پاسخ‌گویی هوشمند بار الکتریکی به‌منظور تداوم برق‌رسانی در شرایط جنگی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار دانشگاه امام حسین (ع)

2 دانشگاه جامع امام حسین (ع)

3 دانشیار دانشگاه جامع امام حسین (ع)

4 کارشناسی ارشد دانشگاه شهید باهنر کرمان

چکیده

تلاش برای برنامه‌ریزی هرچه بهینه‌تر سامانه‌های قدرت از دیدگاه‌های مختلف، اعم از اقتصادی، فنی، و زیست‌محیطی، در راستای تأمین تقاضا به‌صورت مطمئن، پیوسته ادامه دارد. از جمله این برنامه‌ریزی‌ها، برنامه‌ریزی مشارکت واحدهای نیروگاهی است. در این مقاله، برنامه‌ریزی مشارکت امنیت- مقید واحدهای نیروگاهی با تمرکز بر اهمیت راهبردی انرژی الکتریکی در بستر شبکه‌های هوشمند مورد بررسی قرار گرفته است. در این راستا،‌ ابتدا مدلی جامع برای برنامه‌ریزی مشارکت واحدها، توأم با برنامۀ پاسخ‌گویی بار اضطراری (EDRP) ارائه شده است. برای تطبیق مدل مزبور با شرایط جنگی، مدل جدیدی از برنامه EDRP، تحت عنوان برنامه پاسخ‌گویی بار اضطراری راهبردی (SEDRP) نیز ارائه شده است. سپس با استفاده از یک مدل احتمالی برای تخمین برون‌رفت واحدها متأثر از عوامل مختلف در شرایط جنگی،طی سناریوهای متعدد، مدل موردنظر،‌ در قالب یک مسئله بهینه‌سازی خطی آمیخته با اعداد صحیح،‌ با استفاده از نرم‌افزار بهینه‌ساز GAMS حل شده است. در انتها، با توجه به نتایج حاصله، اثربخشی منابع پاسخ‌گویی بار هوشمند بر تداوم برق‌رسانی و هزینه‌های سیستم در شرایط موردنظر مورد ارزیابی قرار گرفته است. مشاهدات حاکی از آن است که مشارکت هوشمند سمت تقاضا، می‌تواند منجر به افزایش تداوم برق‌رسانی و کاهش هزینه‌ها در شرایط بحرانی منجر گردد.

کلیدواژه‌ها


عنوان مقاله [English]

Smart Demad Response of the Electrical Load to Increase the Continuity of Load Meeting under War Condition

نویسندگان [English]

  • R. Ghaffarpour 1
  • E. Zarei 2
  • A. Khanahmadi 3
  • H. Alami 4
1 Imam Hossein University
2 Imam Hossein University
3 Imam Hossein University
4 Shahid Bahonar University of Kerman
چکیده [English]

The efforts for better planning of power systems from various viewpoints, such as economic, technical, and environmental, for reliably meeting the demand are continued. The unit commitment (UC) is one of these planning problems. In this paper, the security-constrained unit commitment problem is addressed with focusing on the strategic importance of electrical energy in the presence of smart grids. To achieve this, firstly, a comprehensive UC model, amalgamating with emergency demand response programs (EDRP), is presented. To adapt the model with war condition, a modified form of EDRP, the so called strategic EDRP, is also proposed. The problem is formulated as a mixed integer linear programming problem solved via the GAMS. Then, to investigate the impacts of smart demand response programs on the reliability of load meeting, several scenarios are conducted regarding a stochastic contingency model for generating units under war condition. It is found in result evaluation that smart demand side contribution under war condition can increase reliability and so decreases the costs.

