Abstract
Stochastic production from wind power plants imposes additional uncertainty in power system operation. It can cause problems in load and generation balancing in the power system and can also cause congestion in the transmission network. This paper deals with the problems of congestion in the transmission network, which are caused by the production of wind power plants. An optimization model for corrective congestion management is developed. Congestions are relieved by re-dispatching several cascaded hydropower plants. Optimization methodology covers the optimization period of one day divided into the 24 segments for each hour. The developed optimization methodology consists of two optimization stages. The objective of the first optimization stage is to obtain an optimal day-ahead dispatch plan of the hydropower plants that maximizes profit from selling energy to the day-ahead electricity market. If such a dispatch plan, together with the wind power plant production, causes congestion in the transmission network, the second optimization stage is started. The objective of the second optimization stage is the minimization of the re-dispatching of cascaded hydropower plants in order to avoid possible congestion. The concept of chance-constrained programming is used in order to consider uncertain wind power production. The first optimization stage is defined as a mixed-integer linear programming problem and the second optimization stage is defined as a quadratic programming (QP) problem, in combination with chance-constrained programming. The developed optimization model is tested and verified using the model of a real-life power system.
Highlights
Electricity market liberalization and the increase in renewable generation investments (especially wind power plants (WPPs)) bring changes and challenges in transmission system operation
The optimization methodology developed consideration of uncertain wind power power plant plant (WPP) output [28,29,30,31], but it is yet to be used for solving problems of in this study is a combination of quadratic programming (QP) and chance-constrained programming
We present a developed optimization methodology whose objective is to minimize the re-dispatching of cascaded hydropower plants (HPPs) with the purpose of removing congestion in the transmission network caused by uncertainties of the wind power forecasts
Summary
Electricity market liberalization and the increase in renewable generation investments (especially wind power plants (WPPs)) bring changes and challenges in transmission system operation. Optimization problems of coordinated scheduling of HPPs and WPPs in transmission networks where congestion occurs were studied in References [24,25]. In these studies, the transmission network was not modeled in detail; instead, the radial connection between the area where HPPs and WPPs are located and the rest of the system was assumed. The concept of CC programming was used in optimization for the congestion in transmission networks with HPPs and WPPs. The optimization methodology developed consideration of uncertain WPP output [28,29,30,31], but it is yet to be used for solving problems of in this study is a combination of quadratic programming (QP) and chance-constrained programming. A short conclusion and comments for further research work are provided at the end of the paper
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
