Solution approach for optimal power flow considering wind turbine and environmental emissions. Issue 2 (April 2022)

• Record Type: Journal Article
• Authors: Maheshwari, Ankur; Sood, Yog Raj
• Is Part Of: Wind engineering. Volume 46:Issue 2(2022)
• Page Start: 480
• Page End: 502
• Publication Date: 2022-04
• Subjects: Optimal power flow -- wind power forecasting -- ant lion optimization -- greenhouse gases -- carbon tax; Wind-pressure -- Periodicals; Winds -- Periodicals; Wind power -- Periodicals; Engineering meteorology -- Periodicals; Pression du vent; Vents; Énergie éolienne; Météorologie appliquée; Engineering meteorology; Wind power; Wind-pressure; Winds; Periodicals; 621.4505
• DOI: 10.1177/0309524X211035152
• Languages: English
• ISSNs: 0309-524X

Abstract

The power grid is changing expeditiously with the increasing penetration of renewable energy sources (RES). Optimal utilization of RES reduces the burden on the primary grid and makes the grid more resilient. Traditional optimal power flow (OPF) is a complex problem in power management systems, and the complexity further increases with the integration of RES due to their intermittency. This paper presents the complete formulation of the OPF model incorporating wind turbines (WT) and environmental emissions for proper scheduling, planning, and efficient operation of thermal generating units (TGU) using the Ant Lion Optimization (ALO) algorithm. The formulation of the OPF problem comprises forecasted active power generation of WT, depending on the real-time measurement and probabilistic wind speed models. The results are analyzed from the perspective of operating cost, voltage profile, and transmission power losses in the system. The OPF approach and the solution methodology are tested on the IEEE 30 and IEEE 57-bus systems. The effectiveness of the proposed ALO algorithm is evaluated against well-established algorithms like Particle Swarm Optimization and Teaching-learning-based optimization. The comparison emphasizes the effectiveness of the ALO approach for solving various OPF problems with complex and non-smooth objective functions.