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A blockchain based privacy-preserving system for electric vehicles through local communication

- Yahaya, Adamu, Javaid, Nadeem, Khalid, Rabiya, Imran, Muhammad, Naseer, Nidal

A blockchain-based decentralized energy management in a P2P trading system

- Khalid, Rabiya, Javaid, Nadeem, Javaid, Sakeena, Imran, Muhammad, Naseer, Nidal

  • Authors: Khalid, Rabiya , Javaid, Nadeem , Javaid, Sakeena , Imran, Muhammad , Naseer, Nidal
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland, 7 to 11 June, IEEE International Conference on Communications Vol. 2020-June
  • Full Text: false
  • Reviewed:
  • Description: Local energy generation and peer to peer (P2P) energy trading in the local market can reduce energy consumption cost, emission of harmful gases (as renewable energy sources (RESs) are used to generate energy at user's premises) and increase smart grid resilience. In this paper, to implement a hybrid P2P energy trading market, a blockchain-based solution is proposed. A blockchain-based system is fully decentralized and it allows the market members to interact with each other and trade energy without involving any third party. Smart contracts play a very important role in the blockchain-based energy trading market. They contain all the necessary rules for energy trading. We have proposed three smart contracts to implement the hybrid electricity trading market. The market members interact with main smart contract which requests P2P smart contract and prosumer to grid (P2G) smart contract for further processing. The main objectives of this paper are to propose a model to implement an efficient hybrid energy trading market while reducing cost and peak to average ratio (PAR) of electricity. © 2020 IEEE.

A blockchain-based privacy-preserving mechanism with aggregator as common communication point

- Yahaya, Adamu, Javaid, Nadeem, Khalid, Rabiya, Imran, Muhammad, Guizani, Mohsen

  • Authors: Yahaya, Adamu , Javaid, Nadeem , Khalid, Rabiya , Imran, Muhammad , Guizani, Mohsen
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland, 7 to 11 June, IEEE International Conference on Communications Vol. 2020-June
  • Full Text: false
  • Reviewed:
  • Description: The high penetration of renewable energy resources into the distributed system and their intermittent behavior of the non-dispatchable generation causes issues of demand supply mismatch and serious security and privacy concerned in the system. It is believed that incorporating blockchain will reduce costs, enhance data security, and improve the system efficiency. However, privacy issues are not completely eliminated and can hinder the wide applications of blockchain. In the study, we present a Reputation Based Starvation Free Energy Allocation Policy (Reputation-SFEAP) in a decentralized and distributed blockchain-based energy trading; while keeping Aggregator as Common Communication Point. In addition, Identity-Based encryption (ID-Based encryption) technique is added that improves transactional information privacy. According to the research analysis, it is observed that the proposed system model has optimal and fair energy allocation algorithms, which prevent all the energy users from energy starvation and share the available energy accordingly. Moreover, the incorporated encryption system has greater security-privacy level, which protects passive attacker and disguises attacker from penetration. © 2020 IEEE.

DE-RUSBoost : an efficient electricity theft detection scheme with additive communication layer

- Mujeeb, Sana, Javaid, Nadeem, Khalid, Rabiya, Imran, Muhammad, Naseer, Nidal

  • Authors: Mujeeb, Sana , Javaid, Nadeem , Khalid, Rabiya , Imran, Muhammad , Naseer, Nidal
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland, 7 to 11 June, IEEE International Conference on Communications Vol. 2020-June
  • Full Text: false
  • Reviewed:
  • Description: Modern power grids depend on the Advanced Metering Infrastructure (AMI) for consumption monitoring, energy management and billing. However, AMIs are vulnerable to electricity theft cyber attacks due to addition of communication layer. Electricity theft is one of the major Non-Technical Losses (NTLs) in the electricity distribution systems that has become a global concern, recently. Although the machine learning techniques are widely used for Electricity Theft Detection (ETD) in literature, some significant challenges need to be address. (i) The consumption data is usually unlabeled, there should be proper method to label the data. (ii) The fair consumers significantly outnumber the fraudulent consumers, which negatively impacts the performance of classification algorithm. (iii) The performance of classifier must be validated using proper performance evaluation measures. In this paper, an enhanced ETD model is proposed that is an optimized classifier Differential Evaluation Random Under Sampling Boosting (DE-RUSBoost) is used for classification. Proposed classifier DE-RUSBoost is optimized using a metaheuristic optimization algorithm named Differential Evaluation (DE). The proposed method is evaluated on a real-world dataset, i.e., State Grid Corporation of China (SGCC) datasets. DE-RUSBoost achieves the highest accuracy of 96% and low false detection rate of 0.004. The proposed method outperforms its counterparts in terms of accuracy and false detection rate. © 2020 IEEE.
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