Cyber-secure decentralized energy management for IoT-enabled active distribution networks

Li, Zhiyi; Shahidehpour, Mohammad; Li, Xuan

doi:10.1007/s40565-018-0425-1

Cited by 62 publications

(31 citation statements)

References 68 publications

(60 reference statements)

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“…The users in community give the preferences in terms of their idles operating modes. The objective function in equation 7and constraints are formulated in equation (8)(9)(10)(11)(12)(13).…”

Section: Problem Formulationmentioning

confidence: 99%

“…In equation (7), to obtain an optimal solution of users and their schedules using the centralized optimization approach to solve the problem by incorporating the constraints from equation (8)(9)(10)(11)(12)(13). This centralized optimization problem is based on aggregated load of whole community.…”

Section: Energy Consumption Gamementioning

confidence: 99%

“…The IoTs are generating a lot of data on the Internet. For this, users need the distributed, lightweight, scalable solutions to secure from cyber attacks, security, privacy, reliable and cheap system [9]. Blockchain technology is used for secure communication to handle the data in distributed and secure way.…”

Section: Introductionmentioning

confidence: 99%

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Blockchain Enabled Distributed Demand Side Management in Community Energy System With Smart Homes

et al. 2020

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Existing work in energy demand side management focuses on the interaction between the utility grid and consumers. However, the previous technique is not focused on energy trading in local community of a renewable energy generation, distributed demand side management and not suitable for real-time environment. This paper presents a distributed demand side management system among multiple homes in community microgrid, with the integration of the internet of things smart meter and in the presence of renewable energy sources. The proposed energy consumption game is formulated for minimizing the cost of electricity in the individual home and the total cost of energy consumption in the whole community. The smart home users are playing game by optimizing their own daily energy consumption of appliances. The multiple participants include the self renewable generation of users, shared community microgrid and optional utility company. Each participant applies its best strategy to minimize energy consumption cost and users can maintain their own privacy of energy consumption. Moreover, the proposed scheme is distributed on blockchain, which provides a trusted communication medium between the participants. It enforces the autonomous monitoring of smart appliances and the billing of electricity consumption via smart contracts. Solidity smart contract is deployed to facilitate the execution of transactions without the involvement of third party in the smart community. Comparison of the results show that the proposed approach minimizes the total cost of energy consumption as well as each user's energy consumption cost. INDEX TERMS Distributed demand side management, community microgrid, appliances scheduling, smart home, Internet of Things, blockchain, smart contracts.

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“…The users in community give the preferences in terms of their idles operating modes. The objective function in equation 7and constraints are formulated in equation (8)(9)(10)(11)(12)(13).…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Energy Consumption Gamementioning

confidence: 99%

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Blockchain Enabled Distributed Demand Side Management in Community Energy System With Smart Homes

et al. 2020

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“…Li et al [77] identified cybersecurity as one of the problems of IoT-based energy management and distribution systems. The architecture proposed by the authors attempted to incorporate blockchain technology in the communication process between IoT devices and microgrid nodes in an energy distribution network.…”

Section: • Architecturesmentioning

confidence: 99%

“…Other studies worth mentioning, are those presented by Amadeo et al [76] and Li et al [77] which included algorithms and encryption packets for data security in an intermediate layer of the architecture. The paper presented by Sittón-Candanedo et al [6] described an architecture that includes Blockchain and data encryption in its three levels, however, the proposal would have been stronger if the authors had implemented Crypto-IoT boards in IoT devices, thus improving the system in terms of security, traceability, and data integrity.…”

