GenCo's mid‐term optimal operation analysis: interaction of wind farm, gas turbine, and energy storage systems in electricity and natural gas markets. Issue 12 (17th May 2019)

• Record Type: Journal Article
• Authors: Ansari, Mostafa; Latify, Mohammad Amin; Reza Yousefi, Gholam
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 12(2019)
• Page Start: 2328
• Page End: 2338
• Publication Date: 2019-05-17
• Subjects: power generation planning -- wind power plants -- power markets -- gas turbines -- integer programming -- power generation economics -- linear programming; day‐ahead market -- daily spot market -- intra‐day mid‐term -- operation planning horizon -- energy arbitrage -- operation planning model -- GenCo's mid‐term optimal operation analysis -- wind farm -- gas turbine -- energy storage systems -- electricity -- natural gas markets -- optimised operation planning -- coordinated operation planning -- generation company -- battery -- electrical energy -- NG trades -- long‐term contracts -- spot markets; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.5910
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : In this study, optimised and coordinated operation planning of a generation company's (GenCo's) generation portfolio consisting of a wind farm, a gas turbine, and energy storage systems [battery and natural gas (NG) energy storage systems] is modelled. In this model, all the electrical energy (EE) and NG trades are performed through long‐term contracts and spot markets in a deregulated environment. It is assumed that EE is traded through day‐ahead market and bilateral contracts while NG is traded via a daily spot market in conjunction with baseline and intra‐day mid‐term contracts. The proposed framework enables the GenCo to maximise its profit in operation planning horizon by coordinating different types of contracts and energy arbitrage. The operation planning model is presented as a mixed‐integer linear programming problem. Five case studies are implemented in GAMS software to evaluate the effectiveness of the proposed model and analyse different factors affecting benefits of the GenCo.