کلیدواژه‌ها [English]

  • UC
  • Demand Response
  • Critical Condition
  • Passive Defence
[1] “National Memorial Institute for the Prevention of Terrorism in the US”; http://MIPT.org, 2001.##
[2] Aalami, H. A.; Ramezani, H. “Presentation of a New Algorithm for the Operation of DG Resources in Electrical Interconnection Grids over the Critical Conditions”; Passive Defence Sci. Technol. 2013, 3, 231-241 (In Persian).##
[3] Namazi, H.; Fakoori, M. “Process for Detecting Passive Defence Acpects”; Department of Sustaining Human Resources, Central Education and Military Service Office, Iran, 2008.##
[4] Firouzi, H. “Introduction of Strategic Aspects of Electricity Network’s Reliable Management from the Perspective of Crisis Management”; Passive Defence Quarterly 2013, 14, 11-18 (In Persian).##
[5] Aghaei, J.; Nikoobakht, A. “Exploring the Reliability Effects on the Short Term AC Security-Constrained Unit Commitment: A Stochastic Evaluation”; Energy 2016, 114, 1016-1032.##

[6] Govardhan, M.; Roy, R.; “Economic Analysis of Unit Commitment with Distributed Energy Resources”; Int. J. Elec. Power Energ Syst. 2015, 71, 1-14.##

[7] Wang, B.; Zhou, X.; Wang, S.; Watada, J. Multi-Objective Unit Commitment with Wind Penetration and Emission Concerns Under Stochastic and Fuzzy Uncertainties”; Energy 2016, 111, 18-31.##

[8] Bayindir, R.; Colak, I.; Fulli, G. K.; Demirtas, K. “Smart Grid Technologies and Applications”; Renew. Sust. Energ. Rev. 2016, 66, 499-516.##

[9] Luis, M. “Collaborative Smart Grids – A Survey on Trends”; Renew. Sust. Energ. Rev.  2016, 65, 283-294, 2016.##

[11] Losi, A.; Mancarella, P.; Vicino, A. “Integration of Demand Response into the Electricity Chain Challenges”; Opportunities and Smart Grid Solutions, 2015.##
[12] Hu, B.; Wu, L.; Guan, X.; Gao, F.; Zhai, Q. “Comparison of Variant Robust SCUC Models for Operational Security and Economics of Power Systems under Uncertainty”; Elec. Power Syst. Res. 2016, 133, 121-131.##

[13] Durga Hari Kiran, B.; Sailaja Kumari, M. “Demand Response and Pumped Hydro Storage Scheduling for Balancing Wind Power Uncertainties: A Probabilistic Unit Commitment Approach”; Int. J. Electrical Power Energ. Syst. 2016, 81, 114-122.##

[14] Partovi, F.; Nikzad, M.; Mozafari, B.; Ranjbar, A. “Stochastic Security Approach Toenergy and Spinning Reserve Scheduling Considering Demand Response Program”; Energy 2011, 295-313.##
 [15] Sahebi, M. M.; Hosseini, S. H. “Stochastic Security Constrained Unit Commitment Incorporating Demand Side Reserve”; Int. J. Elec. Power Energ. Syst. 2014, 56, 175-184.##
 [16] Magnago, F. H.; Alemany, J.; Lin, J. “Impact of Demand Response Resources on Unit Commitment and Dispatch in a Day-Ahead Electricity Market”; Int. J. Elec. Power Energ. Syst. 2015, 68, 142-149.##
[17] Liu, G.; Tomsovic, K. “Robust Unit Commitment Considering Uncertain Demand Response”; Elec. Power Syst. Res. 2015, 119, 126-137.##
[18] Bai, Y.; Zhong, H.; Xia, Q.; Kang, C.; Xie, L. “A Decomposition Method for Network-Constrained Unit Commitment with AC Power Flow Constraints”; Energy 2015, 88, 595-603.##
[19] Nasrolahpour, E.; Ghasemi, H. “A Stochastic Security Constrained Unit Commitment Model for Reconfigurable Networks With High Wind Power Penetration”; Elec. Power Syst. Res. 2015, 121, 341-350.##
[20] Ghaffarpour, R.; Hashemi, Y.; Ehsan, M. “Involving Defensive Approach in Unit Commitment Scheduling and Presenting Probability Model of Plants Inaccessibility”; Passive Defence Sci. Technol. 2015, 4, 231-246.##

