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Blockchain and AI amalgamation for energy cloud management: Challenges, solutions, and future directions
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 …
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 …
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
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 …
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
In the present article, regarding the concept of sustainable development (SD), the
sustainability of Electric Vehicles (EVs) development in Tehran is evaluated. This paper …
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
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 …
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
Demand Response (DR) programs represent an effective way to optimally manage building
energy demand while increasing Renewable Energy Sources (RES) integration and grid …
energy demand while increasing Renewable Energy Sources (RES) integration and grid …
The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms
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 …
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
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 …
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
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 …
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
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 …
control, as well as differential and dynamic pricing schemes. The objective is to maximize …