Blockchain and AI amalgamation for energy cloud management: Challenges, solutions, and future directions

A Kumari, R Gupta, S Tanwar, N Kumar - Journal of Parallel and Distributed …, 2020 - Elsevier
In the recent years, the Smart Grid (SG) system faces various challenges like the ever-
increasing energy demand, the enormous growth of renewable energy sources (RES) with …

Demand response in consumer-Centric electricity market: Mathematical models and optimization problems

BSK Patnam, NM Pindoriya - Electric Power Systems Research, 2021 - Elsevier
This article presents an overview of mathematical modeling and optimization of demand
response (DR) algorithms reported in the literature. The DR can be implemented at various …

Artificial intelligence enabled demand response: Prospects and challenges in smart grid environment

MA Khan, AM Saleh, M Waseem, IA Sajjad - Ieee Access, 2022 - ieeexplore.ieee.org
Demand Response (DR) has gained popularity in recent years as a practical strategy to
increase the sustainability of energy systems while reducing associated costs. Despite this …

Comparison of sustainability models in development of electric vehicles in Tehran using fuzzy TOPSIS method

F Samaie, H Meyar-Naimi, S Javadi… - Sustainable Cities and …, 2020 - Elsevier
In the present article, regarding the concept of sustainable development (SD), the
sustainability of Electric Vehicles (EVs) development in Tehran is evaluated. This paper …

A Bayesian game theoretic based bidding strategy for demand response aggregators in electricity markets

S Abapour, B Mohammadi-Ivatloo, MT Hagh - Sustainable Cities and …, 2020 - Elsevier
In recent years, significant development in smart metering and remote sensing systems in
the electricity industry, especially on the side of consumers, it has made in implementation …

[HTML][HTML] Exploring the potentialities of deep reinforcement learning for incentive-based demand response in a cluster of small commercial buildings

D Deltetto, D Coraci, G Pinto, MS Piscitelli, A Capozzoli - Energies, 2021 - mdpi.com
Demand Response (DR) programs represent an effective way to optimally manage building
energy demand while increasing Renewable Energy Sources (RES) integration and grid …

The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms

BY Katanalp, E Eren - Accident Analysis & Prevention, 2020 - Elsevier
In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was
revised with the C4. 5 decision tree (DT) algorithm, were applied to the classification of …

A MILP model to relieve the occurrence of new demand peaks by improving the load factor in smart homes

FV Cerna, J Contreras - Sustainable Cities and Society, 2021 - Elsevier
Demand response (DR) programs based on pricing options allow residential customers to
achieve a financial reduction in their energy bill due to changes in their consumption …

GIS-based assessment of pedestrian-vehicle accidents in terms of safety with four different ML models

BY Katanalp, E Eren - Journal of Transportation Safety & Security, 2022 - Taylor & Francis
In this study, both micro and macro level evaluation of pedestrian-vehicle crashes were
conducted. Macro-level findings were obtained with GIS-based density analyzes, and critical …

Power distribution network design considering the distributed generations and differential and dynamic pricing

YC Tsao, TD Beyene, VV Thanh, SG Gebeyehu… - Energy, 2022 - Elsevier
In this study, a power distribution network design model is developed considering voltage
control, as well as differential and dynamic pricing schemes. The objective is to maximize …