EVSE Effectiveness in Multi-Unit Residential Buildings Using Composite Optimization and Heuristic Search

Samadi, Mikhak; Fattahi, Javad

doi:10.1109/tpwrs.2023.3280434

Cited by 3 publications

(1 citation statement)

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“…With the increasing diversity of distributed energy resources (which include evolving load categories such as EV charging [10,11]), the high cost of supporting peak electricity consumption through centralized generation can be overcome at the distribution level if bottleneck issues associated with consumer participation in energy management can be addressed in the context of the likelihood of individual responses to distributed requests. The weakness of most DR approaches is an architectural one, a failure to accommodate the likelihood of the scope of individual responses to DR requests through a privacy-by-design probabilistic framework that is both fair and transparent, and that simultaneously expands and monetizes the energy informatics' role of the individual consumer using a robust and secure energy blockchain whose consensus algorithm addresses reputation, DR availability, and compliance.…”

Section: Introductionmentioning

confidence: 99%

Secure and Robust Demand Response Using Stackelberg Game Model and Energy Blockchain

Samadi,

Ruj,

Schriemer

et al. 2023

Sensors

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Demand response (DR) has been studied widely in the smart grid literature, however, there is still a significant gap in approaches that address security, privacy, and robustness of settlement processes simultaneously. The need for security and robustness emerges as a vital property, as Internet of Things (IoT) devices become part of the smart grid; in the form of smart meters, home energy management systems (HEMSs), intelligent transformers, and so on. In this paper, we use energy blockchain to secure energy transactions among customers and the utility. In addition, we formulate a mixed-strategy stochastic game model to address uncertainties in DR contributions of agents and achieve optimal demand response decisions. This model utilizes the processing hardware of customers for block mining, stores customer DR agreements as distributed ledgers, and offers a smart contract and consensus algorithm for energy transaction validation. We use a real dataset of residential demand profiles and photovoltaic (PV) generation to validate the performance of the proposed scheme. The results show the impact of electric vehicle (EV) discharging and customer demand reduction on increasing the probability of successful block mining and improving customer profits. Moreover, the results demonstrate the security and robustness of our consensus algorithm for detecting malicious activities.

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Section: Introductionmentioning

confidence: 99%