International Journal of Nonlinear Analysis and Applications

Reliability based planning and operation planning of thermal-wind units

Articles in Press

Document Type : Research Paper

Authors

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

10.22075/ijnaa.2024.34298.5119

Abstract

Today, the issue of planning and operation planning of thermal units (TUs) based on generation system reliability has become very important due to the restructuring process in power systems, load increment and distributed generation penetration on the demand side. This paper proposes a two-step approach to solve the aforementioned issue in the presence of wind farm renewable energy resources in the electricity market environment. In the first step, the optimal installation capacity of TUs is determined by the goal of providing annual peak load and being at the desired level of generation system risk using the loss of load probability analysis. Their economic dispatch and spinning reserve are determined in the second step. Expected energy not served is used for generation system reliability evaluation in the operation planning phase. Single contingencies of TUs are defined as system uncertainty. It is assumed that wind farm has constant capacity in the planning phase, and it generates active power (negative injection) as a function of wind speed at the installation region in the operation planning phase. Auto Recursive and Moving Average time series model is applied for wind speed estimation at different time intervals in the operation planning phase. The genetic algorithm has been used to solve this optimization problem. To validate the effectiveness of the proposed model, numerical studies and simulations are performed on the standard test generation system with 32 TUs and 1 wind farm. Finally, conceptual results have been expressed.

Keywords

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International Journal of Nonlinear Analysis and Applications

Articles in Press, Corrected Proof
Available Online from 04 November 2024
  • Receive Date: 05 April 2024
  • Accept Date: 26 June 2024