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A Strategy for System Risk Mitigation Using FACTS Devices in a Wind Incorporated Competitive Power System

doi: 10.3390/su14138069
Electricity demand is sharply increasing with the growing population of human beings. Due to financial, social, and political barriers, there are lots of difficulties when building new thermal power plants and transmission lines. To solve this problem, renewable energy sources and flexible AC transmission systems (FACTS) can operate together in a power network. Renewable energy sources can provide additional power to the grid, whereas FACTS devices can increase the thermal limit of existing transmission lines. It is always desirable for an electrical network to operate under stable and secure conditions. The system runs at risk if any abnormality occurs in the generation, transmission, or distribution sections. This paper outlines a strategy for reducing system risks via the optimal operation of wind farms and FACTS devices. Here, a thyristor-controlled series compensator (TCSC) and a unified power flow controller (UPFC) have both been considered for differing the thermal limit of transmission lines. The impact of the wind farm, as well as the combined effect of the wind farm and FACTS devices on system economy, were investigated in this work. Both regulated and deregulated environments have been chosen to verify the proposed approach. Value at risk (VaR) and cumulative value at risk (CVaR) calculations were used to evaluate the system risk. The work was performed on modified IEEE 14 bus and modified IEEE 30-bus systems. A comparative study was carried out using different optimization techniques, i.e., Artificial Gorilla Troops Optimizer Algorithm (AGTO), Honey Badger Algorithm (HBA), and Sequential Quadratic Programming (SQP) to check the effect of renewable integration in the regulated and deregulated power systems in terms of system risk and operating cost.
- Mizoram University India
- AIST Japan
- Mizoram University India
Environmental effects of industries and plants, Honey Badger Algorithm (HBA), Artificial Gorilla Troops Optimizer Algorithm (AGTO), TJ807-830, system risk, TD194-195, Renewable energy sources, Environmental sciences, system economy, FACTS devices, GE1-350, competitive power market; FACTS devices; system risk; system economy; Artificial Gorilla Troops Optimizer Algorithm (AGTO); Honey Badger Algorithm (HBA), competitive power market
Environmental effects of industries and plants, Honey Badger Algorithm (HBA), Artificial Gorilla Troops Optimizer Algorithm (AGTO), TJ807-830, system risk, TD194-195, Renewable energy sources, Environmental sciences, system economy, FACTS devices, GE1-350, competitive power market; FACTS devices; system risk; system economy; Artificial Gorilla Troops Optimizer Algorithm (AGTO); Honey Badger Algorithm (HBA), competitive power market
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).35 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
