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Risk-Cost Minimization in Optimal Reactive Power Dispatch Problem in the DFIG Integrated System | ||
| International Journal of Industrial Electronics Control and Optimization | ||
| مقاله 7، دوره 6، شماره 3، آذر 2023، صفحه 229-240 اصل مقاله (707.89 K) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22111/ieco.2023.46094.1492 | ||
| نویسندگان | ||
| Mohammad Hassan Moradi* 1؛ Meysam - Mokari2؛ mohammad abedini3 | ||
| 1Bu-ali Sina University, Hamadan | ||
| 2Iran Grid Management Company (IGMC) | ||
| 3Department of Electrical Engineering, Ayatollah Boroujerdi University, Boroujerd, Iran | ||
| چکیده | ||
| In this paper, a novel method for a multi-objective and risk-based optimal reactive power dispatch is proposed. The method includes two main objective functions: technical and economic. The technical objective involves minimizing the risks of voltage instability, voltage deviation, and flow violation, and the economic objective involves minimizing the costs of reactive power generation, active power losses, load shedding, and active power rescheduling. Using these functions and assigning different weighting factors for each sub-objective, the risk of the events or uncertainties to customers or the grid can be managed. In addition, moment matching is used to discretize and create scenarios from continues probability distribution functions of wind speed and electrical energy uncertainties. As the number of uncertain variables increases, so does the number of scenarios and the simulation time. Therefore, the fast-forward selection algorithm is applied to reduce the number of scenarios. To reduce the computational complexity and the number of topological scenarios, a new contingency filtering method based on high-risky events is proposed. A modified multi-objective PSO algorithm based on a hybrid PSO with sine-cosine acceleration coefficients is proposed to find the Pareto front of solutions. The method is implemented on the modified IEEE 30-bus test system. To demonstrate the effectiveness of the proposed method, the results are compared with previously published literature. The results show that risk-based scheduling increases system reliability and cost-effectiveness compared to traditional scheduling. | ||
| کلیدواژه‌ها | ||
| Multi-objective risk-based optimal reactive power dispatch؛ Voltage instability Risk؛ Power system uncertainty؛ Hybrid multi objective PSO with sine cosine acceleration coefficients | ||
| مراجع | ||
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[1] J.D. McCalley, V. Vittal, N. Abi-Samra, “An overview of risk based security assessment,” IEEE Power Engineering Society Summer Meeting. Conference Proceedings Edmonton, Alta., Canada, 1999.
[2] A. Rabiee, A. Soroudi, B. M. Ivatloo, “Corrective voltage control scheme considering demand response and stochastic Wind power,” IEEE Transactions on Power Systems, 2014. [3] A. Rabiee, A. Souroudi, A. Keane, “Risk-Averse preventive voltage control of AC/DC power systems including wind power generation,” IEEE Transaction on Sustainable Energy, 10.1109/ TSTE. 2451511, 2015. [4] L. Roald, M. Vrakopoulou, F. Oldewurtel, G. Andersson, “ Risk-Constrained optimal power flow with probabilistic Guarantees,” Power Systems Computation Conference, 2015. [5] Y. . Li, Q. H. Wu, “Downside riskconstrained probabilistic optimal power flow with wind power integrated,” IEEE Transactions on Power Systems, Volume: 31, Issue: 2,2016. [6] L. Roald , G. Andersson, S. Misra, M. Chertkov, S. Backhaus, “Optimal power flow with wind power control and limited expected risk of overloads,” Power Systems Computation Conference (PSCC), Genoa, Italy,2016. [7] L. Roald, S. Misra, A. Morrison, G. Andersson, “Optimized risk limits for stochastic optimal power flow,” IEEE 56th Annual Conference on Decision and Control (CDC) December 12-15, Melbourne, Aus,2016. [8] M. Nojvan, H. Seyedi, B. H. Ivatloo, “Preventive voltage control scheme considering demand response, correlated wind and load uncertainties,” Journal of Energy Management and Technology (JEMT), 13, Paper no. JEMT1705-1011, 2017. [9] P. Fakhrooeian, M. Abedi, P. Karimyan, “optimal allocation and sizing of dynamic VAR support to improve short-termvoltage stability considering wind farm and dynamic load model,” International Journal of Industrial Electronics, Control and Optimization, Vol. 