A hybrid approach for enhancing grid restoration

• Autorzy: Minaxi Minaxi , Saini Sanju , Tiwari Garima

Identyfikatory

DOI

10.15199/48.2024.09.13

Warianty tytułu

PL

Hybrydowe podejście do poprawy odtwarzania sieci

• Języki publikacji: EN

Abstrakty

EN

Blackout restoration is crucial to energy security and infrastructure resilience. Black-start procedures must be used to restore a power grid methodically. Grid recovery requires selecting the correct unit black-start optimization methods. Each Dijkstra shortest path approach determines a unit's optimum recovery route after a large power loss. A full indication includes unit capacity, climbing rate, beginning power, recovery time, and route recovery capacitance. An exhaustive index. This index facilitates unit startup. We end with a unit black-start strategy using the optimal recovery route, unit start sequence, and unit start limitations. This method works in the IEEE30 node system simulation. Research suggests the black-start method may boost unit recovery and success. Black-start strategy performance is assessed for two prominent graph-based algorithms, Dijkstra and A*. Unit black-start analysis is assessed for Dijkstra and A* algorithms. Priorities include start sequence and recovery path optimization. Grid recovery efficiency and efficacy depend on performance measures. Optimization, route length, and calculation time improve process dependability and efficiency. Dijkstra's simple, reliable approach works well in certain situations. The heuristic A* algorithm works well in certain cases. Both strategies are used in this paper to improve system performance. Explaining the power system's peculiarities comparatively allows for selecting an algorithm.

PL

Przywracanie po awarii ma kluczowe znaczenie dla bezpieczeństwa energetycznego i odporności infrastruktury. Procedury czarnego startu muszą być stosowane w celu metodycznego przywracania sieci energetycznej. Przywracanie sieci wymaga wybrania prawidłowych metod optymalizacji czarnego startu jednostki. Każde podejście Dijkstry do najkrótszej ścieżki określa optymalną trasę odzyskiwania jednostki po dużej utracie mocy. Pełne wskazanie obejmuje pojemność jednostki, szybkość wznoszenia, moc początkową, czas odzyskiwania i pojemność odzyskiwania trasy. Wyczerpujący indeks. Ten indeks ułatwia uruchamianie jednostki. Kończymy strategią czarnego startu jednostki, wykorzystując optymalną trasę odzyskiwania, sekwencję uruchamiania jednostki i ograniczenia uruchamiania jednostki. Ta metoda działa w symulacji systemu węzłów IEEE30. Badania sugerują, że metoda czarnego startu może zwiększyć odzyskiwanie i sukces jednostki. Wydajność strategii czarnego startu jest oceniana dla dwóch wybitnych algorytmów opartych na grafach, Dijkstry i A*. Analiza czarnego startu jednostki jest oceniana dla algorytmów Dijkstry i A*. Priorytety obejmują sekwencję uruchamiania i optymalizację ścieżki odzyskiwania. Efektywność i skuteczność odzyskiwania sieci zależą od miar wydajności. Optymalizacja, długość trasy i czas obliczeń poprawiają niezawodność i wydajność procesu. Proste, niezawodne podejście Dijkstry sprawdza się w pewnych sytuacjach. Heurystyczny algorytm A* sprawdza się w pewnych przypadkach. Obie strategie są używane w tym artykule w celu poprawy wydajności systemu. Wyjaśnienie osobliwości systemu energetycznego w sposób porównawczy pozwala na wybór algorytmu.

Słowa kluczowe

EN

hybrid algorithm; grid restoration; black-start recovery; resilience strategy

PL

algorytm hybrydowy; przywracanie sieci; odzyskiwanie po czarnym starcie; strategia odporności

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 9
• Strony: 80--84
• Opis fizyczny: Bibliogr. 32 poz., rys., tab.