[21] Guan, X.; Guo, S.; Zhai, Q. “The Conditions For Obtaining Feasible Solutions to Security-Constrained Unit Commitment Problems”; IEEE Trans. Power Syst. 2005, 20, 1746-1756.##

[22] Fu, Y.; Shahidehpour, M.; Li, Z. “Security-Constrained Optimal Coordination of Generation and Transmission Maintenance Outage Scheduling”; IEEE Trans. Power Syst. 2007, 22, 1302-1313.##

[23] Fu, Y.; Shahidehpour, M.; Li, Z. “Security-Constrained Unit Commitment with AC Constraints”; IEEE Trans. Power Syst. 2005, 20, 1538-1550.##

[24] Jeong, Y. W.; Park, J. B.; Jang, S. H. “A New Quantum-Inspired Binary PSO: Application to Unit Commitment Problems for Power Systems”; IEEE Trans. Power Syst. 2010, 25, 1486-1495.##
[25] Arroyo, J. M.; Conejo, A. J. “Parallel Repair Genetic Algorithm to Solve the Unit CommitmentProblem”; IEEE Trans. Power Syst. 2002, 17, 1216-1224.##

[26] Dudek, G. “Adaptive simulated annealing schedule to the unit commitment problem”; Elec. Power Syst. Res. 2010, 80, 465-472.##

[27] Eslamian, M.; Hosseinian, S. H.; Vahidi, B. “Bacterial Foraging-Based Solution to the Unit Commitment Problem”; IEEE Trans. Power Syst. 2009, 24, 1478-1488.##
[28] Mohammadi, F.; Abdi, H.; Dehnavi, E. “Solving Dynamic Economic Emission Dispatch Problem with Optmal Emergency Demand Response Program Considering Spinning Reserve and Valve Point-effect Constraintsm”; Tabriz J. Elec. Eng.  2016, 46, 343-356.##
[29] Abdollahi, A.; Moghaddam, M. P.; Rashidinejad, M. “Investigation of Economic and Environmental-Driven Demand Response Measures Incorporating UC”; IEEE Trans. Smart Grid 2011, 3, 12-25.##
[30] Aalami, H.; Moghaddam, M. P.; Yousefi, G. “Demand Response Modeling Considering Interruptible/Curtailable Loads and Capacity Market Programs”; Appl. Energy 2010, 87, 243-250.##
[31] Aalami, H.; Moghaddam, M. P.; Yousefi, G. “Modeling and Prioritizing Demand Response Programs in Power Markets”; Elec. Power Syst. Res. 2010, 80, 426-435.##
[32] Yousefi, S.; Moghaddam, M. P.; Majd, V. J. “Optimal Real Time Pricing in an Agent-Based Retail Market Using a Comprehensive Demand Response Model”; Energy 2011, 36, 5716-5727.##
[33] Bisanovic, S.; Hajro, M.; Dlakic, M. “Hydrothermal Self-Scheduling Problem in a Day-Ahead Electricity Market”; Elec. Power Syst. Res. 2008, 78, 1579-1596.##

[34] Aghaei, J.; Alizadeh, M. I. “Critical Peak Pricing With Load Control Demand Response Program in Unit Commitment Problem”; IET Generation, Transmission & Distribution 2013, 7, 681-690.##

 [35] Carrion, M.; Arroyo, J. M. “A Computationally Efficient Mixed-Integer Linear Formulation for the Thermal Unit Commitment Problem”; IEEE Trans. Power Syst. 2006, 21, 1371-1378.##

 [36] Careri, F.; Genesi, C.; Marannino, P.; Montagna, M.; Rossi, S.; Sivierom, I. “Generation Expansion Planning in the Age of Green Economy”; IEEE Trans. Power Syst. 2011, 26, 2214-2223.##

[37] Wong, P.; Albrecht, P.; Allan, R.; Billinton, R.; Chen, Q.; Fong, C. “The IEEE Reliability Test System-1996. A Report Prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee”; IEEE Trans. Power Syst. 1999, 14, 1010-1020.##