[논문]Artificial Intelligence Application using Nutcracker Optimization Algorithm to Enhance Efficiency & Reliability of Power Systems via Optimal Setting and Sizing of Renewable Energy Sources as Distributed Generations in Radial Distribution Systems

Nawaf A. AlZahrani; Mohammad Hamza Awedh; Ali M. Rushdi

doi:10.22937/ijcsns.2024.24.1.5

Artificial Intelligence Application using Nutcracker Optimization Algorithm to Enhance Efficiency & Reliability of Power Systems via Optimal Setting and Sizing of Renewable Energy Sources as Distributed Generations in Radial Distribution Systems

International journal of computer science and network security : IJCSNS, v.24 no.1, 2024년, pp.31 - 44

Nawaf A. AlZahrani (Electrical Engineering Department, Faculty of Engineering, King Abdulaziz University) , Mohammad Hamza Awedh (Electrical Engineering Department, Faculty of Engineering, King Abdulaziz University) , Ali M. Rushdi (Electrical Engineering Department, Faculty of Engineering, King Abdulaziz University)

Abstract ▼ AI-Helper

People have been using more energy in the last years. Several research studies were conducted to develop sustainable energy sources that can produce clean energy to fulfill our energy requirements. Using renewable energy sources helps to decrease the harm to the environment caused by conventional power plants. Choosing the right location and capacity for DG-RESs can greatly impact the performance of Radial Distribution Systems. It is beneficial to have a good and stable electrical power supply with low energy waste and high effectiveness because it improves the performance and reliability of the system. This research investigates the ideal location and size for solar and wind power systems, which are popular methods for producing clean electricity. A new artificial intelligent algorithm called Nutcracker Optimization Algorithm (NOA) is used to find the best solution in two common electrical systems named IEEE 33 and 69 bus systems to examine the improvement in the efficiency & reliability of power system network by reducing power losses, making voltage deviation smaller, and improving voltage stability. Finally, the NOA method is compared with another method called PSO and developed Hybrid Algorithm (NOA+PSO) to validate the proposed algorithm effectiveness and enhancement of both efficiency and reliability aspects.

주제어

표/그림 (23)

그림 Fig. 1. Nutcracker Bird
그림 Fig. 2. Search Space in NOA
그림 Fig. 3. Three different locations for the nutcracker in 3-D space, with three different locations of 𝑹𝑷 for one cache
그림 Fig. 4. Different viewing angles of the nutcracker for both cache and 𝑹𝑷
그림 Fig. 5. Framework of NOA
그림 Fig. 6. Flowchart of the exploration and exploitation process in the foraging and storage strategy
그림 Fig. 7. Probable options for the Nutcracker to recover its recover its cache
그림 Figure 10. IEEE-33 Bus Radial Distribution System
그림 Fig. 11. Voltage Profile of IEEE-33 Bus in case of DG PV using NOA Algorithm
그림 Fig. 12. Voltage Profile of IEEE-33 Bus in case of DG WT using NOA Algorithm
그림 Fig. 13. Voltage Profile of IEEE-33 Bus in case of Combined DGs PV and WT using NOA Algorithm
그림 Figure 14. IEEE-69 Bus Radial Distribution System
그림 Fig. 15. Voltage Profile of IEEE-69 Bus in case of DG PV using NOA Algorithm
그림 Fig. 16. Voltage Profile of IEEE-69 Bus in case of DG WT using NOA Algorithm
그림 Fig. 17. Voltage Profile of IEEE-69 Bus in case of Combined DGs PV and WT using NOA Algorithm
그림 Fig. 8. Flowchart of NOA
그림 Fig. 9. Flowchart of Hybrid Algorithm (NOA+PSO)
표 Table 1. Outcomes for the 33-node grid in case of DG PV
표 Table 2. Outcomes for the 33-node grid in case of DG WT
표 Table 3. Outcomes for the 33-node grid in case of combined PV and WT
표 Table 4. Outcomes for the 69-node grid in case of DG PV
표 Table 5. Outcomes for the 69-node grid in case of DG WT
표 Table 6. Outcomes for 69-node grid in case of combined DGs PV & WT

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표제어: PCR

동의어: Packet Collision Rate

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