Results 61 to 70 of about 1,525,022 (327)

Demand Response Implementation: Overview of Europe and United States Status

open access: yesEnergies, 2023
The authors review the efforts made in the last five years to implement Demand Response (DR) programs, considering and studying several models and countries.
C. Silva, P. Faria, Z. Vale
semanticscholar   +1 more source

Residential electricity demand on CAISO Flex Alert days: a case study of voluntary emergency demand response programs

open access: yesEnvironmental Research: Energy, 2023
The California Independent System Operator (CAISO) utilizes a system-wide, voluntary demand response (DR) tool, called the Flex Alert program, designed to reduce energy usage during peak hours, particularly on hot summer afternoons when surges in ...
McKenna Peplinski, Kelly T Sanders
doaj   +1 more source

A truthful incentive mechanism for emergency demand response in colocation data centers [PDF]

open access: yes, 2015
Data centers are key participants in demand response programs, including emergency demand response (EDR), where the grid coordinates large electricity consumers for demand reduction in emergency situations to prevent major economic losses. While existing
Li, Z, Ren, S, Wu, C, Zhang, L
core   +1 more source

Blockchain-Enabled Demand Response Scheme with Individualized Incentive Pricing Mode

open access: yesEnergies, 2020
Demand response (DR) can offer a wide range of advantages for electrical systems by facilitating the interaction and balance between supply and demand. However, DR always requires a central agent, giving rise to issues of security and trust. Besides this,
Zishan Guo, Zhenya Ji, Qi Wang
doaj   +1 more source

Capturing Aggregate Flexibility in Demand Response

open access: yes, 2014
Flexibility in electric power consumption can be leveraged by Demand Response (DR) programs. The goal of this paper is to systematically capture the inherent aggregate flexibility of a population of appliances.
Alizadeh, Mahnoosh   +3 more
core   +1 more source

Increasing the Benefit from Cost-Minimizing Loads via Centralized Adjustments

open access: yesEnergies, 2016
Several demand response (DR) strategies rely on real-time pricing and selfish local optimization, which may not result in optimal electricity consumption patterns from the viewpoint of an energy supplier or a power system.
Antti Alahäivälä, Matti Lehtonen
doaj   +1 more source

Electric Water Heater Modeling, DR Approaches Analysis and Study of Consumer Comfort for Demand Response

open access: yesDREAM-GO 4th Whorshop - Demand response approaches for real-time renewable energy integration, 2019
With the smart energy management system household residential appliances is able to participate in the demand response events. To reduce peak load demand and complexities in the local infrastructure DR can play an important role now a days. This paper presents a study and analysis of several papers on residential EWH DR modeling and implementation.
Ahmed, Faria, Pedro, Vale, Zita
openaire   +2 more sources

A Discount-Based Time-of-Use Electricity Pricing Strategy for Demand Response with Minimum Information Using Reinforcement Learning

open access: yesIEEE Access, 2022
Demand Response (DR) programs show great promise for energy saving and load profile flattening. They bring about an opportunity for indirect control of end-users’ demand based on different price policies.
Alejandro Fraija   +5 more
semanticscholar   +1 more source

Demand Response Technology Readiness Levels for Energy Management in Blocks of Buildings

open access: yesBuildings, 2018
Fossil fuels deliver most of the flexibility in contemporary electricity systems. The pressing need to reduce CO2 emissions requires new methods to provide this flexibility.
Tracey Crosbie   +4 more
doaj   +1 more source

BQL-DRS: A Novel Balanced Q-Learning Based Demand Response System for IoT based Smart Grids

open access: yesInternational Journal on Recent and Innovation Trends in Computing and Communication, 2023
The modernization of electricity networks and the integration of renewable energy resources in Internet of Things (IoT) based smart grids have led to increased variability in market prices, necessitating effective demand response (DR) strategies. To address this challenge, this paper proposes a novel Balanced Q-Learning based Demand Response System ...
openaire   +1 more source

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