Multi-Objective Generation Scheduling of Hydro-Thermal System Incorporating Energy Storage With Demand Side Management Considering Renewable Energy Uncertainties

Atmospheric pollutants, mainly produced by thermal power plants compel to utilize green energy sources such as renewable energy sources and hydroelectric plants in a power system. But due to blinking behavior of sources of renewable energy and due to very high rate of outages, it has a detrimental c...

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Bibliographic Details
Published in:IEEE access 2022, Vol.10, p.52343-52357
Main Authors: Jena, Chitralekha, Guerrero, Josep M., Abusorrah, Abdullah, Al-Turki, Yusuf, Khan, Baseem
Format: Article
Language:English
Subjects:
Alternative energy sources
Blinking
Clean energy
Costs
Demand side management
Electric power demand
Energy management
Energy resources
Energy storage
Evolutionary algorithms
fixed head hydro plant
Genetic algorithms
Hydroelectric plants
Multiple objective analysis
Optimal scheduling
outage
Outages
Pollutants
pumped storage plant(PSP)
pumped-hydro storage unit
Renewable energy sources
Renewable resources
Scheduling
Sorting algorithms
sources of renewable energy
Thermal power plants
Uncertainty
Wind power generation
Wind turbines
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Summary:Atmospheric pollutants, mainly produced by thermal power plants compel to utilize green energy sources such as renewable energy sources and hydroelectric plants in a power system. But due to blinking behavior of sources of renewable energy and due to very high rate of outages, it has a detrimental consequence on overall grid. Demand side management (DSM) programs decrease cost and improve power system security. This study proposes non-dominated sorting genetic algorithm-II (NSGA-II) to solve multi-objective scheduling of generation for fixed head hydro-thermal system integrating pumped hydro energy storage and sources of renewable energy taking into consideration the outage and uncertainty in presence of DSM. Numerical results of the test system attained using the proposed technique were compared with strength pareto evolutionary algorithm 2 (SPEA 2).
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3172500