Twórcy

autor

Minaxi Minaxi

• Deenbandhu Chhotu Ram University of Science and Technology, Murthal

• https://orcid.org/0000-0003-4172-725X

autor

Saini Sanju

• Deenbandhu Chhotu Ram University of Science and Technology, Murthal

• https://orcid.org/0000-0003-1390-4861

autor

Tiwari Garima

• Deenbandhu Chhotu Ram University of Science and Technology, Murthal

• https://orcid.org/0000-0002-3004-0375

Bibliografia

• [1] J. Zhao, H. Wang, Y. Liu, Q. Wu, Z. Wang, and Y. Liu, Coordinated Restoration of Transmission and Distribution System Using Decentralized Scheme, IEEE Transactions Power System, 34 (2019), No. 5, 3428–3442.
• [2] M. S. Javed, T. Ma, J. Jurasz, and M. Y. Amin, Solar and wind power generation systems with pumped hydro storage: Review and future perspectives, Renewable Energy, 148 (2020), 176 192.
• [3] P. Yuan et al., Analysis and Enlightenment of the Blackouts in Argentina and New York, in Chinese Automation Congress (CAC), Hangzhou, China: IEEE, (2019), 5879–5884.
• [4] Y. Liu, R. Fan, and V. Terzija, Power system restoration: a literature review from 2006 to 2016, Journal of Modern Power Systems and Clean Energy, 4 (2016), No. 3, 332–341.
• [5] A. Ketabi, A. Karimizadeh, and M. Shahidehpour, Optimal generation unit’s start-up sequence during the restoration of power system considering network reliability using bi-level optimization, International Journal of Electrical Power & Energy Systems, 104 (2019), 772–783.
• [6] C. Shen, P. Kaufmann, and M. Braun, Optimizing the generator start-up sequence after a power system blackout, in 2014 IEEE PES General Meeting, Conference & Exposition, National Harbor, MD, USA: IEEE, (2014), 1–5.
• [7] Y. Zhao et al., Energy storage for black start services: A review, International Journal of Minerals, Metallurgy and Materials, 29 (2022), No. 4, 691–704.
• [8] H. Bevrani, M. R. Feizi, and S. Ataee, Robust Frequency Control in an Islanded Microgrid: H∞ and μ-Synthesis Approaches, IEEE Transaction Smart Grid, (2015).
• [9] A. Fathi, Q. Shafiee, and H. Bevrani, Robust Frequency Control of Microgrids Using an Extended Virtual Synchronous Generator, IEEE Transaction Power System, 33 (2018), No. 6, 6289–6297.
• [10] A. Halik, Y. Syam, A VECM Analysis of the Impact of Economic Growth and Investment on Electricity Consumption in Indonesia, Przegląd Elektrotechniczny, 2(2024), 140-144.
• [11] P. Yuan et al., Analysis and Enlightenment of the Blackouts in Argentina and New York, in 2019 Chinese Automation Congress (CAC), Hangzhou, China: IEEE, (2019), 5879–5884.
• [12] J. Su, C. Chen, and Z. Bie, Optimal Generator Start-Up Sequence Strategy Considering Renewable Energy Participation, in The Proceedings of the 17th Annual Conference of China Electrotechnical Society, 1014 (2023), 934–945.
• [13] S. Zhai, H. Wang, Y. Shan, and X. Zhang, Optimal Generator Start-up Sequence with Active Distribution Networks Considering Recovery Path, in 2021 IEEE 4th International Conference on Electronics Technology (ICET), Chengdu, China: IEEE, (2021), 472–478.
• [14] S. Alhamid, O. hamandouch, A. Darwish, A hybrid Bees Algorithm to Enhance the Performance of Radial Distribution Systems, Przegląd Elektrotechniczny, 2(2024), 193-196.
• [15] K. Liang, H. Wang, D. Pozo, and V. Terzija, “Power system restoration with large renewable Penetration: State-of-the-Art and future trends,” International Journal of Electrical Power and Energy Systems, 155 (2024), 109494.
• [16] En Lu, Ning Wang, Zhijun Qin, Haoming Liu, and Yunhe Hou, Black-start strategy for power grids including fast cut thermal power units, in 2013 IEEE Power & Energy Society General Meeting, Vancouver, BC: IEEE, (2013), 1–5.
