Antlion Optimization Algorithm for Optimal Self-Scheduling Unit ‎Commitment in Power System Under Uncertainties

سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 53

فایل این مقاله در 16 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_JOAPE-9-3_005

تاریخ نمایه سازی: 13 آبان 1402

چکیده مقاله:

optimal and economic operation is one of the main topics in power systems. In this paper, a stochastic single objective framework for GenCoʼs optimal self-scheduling unit commitment under the uncertain condition and in the presence of SH units is proposed. In order to solve this problem, a new meta-heuristic optimization technique named antlion optimizer (ALO) has been used. Some of the capabilities of the ALO algorithm for solving the optimization problems included : (۱) the exploration and utilization, (۲) abiding convergence, (۳) capable of maintaining population variety, (۴) lack of regulation parameters, (۵) solving problems with acceptable quality. To approximate the simulation conditions to the actual operating conditions, the uncertainties of the energy price, spinning and non-spinning reserve (operating services) prices, as well as the renewable energy resources uncertainty, are considered in the proposed model. The objective function of the problem is profit maximization and modeled as a mixed-integer programming (MIP) problem. The proposed model is implemented on an IEEE ۱۱۸-bus test system and is solved in the form of six case studies. Finally, the simulation results substantiate the strength and accuracy of the proposed model.

کلیدواژه ها:

