Handling Multiple-Fuel Options in Economic Dispatch of Thermal Power Plants Through a Tight Model Applying Indicator Variables

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:International Transactions on Electrical Energy System vol. 2025 (2025)
المؤلف الرئيسي: Sharifzadeh, Hossein
منشور في:
John Wiley & Sons, Inc.
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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024 7 |a 10.1155/etep/1572487  |2 doi 
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045 2 |b d20250101  |b d20251231 
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100 1 |a Sharifzadeh, Hossein  |u Department of Electrical and Computer Engineering Hakim Sabzevari University Sabzevar Iran 
245 1 |a Handling Multiple-Fuel Options in Economic Dispatch of Thermal Power Plants Through a Tight Model Applying Indicator Variables 
260 |b John Wiley & Sons, Inc.  |c 2025 
513 |a Journal Article 
520 3 |a Thermal power plants play a central role in present power systems because of their high efficiency, fast startup capability, and flexibility to integrate the variability of renewable generations. These thermal units can utilize various fuels, including coal, natural gas, and oil, which enhances both the economic performance and security of the overall energy system. Representing the fuel cost functions of these units with multiple fuels (MFs) as binary decisions involves adding binary variables to the economic dispatch (ED) problem. The inclusion of these binary variables and nonlinear cost functions results in a complex NP-hard mixed-integer nonlinear programming (MINLP). This paper provides another perspective on the ED, where indicator variables represent the MF options and determine which cost functions should be set to zero. Based on this perspective, the paper builds a tight model to handle the indicator variables and solve the MINLP ED. Moreover, the paper introduces an iterative solution method with a bound-tightening technique to speed up the solution process. We conducted experimental studies using eight ED case studies with MF options involving up to 1280 generating units. The optimal costs obtained from these case studies demonstrate the effectiveness of the tight model and the iterative solution method for solving the MINLP ED problem. Furthermore, the proposed approach generally outperforms earlier algorithms in terms of solution quality and robustness. Finally, the tight model can speed up the solution process by 18%–45% compared with the standard formulation in the adopted case studies. 
653 |a Fuels 
653 |a Thermal power plants 
653 |a Cost function 
653 |a Thermoelectricity 
653 |a Power plants 
653 |a Complex variables 
653 |a Optimization 
653 |a Convergence 
653 |a Iterative solution 
653 |a Nonlinear programming 
653 |a Efficiency 
653 |a Case studies 
653 |a Mathematical programming 
653 |a Economics 
653 |a Thermal power 
653 |a Costs 
653 |a Decision making 
653 |a Flexibility 
653 |a Variables 
653 |a Algorithms 
653 |a Linear programming 
653 |a Natural gas 
653 |a Methods 
653 |a Mixed integer 
653 |a Power dispatch 
653 |a Electric power 
653 |a Economic 
773 0 |t International Transactions on Electrical Energy System  |g vol. 2025 (2025) 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3164853382/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3164853382/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3164853382/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch