Abstract
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).
| Original language | English |
|---|---|
| Pages (from-to) | 52343-52357 |
| Number of pages | 15 |
| Journal | IEEE Access |
| Volume | 10 |
| DOIs | |
| Publication status | Published - 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Demand side management
- fixed head hydro plant
- outage
- pumped storage plant(PSP)
- pumped-hydro storage unit
- sources of renewable energy
- uncertainty
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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