نویسندگان

M.R. Behnamfar

Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful,

H. Barati

Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful,

M. Karami

Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • M. Shahidehpour et al., “Market operations in electric powersystems, forecasting, ...
  • A.j. Wood and B. Wollenberg, “Power generation operation and control”, ...
  • M. Sharafi Masouleh et al., “Mixed- integer programming of stochastic ...
  • L. Lakshminarasimman and S. Subramanian, “Short-term scheduling of hydro-thermal power ...
  • A. Esmaeily et al., “Evaluatin the effectiveness of Mixed - ...
  • S. Bisanovic, M. Hajro and M. Dlakic, “Hydro-thermal Self-scheduling problem ...
  • A. Conejo et al., “Self-scheduling of a hydro producer in ...
  • M. Karami et al., “Scenario-basedsecurity constrained hydro- Therm coordination with ...
  • J. Aghaei et al., “A mixed-integer programming of generalized hydro ...
  • A. Ahmadi et al., “A Mixed-integer programming of multi-objective Hydro ...
  • UN, World population prospects: the ۲۰۰۸ revision, highlights ”, New ...
  • D. Connolly et al., “A review of computer tools for ...
  • A. Foley et al., “A long-term analysis of pumped Hydrostorageto ...
  • P. Ilak et al., “The impact of a wind variable ...
  • K. Wang et al., “Optimal coordination of wind-hydro-thermal Based on ...
  • E. Castronuovo and J. Lopes, “On the optimization of the ...
  • Z. Jianzhong et al., “Short-term hydro-thermal-wind complementary scheduling considering uncertainty ...
  • H. Pousinho, V. Mendes and J. Catalão, “A risk-averse optimization ...
  • J. Catalão, H. Pousinho and J. Contreras, “Optimal hydro scheduling ...
  • L. Wu, M. Shahidehpour and T. Li, “GENCO’s risk-Based maintenance ...
  • L. Wu, M. Shahidehpour and Z. Li, “GENCO’s risk-constrained hydro-thermal ...
  • Swedish Energy Agency, “Energy in Sweden ۲۰۱۰, Facts and Figures”, ...
  • H. Moghimi et al., “Risk constrained self-scheduling of Hydro-wind units ...
  • G. Shrestha, S. Kai and L. Goel, “An efficient stochastic ...
  • M. Li, Y. Li and G. Huang, “An interval Fuzzy ...
  • K. Meng et al., “Quantum inspired particle swarm optimization for ...
  • T. Li and M. Shahidehpour, “Dynamic ramping in unit commitment”, ...
  • M. Karami et al., “Mixed-integer programming of Security - constrained ...
  • A. Ahmadi, M. Charw and J. Aghaei, “Risk-constrained optimal strategy ...
  • H. Wei et al., “Short-term optimal operation of hydro – ...
  • G. Díaz, J. Coto and J. Aleixandre, “Optimal operation value ...
  • E. Akbari et al., “Stochastic programming based optimal bidding of ...
  • J. Xu et al., “Economic - environmental equilibrium Based optimal ...
  • S. Zabetian-Hosseini and M. Oloomi-Buygi, “How does large - scale ...
  • S. Mirjalili, “The Antlion Optimizer”, Adv. Eng. Soft., vol. ۸۳, ...
  • H. Dubey, M. Pandit and B. Panigrahi, “Hydro - thermal ...
  • A. Wijesinghe and L. Lai, “Small hydro power plant analysis ...
  • M. Baneshi and F. Hadianfard, “Techno - economic feasibility of ...
  • F. Li and J. Qiu, “Multi-objective optimization for Integrated hydro-photovoltaic ...
  • Z. Ding et al., “Performance analysis of a wind - ...
  • X. Wang et al., “Hydro - thermal - wind - ...
  • X. Wang et al., “Short–term hydro – thermal - wind- ...
  • A. Zakaria et al., “Uncertainty models for stochastic optimizatio in ...
  • L.Wu, M. Shahidehpour and T. Li, “Stochastic Security - constrained ...
  • L. Wu, M. Shahidehpour and T. Li, “Cost of reliability ...
  • N. Amjady, J. Aghaei and H. A . Shayanfar, “Stochastic ...
  • I. Damousis, A. Bakirtzis and P. Dokopolous, “Asolution to the ...
  • O. Nilsson and D. Sjelvgren, “Hydro unit start-up costs and ...
  • H. Daneshi et al., “Mixed- integer programming method to solve ...
  • M. AlRashidi and M. El-Hawary, “Hybrid particle swarm optimization approach ...
  • T. Li and M. Shahidehpour, “Price-based unit commitment : a ...
  • J. Arroyo and A. Conejo, “Optimal response of a thermal ...
  • Generalized Algebraic Modeling Systems (GAMS), [Online] Available : http://www.gams. com ...
  • http: //motor.ece.iit. edu / data / PBUC data .pdf. Also ...
  • http://motor.ece.iit.edu/data /۱۱۸bus_abreu. xls ...
  • http://motor.ece.iit.edu/data/۱۱۸_nonsmooth. xls ...
  • X. Yuan et al., “An extended NSGA-III for solution of ...
  • P. Biswas, P. Suganthan and G. Amaratunga, “Optimal power flow ...
  • M. Behnamfar, H. Barati and M. Karami, “Stochastic short - ...
  • X. Wang et al., “Improved multi - objective model and ...
  • S. Mandal, B. Das and N. Hoque, “Optimum sizing of ...
  • Z. Movahediyan and A. Askarzadeh, “Multi-objective optimization framework of a ...
  • E. Rakhshani, H. Mehrjerdi and A. Iqbal, “Hybrid Wind-Diesel- Battery ...
  • X. Shi et al., “Impacts of photovoltaic / wind turbine ...
  • O. Abedinia et al., “Optimal offering and Bidding Strategies of ...
  • L. Li et al., “Short -term wind power forecasting based ...
  • H. Khaloie et al., “Co-optimized bidding strategy of an integrated ...
  • A. Panda et al., “Hybrid power systems with emission Minimization ...
  • J. Lee, K. Aviso and R. Tan, “Multi-objective optimisation of ...
  • Y. Yin, T. Liu and C. He, “Day-ahead stochastic coordinated ...
  • A. Ioannou et al., “Multi-Stage stochastic optimization framework for power ...
  • F. Zhu et al., “Short-term stochastic optimization of a hydro-wind-pv ...
  • F. Alazemi and A. Hatata, “Ant-lion optimizer for optimum economic ...
  • F. Jabari et al., “Optimal short-term coordination of desalination, hydro ...
  • H. Siahkali, “Operation planning of wind farms with pumped storage ...
  • نمایش کامل مراجع