• [17] V. Singhvi, D. Ramasubramanian, S. Uppalapati, W. Baker, and E. Farantatos, An Analytical Procedure to Evaluate Optimal Restoration Path with Multiple Blackstart Units Including Inverter Based Resources, in 2021 IEEE Power & Energy Society General Meeting (PESGM), Washington, DC, USA: IEEE, (2021), 1–5.
• [18] J. Zhao et al., Research on the Unit Black-Start Strategy Considering Recovery Path and Start Sequence, Sustainability, 14 (2022), No. 20, 13057.
• [19] T. Wang, H. Zhu, Z. Wang, Y. Wang, N. Sun, and Y. Dong, Multi-objective Optimization of Unit Restoration During Network Reconstruction Based on DE-EDA, in 2020 IEEE 3rd International Conference on Electronics and Communication Engineering (ICECE), Xi’An, China: IEEE, (2020), 102–106.
• [20] A. Ketabi, A. Karimizadeh, and M. Shahidehpour, Optimal generation unit’s start-up sequence during restoration of power system considering network reliability using bi-level optimization, International Journal of Electrical Power & Energy Systems, 104 (2019), 772–783.
• [21] Y. Hou, C.-C. Liu, K. Sun, P. Zhang, S. Liu, and D. Mizumura, Computation of Milestones for Decision Support During System Restoration, IEEE Transactions on Power Systems, 26 (2011), No. 3, 1399–1409.
• [22] En Lu, Ning Wang, Zhijun Qin, Haoming Liu, and Yunhe Hou, Black-start strategy for power grids including fast cut thermal power units, in 2013 IEEE Power & Energy Society General Meeting, Vancouver, BC: IEEE, (2013), 1–5.
• [23] X. Gu, G. Zhou, S. Li, and T. Liu, “Global optimization model and algorithm for unit restarting sequence considering black start zone partitioning,” IET Generation, Transmission & Distribution, 13 (2019), No. 13, 2652–2663.
• [24] A. Ketabi, H. Asmar, A. M. Ranjbar, and R. Feuillet, An approach for optimal unit’s start-up during bulk power system restoration, in LESCOPE 01. 2001 Large Engineering Systems Conference on Power Engineering. Conference Proceedings. Theme: Powering Beyond 2001 (Cat. No.01ex490), Halifax, NS, Canada: IEEE, (2001), 190–194.
• [25] D. Hazarika and A. K. Sinha, “Power system restoration: planning and simulation,” International Journal of Electrical Power & Energy Systems, 25 (2003), No. 3, 209–218.
• [26] G. Bagha and A. Kumar, Load Flow Analysis of IEEE-30 Bus System Using FACTS Device, SSRN Electron. Journal, (2020).
• [27] Zhou Yunhai and Min Yong, Optimal algorithm for system reconstruction, in Proceedings. International Conference on Power System Technology, Kunming, China: IEEE, (2002), 201–203.
• [28] L. Xu, Q. Guo, Y. Sheng, S. M. Muyeen, and H. Sun, On the resilience of modern power systems: A comprehensive review from the cyber-physical perspective, Renewable and Sustainable Energy Review, 152 (2021), 111642.
• [29] C. Ju, Q. Luo, and X. Yan, Path Planning Using an Improved A-star Algorithm, in 2020 11th International Conference on Prognostics and System Health Management (PHM-2020 Jinan), Jinan, China: IEEE, (2020), 23–26.
• [30] D. Foead, A. Ghifari, M. B. Kusuma, N. Hanafiah, and E. Gunawan, A Systematic Literature Review of A* Pathfinding, Procedia Computer Science, 179 (2021), 507–514.
• [31] D. Rachmawati and L. Gustin, Analysis of Dijkstra’s Algorithm and A* Algorithm in Shortest Path Problem, Journal of Physics: Conference Series, 1566 (2020), No. 1, 012061.
• [32] S. Erke, D. Bin, N. Yiming, Z. Qi, X. Liang, and Z. Dawei, An improved A-Star based path planning algorithm for autonomous land vehicles, International Journal of Advanced Robotic Systems, 17 (2020), No. 5, 172988142096226.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).