Security Constrained Optimal Redispatch Management in Balancing Markets

Date

2023-8-2

Author

Eren, Sinan

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A core function of each Transmission System Operator (TSO) is the procurement of ancillary services in real-time balancing markets, necessary for a stable and reliable operation of the system. In a balancing market, TSO controls the active power generation and manages congestions in the transmission network in the sense of single or multiple elements over-loadings or violations of the N-1 security criterion. Congestion management is achieved by rescheduling generation using mainly operators’ experiences. However, TSO has legal obligations to procure ancillary services in accordance to economic, transparent, non-discriminatory procedures. This thesis aims to develop an algorithm for TSO to decide the optimum redispatch in the sense of economy and security to eliminate transmission bottlenecks. The suggested algorithm considers the bidding strategies of power producers in balancing markets, physical constraints of generators, and transmission constraints. Single cost formulation for multiple generation units can be applied to the problem so that power plants whose generators locate at different voltage levels and virtual power plants of aggregators can be modeled. The problem is formulated as an optimal power flow to calculate both corrective and preventive actions. To obtain a robust application, state-dependent linearization techniques are applied to network constraints thanks to the nature of the close states of pre- and post-operating points of redispatch actions. Unlike the classical DC OPF formulation, reactive power flows and voltage magnitudes are considered in the optimization. Accuracy-enhancing approaches and strategies to minimize the number of control actions have been developed. The proposed algorithm is tested with standard test cases and a real large-scale electricity network. Benders Decomposition technique is utilized for solving security-constrained formulation; thus, large-scale optimization problems (such as those with more than 1M variables) can be solved in less than a minute. The developed application is deployed as a decision support system for a large-scale transmission network in real-time operation for a year, and it has been observed to produce more economical redispatches.

Subject Keywords

Security Constrained Optimum Power Flow, Redispatch in Balancing Market, Congestion Management, Network Linearization, Robust Optimization

URI

https://hdl.handle.net/11511/105118

Collections

Graduate School of Natural and Applied Sciences, Thesis