Search Results - "Mixed Integer Linear Programming Framework"

Day‐ahead charging operation of electric vehicles with on‐site renewable energy resources in a mixed integer linear programming framework

Authors: İbrahim Şengör Ayşe Kübra Erenoğlu Ozan Erdinç et al.

Contributors: İbrahim Şengör Ayşe Kübra Erenoğlu Ozan Erdinç et al.

Source: IET Smart Grid (2020)

Subject Terms: Power System, peak load limitation, 02 engineering and technology, related evpl, 7. Clean energy, demand response strategies, pricing, 0202 electrical engineering, electronic engineering, information engineering, Photovoltaic Power Systems, Smart Grid Paradigm, ev parking lots, electric vehicles, distribution system operators, demand side management, On-Site Renewable Energy Resources, Scenario-Based Approach, different aggregators, Related EVPL, scenario-based approach, Mixed Integer Linear Programming Framework, linear programming, dr strategies, Battery Storage Plants, Dsos, day-ahead charging operation, power system, EV Parking Lots, Peak Load Limitation, Electrical engineering. Electronics. Nuclear engineering, daily solar irradiation data, dsos, on-site renewable energy resources, PLL, peak load limitation based dr strategies, battery storage plants, evpls, Large-Scale Penetration, pv generation, smart grid paradigm, Different Aggregators, Demand Response Strategies, DR Strategies, Arrival Time, arrival time, Operational Flexibility, PV Generation, Distribution System Operators, Daily Solar Irradiation Data, Linear Programming, State-Of-Energy, integer programming, operational flexibility, related ev owners, pll, state-of-energy, photovoltaic power systems, Peak Load Limitation Based DR Strategies, Evpls, large-scale penetration, mixed integer linear programming framework, Demand Side Management, TK1-9971, Day-Ahead Charging Operation, smart power grids, Related EV Owners, power generation scheduling, Power Generation Scheduling, Smart Power Grids, Electric Vehicles, Pricing, Integer Programming

File Description: application/pdf

Access URL: https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-stg.2019.0282
https://doaj.org/article/c9b2c7f5eed54049afcd2b43bae01327
https://avesis.yildiz.edu.tr/yayin/0d476fff-d9f4-43b1-8818-6edd9f6c958d/day-ahead-charging-operation-of-electric-vehicles-with-on-site-renewable-energy-resources-in-a-mixed-integer-linear-programming-framework
https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-stg.2019.0282
https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-stg.2019.0282
https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0282
https://hdl.handle.net/20.500.12809/461
https://doi.org/10.1049/iet-stg.2019.0282
https://avesis.yildiz.edu.tr/publication/details/0d476fff-d9f4-43b1-8818-6edd9f6c958d/oai
https://aperta.ulakbim.gov.tr/record/6571

A novel multiobjective generation and transmission investment framework for implementing 100% renewable energy sources

Authors: Abed Bagheri Vahid Vahidinasab Kamyar Mehran et al.

Contributors: Abed Bagheri Vahid Vahidinasab Kamyar Mehran et al.

Source: IET Generation, Transmission & Distribution. 12:455-465

Subject Terms: stochastic multiobjective mixed-integer linear programming framework, power transmission economics, 4. Education, 0211 other engineering and technologies, generation unit types, investment, linear programming, 02 engineering and technology, novel multiobjective transmission investment framework, 7. Clean energy, novel multiobjective generation investment framework, harmful gaseous emission reduction, smart power grids, stochastic programming, RES-based system, 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, dominated RES power system, renewable energy sources, smart grid, integer programming, power generation economics, uncertainty level

Access URL: https://ieeexplore.ieee.org/document/8281359/
https://core.ac.uk/display/159078172
https://qmro.qmul.ac.uk/xmlui/handle/123456789/31828
https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-gtd.2017.0976
https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2017.0976