable, when either of maximum demand or voltage limit violation occurs. Finally, the suggested model is validated on a modified 12 bus radial distribution system. The result analysis shows that the suggested Gated Recurrent Unit minimizes the forecast error and demand response program schedules household appliances without a demand limit violation and ensures the prevention of voltage collapse.

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Internet of energy-based demand response management scheme for smart homes and PHEVs using SVM

Cited by 37 publications

References 24 publications

An Efficient Privacy-Preserving Authentication Scheme for Energy Internet-Based Vehicle-to-Grid Communication

An Efficient Privacy-Preserving Authentication Scheme for Energy Internet-Based Vehicle-to-Grid Communication

GUARDIAN: Blockchain-Based Secure Demand Response Management in Smart Grid System

Gated recurrent unit based demand response for preventing voltage collapse in a distribution system

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