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Computational Intelligence Based Pevs Aggregator Scheduling with Support for Photovoltaic Power Penetrated Distribution Grid Under Snow Conditions

https://doi.org/10.2139/ssrn.4051093
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1 of 25 checkable references need attention · checked 2026-07-24

At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.

6 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

References needing attention

marked retracted — notice via Crossref, record curated by Retraction Watch10.1016/j.ijepes.2021.107179
RETRACTED: A robust optimization method for optimizing day-ahead operation of the electric vehicles aggregator
The 24 checked references that resolve
resolves10.1016/j.est.2020.101193
A review of strategic charging–discharging control of grid-connected electric vehicles
resolves10.1016/j.ijepes.2021.107361
The key role of aggregators in the energy transition under the latest European regulatory framework
resolves10.1007/978-1-4419-7421-1
Decision Making Under Uncertainty in Electricity Markets
resolves10.1016/j.epsr.2020.106367
A risk-constrained decision support tool for EV aggregators participating in energy and frequency regulation markets
resolves10.1016/j.energy.2016.10.141
Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets
resolves10.3390/en12091755
Optimal Coordinated Bidding of a Profit Maximizing, Risk-Averse EV Aggregator in Three-Settlement Markets Under Uncertainty
resolves10.1109/TSG.2017.2715259
An Innovative Two-Level Model for Electric Vehicle Parking Lots in Distribution Systems With Renewable Energy
resolves10.1109/TVT.2019.2900931
Stochastic-Based Optimal Charging Strategy for Plug-In Electric Vehicles Aggregator Under Incentive and Regulatory Policies of DSO
resolves10.1016/j.trd.2018.03.006
A review of EVs charging: From the perspective of energy optimization, optimization approaches, and charging techniques
resolves10.1109/TITS.2018.2889439
Distribution System Services Provided by Electric Vehicles: Recent Status, Challenges, and Future Prospects
resolves10.1109/TSTE.2015.2498521
Self Scheduling of Plug-In Electric Vehicle Aggregator to Provide Balancing Services for Wind Power
resolves10.1016/j.apenergy.2019.01.238
Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach
resolves10.3390/en9070538
Optimal Coordinated Management of a Plug-In Electric Vehicle Charging Station under a Flexible Penalty Contract for Voltage Security
resolves10.1109/TVT.2019.2936786
A Discounted Stochastic Multiplayer Game Approach for Vehicle-to-Grid Voltage Regulation
resolves10.1109/JSYST.2020.3006848
A Coordinated Electric Vehicle Management System for Grid-Support Services in Residential Networks
resolves10.1109/JSYST.2020.2997189
DLMP Calculation and Congestion Minimization With EV Aggregator Loading in a Distribution Network Using Bilevel Program
resolves10.1016/j.ijepes.2021.107176
A taxonomical review on recent artificial intelligence applications to PV integration into power grids
resolves10.1109/JPHOTOV.2020.2987158
Snow Loss Prediction for Photovoltaic Farms Using Computational Intelligence Techniques
resolves10.1002/pip.1224
Local and regional photovoltaic power prediction for large scale grid integration: Assessment of a new algorithm for snow detection
resolves10.1145/3004056
A Cloud-Based Black-Box Solar Predictor for Smart Homes
resolves10.1016/j.enconman.2018.11.074
Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting
resolves10.1016/j.renene.2018.08.005
Short-term and regionalized photovoltaic power forecasting, enhanced by reference systems, on the example of Luxembourg
resolves10.1109/TSG.2014.2317502
Integration of Price-Based Demand Response in DisCos' Short-Term Decision Model
resolves10.1162/neco.1997.9.8.1735
Long Short-Term Memory
The 6 references without a DOI — listed, not checked
no DOI — not checkedRisk-constrained bidding strategy for demand response, green energy resources, and plug-in electric vehicle in a flexible smart grid
no DOI — not checkedref26
no DOI — not checkedref27
no DOI — not checkedref29
no DOI — not checkedRadial distribution test feeders
no DOI — not checkedref31
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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