Section: • Architecturesmentioning

confidence: 99%

A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

et al. 2019

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Context: Smart Energy is a disruptive concept that has led to the emergence of new energy policies, technology projects, and business models. The development of those models is driven by world capitals, companies, and universities. Their purpose is to make the electric power system more efficient through distributed energy generation/storage, smart meter installation, or reduction of consumption/implementation costs. This work approaches Smart Energy as a paradigm that is concerned with systemic strategies involving the implementation of innovative technological developments in energy systems. However, many of the challenges encountered under this paradigm are yet to be overcome, such as the effective integration of solutions within Smart Energy systems. Edge Computing is included in this new technology group. Objective: To investigate developments that involve the use of Edge Computing and that provide solutions to Smart Energy problems. The research work will be developed using the methodology of systematic mapping of literature, following the guidelines established by Kitchenham and Petersen that facilitate the identification of studies published on the subject. Results: Inclusion and exclusion criteria have been applied to identify the relevant articles. We selected 80 papers that were classified according to the type of publication (journal, conferences, or book chapter), type of research (conceptual, experience, or validation), type of activity (implement, validate, analyze) and asset (architecture, framework, method, or models). Conclusion: A complete review has been conducted of the 80 articles that were closely related to the questions posed in this research. To reach the goal of building Edge Computing architectures for Smart Energy environments, several lines of research have been defined. In the future, such architectures will overcome current problems, becoming highly energy-efficient, cost-effective, and capacitated to process and respond in real-time.Electronics 2020, 9, 48 2 of 33 Ledger Technologies (such as blockchain) [15]; or distributed sensing and actuation technologies such as the Internet of Things (IoT) [3,16].Regarding the Internet of Things (IoT), its recognition as a paradigm dates back to 2011-2012, when renowned companies and institutions such as Gartner, Forbes, or Wired started using this term to refer to the emerging technology [17]. The Internet of Things implies the connection of different heterogeneous objects, including buildings, machinery, vehicles, and electronic devices, such as sensors and actuators interconnected by means of communication protocols and forming wireless or wired networks [18] to collect information and extract knowledge [19]. Since then, the scope of IoT has spread throughout a great variety of environments and disciplines, including solutions for development of Smart Cities [20,21], Industry 4.0 [22][23][24], transportation and logistics [25,26], smart homes and hotels [13,27,28] or, more relevant to this research, energy efficiency [8,29,30]. IoT provid...

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Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

Rahman

Islam

Kundu

et al. 2023

Int J Communication

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SummaryAs an emerging technology, blockchain (BC) has been playing a promising role in today's software‐defined networking (SDN)‐enabled Internet of Things (IoT) applications. Because of the salient feature of the network function virtualization (NFV) techniques, SDN can ensure an IoT system runs efficiently and smoothly in a cloud‐driven ecosystem. When cloud‐enabled systems encounter immense security and operational challenges caused mainly by third‐party dependency, large‐scale data communication, and maintenance, BC offers effective and robust data transfer solutions without incorporating intermediaries over the distributed network. With the increased SDN‐BC convergence in the IoT domain, the underlying challenges and perspectives deserve proper attention methodically and structurally. From the motivation of addressing such issues, this study provides necessary insights to combine those for successful plug‐and‐play. Therefore, the study includes purposefully investigating current state‐of‐the‐art to extract the research trends, future directions, and perspectives in this domain. This study provides a comprehensive survey of IoT, SDN, NFV, and BC‐enabled emerging technologies. More importantly, the authors intelligently integrated the four different technologies—IoT, SDN, BC, and NFV based on characteristics, scopes, challenges, taxonomies, and tables in numerous areas. Initially, the authors introduce the SDN‐IoT ecosystem in brief and address the features and applications. We took a close look at the SDN's overall taxonomy based on security, environment, scopes, and challenges. We also briefly describe the integration of SDN‐IoT with the NFV ecosystems. Moreover, we review the prospect of BC technology from security perspectives, its extent, challenges of practical implementation, and the possible integration of IoT regarding smart applications. Finally, this study highlights several future directions based on these technologies.

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Cyber-secure decentralized energy management for IoT-enabled active distribution networks

Cited by 62 publications

References 68 publications

Blockchain Enabled Distributed Demand Side Management in Community Energy System With Smart Homes

Blockchain Enabled Distributed Demand Side Management in Community Energy System With Smart Homes

A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

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