1, No. 1,pp. 41-51, June 2018. [10] M. Ghaljehei, Z. Soltani, J. Lin, G.B. Gharehpetian, M.A Golkar, “Stochastic multi-objective optimal energy and reactive power dispatch considering cost, loading margin and coordinated reactive power reserve management,” Electric Power Systems Research 166, 163–177, 2019. [11] M. Mokari, M.H. Moradi, “Security constraint optimal reactive power dispatch under uncertainty in a wind integrated power system,” 55th International Universities Power Engineering Conference (UPEC),2020. [12] M. Knittel, N. Majumdar, M. Schneider, N. Thie, A. Moser, “Voltage control in transmission grids considering uncertainties of renewable energy sources,” 6th IEEE International Energy Conference, 2020. [13] M. Ettappan, V. Vimala, S. Ramesh, V. Thiruppathy Kesavan, “Optimal reactive power dispatch for real power loss minimization and voltage stability enhancment using artificial Bee colony algorithm,” Microprocessors and Microsystems doi.org/10.1016/j.micpro.2020.103085, 2020. [14] P. Lei, C. Wang, Q. Wu, M. Yan, “Risk-based distributionally robust real-time dispatch considering voltage security,” IEEE Transaction on Sustainable Energy, Volume: 12, Issue: 1 , 2021. [15] M. Hassan, S. Kamel, M. El-Dabah, T. Khurshaid, J. L. Dominguez-Garcia, “Optimal reactive power dispatch with time-varying demand and renewable energy uncertainty using Rao-3 algorithm,” IEEE Access ( Volume: 9), DOI: 10.1109/ACCESS.2021.3056423.2021. [16] S. Hosseini-Hemati, S. Karimi, G. H. Sheisi, “MultiObjective ORPD considering different load models for active distribution networks,” International Journal of Industrial Electronics, Control and Optimization, Vol. 4, No. 2,pp. 191-210, April 2022. [17] V. Zakutsky, M. G. Gadzhiev, “Coordinated voltage and reactive power control of power systems with wind farms and SVCs as problem,” 4th International Youth Conference on Radio Electronics, Electrical and Power Engineering, 2022. [18] M. S.Saddique, S. Habib, S. S. Haroon., A. R. Bahatti, S. Amin, “Optimal solution of reactive power dispatch in transmission system to minimize power losses using sinecosine algorithm,” IEEE Access, Vol: 10, 2022. [19] M.H. Moradi, M.Mokari, M. Abedini, “An investigation of technical uncertainties in power networks with the aim of improving voltage stability and reducing system losses using the SPEA-II optimization algorithm,” Iranian Electric Industry Journal Quality & Productivity Vol. 11 / No. 1/ Spring 2022 (In Persian). [20] M.Mokari, M.H.Moradi, M. Abedini, “Fuzzy risk-based optimal reactive power dispatch in a wind-integrated power system,” Tabriz Journal of Electrical Engineering (TJEE), vol. 53, no. 1, Spring 2023. [21] W. Li, “Risk assessment of power systems: Models, methods, and applications, Second Edition,” John Wiley & Sons, 2014. [22] Z. Hu, GA. Hu, “Two-stage stochastic programming model for lot-sizing and scheduling under uncertainty,” International Journal of Production Economics, 180 , 198{207}, 2016. [23] P. Kessel, H. Glavitsch, “Estimating the voltage stability of a power system,” IEEE Transactions on Power Delivery, 346-54, 1986. [24] M. Jazaeri, M. Mokari, “A new technical-economical algorithm to improve asymmetry in system voltage by SVC,” European Journal of Scientific Research. vol. 115 No.3. 2013. [25] C. A. Coello, G. T. Pulido, M. S. Lechuga, “Handling multiple objectives with particle swarm optimization,” IEEE Transactions on Evolutionary Computation, VOL. 8. 8, NO. 3, 2004. [26] K. Chen, F. Zhou, L. Yin, Sh. Wang, Y. Wang, F. Wan, “A hybrid particle swarm optimizer with sine cosine acceleration coefficients,” Information Sciences 422, 218–241, 2018. [27] A. Abou El Elaa, M.A. Abidob, S.R. Spea, “Differential evolution algorithm for optimal reactive power dispatch,” Electric Power Systems Research 81 (2011) 458–464.
[28] A. Ghasemi, Kh. Valipour, A. Tohidi, “Multi objective optimal reactive power dispatch using a new multi objective strategy,” Electrical Power and Energy Systems 57 (2014) 318–334. [29] S. M. Bonab, A. Rabiee, B. M. Ivatloo, “Multi-Objective optimal reactive power dispatch considering uncertainties in the wind integrated power system,” Springer international Publishing , 10.1007/978-3-319-51118-4_12,AG 2017. | ||
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آمار تعداد مشاهده مقاله: 162 تعداد دریافت فایل اصل مقاله: 243 |
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